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Tilburg University

Psychological burden in peripheral arterial disease

Smolderen, K.G.E.

Publication date:2009

Link to publication

Citation for published version (APA):Smolderen, K. G. E. (2009). Psychological burden in peripheral arterial disease: A call to action. [s.n.].

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Download date: 08. Jun. 2020

https://research.tilburguniversity.edu/en/publications/450971c1-60a1-4f30-964a-13cc3c1e29c2

Kim G.E. Smolderen

Psychological Burden in Peripheral Arterial Disease: A Call to Action

© Kim G.E. Smolderen, Tilburg 2009

Cover design & layout: Liesbet GoetschalckxArtwork cover: Marcel Goetschalckx

ISBN / EAN: 978-90-5335-208-3

Psychological Burden in Peripheral Arterial Disease: A Call to Action

PROEFSCHRIFTter verkrijging van de graad van doctor aan de Universiteit van Tilburg, op gezag van de rector magnificus, prof.dr. Ph. Eijlander, in het openbaar te verdedigen ten overstaan van een door het col-lege voor promoties aangewezen commissie in de aula van de Universiteit op vrijdag 23 oktober 2009 om 14.15 uur

door

Kim Germaine Emiel Smolderen,

geboren op 18 oktober 1980 te Turnhout, België.

PROMOTOR

Prof. Dr. Johan Denollet

COPROMOTORES

Dr. Annelies E. Aquarius

Dr. Patrick W. Vriens

PROMOTIECOMMISSIE

Prof. Dr. Jaap F. Hamming

Dr. Susanne S. Pedersen

Prof. Dr. Don Poldermans

Dr. François Pouwer

Prof. Dr. John A. Spertus

Dr. Joep A. Teijink

Financial support by The Netherlands Heart Foundation for the publication of this thesis is gratefully acknowledged.

CONTENTSChapter 1 Introduction 9

PART I THE NEED FOR A PAD-SPECIFIC HEALTH STATUS INSTRUMENT 29

Chapter 2 Further validation of the Peripheral Artery Questionnaire: results from a peripheral vascular surgery survey in The Netherlands

31

Chapter 3 Clinical validity of a disease-specific health status questionnaire: the Peripheral Artery Questionnaire

55

PART II THE NEED TO INCREASE AWARENESS OF THE PSYCHOLOGICAL BURDEN IN PERIPHERAL ARTERIAL DISEASE

79

Chapter 4 Depressive symptoms in peripheral arterial disease: a follow-up study on prevalence, stability, and risk factors

81

Chapter 5 Younger women with peripheral arterial disease are at increased risk of depressive symptoms

103

Chapter 6 Lower-leg symptoms in peripheral arterial disease are associated with anxiety, depression, and anhedonia

125

Chapter 7 Peripheral endovascular revascularization: associations between depressive symptoms and diminished health status benefits

149

Chapter 8 Type D personality and reduced benefit following exercise therapy in peripheral arterial disease

175

Chapter 9 Type D personality predicts mortality in peripheral arterial disease: a pilot study

195

PART III HOLDING UP A MIRROR: REFLECTIONS OF PATIENT-CENTERED RESEARCH IN CARDIAC DISEASE

213

Chapter 10 Impact of peripheral arterial disease on health status: a comparison with chronic heart failure

215

Chapter 11 The association of cognitive and somatic depressive symptoms with depression recognition and outcomes after myocardial infarction

241

Chapter 12 Discussion 273

Appendix Depression and screening cardiovascular events 299

Dutch summary 303

Acknowledgements 309

Publications 315

Chapter 1

Introduction

1

10 Chapter 1 - Introduction

Scope of the problem: peripheral arterial disease epidemiology, risk factors, and prognosis

Peripheral arterial disease (PAD) refers to a range of noncoronary arterial syndromes caused by an altered structure and function of the arteries that supply the brain, visceral organs, and the limbs. Numerous pathophysiologic processes can underlie PAD, but atherosclerosis is the disease process that is most commonly described to affect the peripheral arteries.1 Although PAD encompasses a broad range of disorders in which the peripheral arteries are affected, this thesis will limit its focus to PAD of the lower extremity arteries in which atherosclerosis is the underlying disease.

Both in epidemiologic registries and in clinical practice, the standard for the diagnosis of lower ex-tremity PAD is the non-invasive ankle-brachial index (ABI). An abnormal resting ABI is defined as ≤0.90 and indicates a hemodynamically-significant arterial stenosis. This definition of PAD has a sen-sitivity of approximately 95% for detecting arteriogram-positive PAD and an almost 100% specificity for identifying healthy individuals.2 In addition, exercise testing in combination with ABI measurement can be used as an adjunct diagnostic procedure when resting measures of the ABI are normal (in case of an isolated iliac stenosis). Exercise will induce a decrease in the ABI that can be detected in the immediate recovery period and, usually, a decrease in ABI of 15% is considered diagnostic of PAD.3 Both resting and post-exercise ABI values are strong predictors of overall mortality and cardiac death in PAD patients.4

Within lower extremity arterial disease, an important distinction should be made between patients that are unaware of their condition and have asymptomatic disease and patients that have symptomatic disease. The most typical presentation of symptomatic disease is intermittent claudication or pain during walking that is relieved upon rest. The majority of patients with PAD is asymptomatic or has atypical leg symptoms and may not be recognized as having systemic cardiovascular disease. Non-invasive PAD testing may be an important tool that allows for the early identification of patients with asymptomatic disease in the community and in populations at risk for PAD.1, 3 However, PAD patient populations represented in research and in clinical practice are typically patients with symptomatic PAD and findings resulting from these observations, will likely be an underestimation of the scope of the problem. Likewise, most of the PAD patients described in this thesis consulted a clinician for symptomatic disease or were patients with risk factors for vascular disease that received cardiovas-cular screening, which also included a diagnostic work-up for PAD. It is important to bear in mind

1

Psychological burden in peripheral arterial disease: a call to action 11

that, regardless of its symptomatic presentation, PAD patients with atherosclerosis as the underlying pathophysiologic condition, share the same risk factors, clinical path, and prognosis.

Peripheral arterial disease epidemiology

Total disease prevalence - including both asymptomatic and symptomatic disease - ranges from 3 -10% to 15-20% in patients aged 70 years and older.5-7 Disease prevalence depends on the used methodology, the age of the cohort that is studied, their risk profile, the presence of a concomitant manifestation of significant atherosclerosis, and the setting where patients are being studied. Over two-thirds of PAD patients present with asymptomatic disease or with atypical symptoms that do not meet the clinical criteria for intermittent claudication.8, 9 Prevalence rates of PAD among community-dwelling individuals are the same - if not higher – for women as compared with men,7, 9, 10 although presentation with typical intermittent claudication symptoms has been more frequently documented in men compared to women.11 Women are more likely to report atypical complaints, which makes them more vulnerable to be underdiagnosed and undertreated.12, 13 Finally, PAD prevalence rates are twice as high in non-Hispanic Blacks compared to Caucasians and prevalence rates of PAD are extremely high in populations with a high prevalence of atherosclerotic risk factors, including geriatric popula-tions, cardiac patients, renal transplant recipients, and brain infarction patients.14-16

Risk factors

Since atherosclerosis is the underlying pathophysiological condition for most cases of PAD, risk fac-tors common to all atherosclerotic diseases are also applicable to PAD, although the relative im-portance of individual risk factors may vary substantially for PAD compared to other cardiovascular conditions. Cigarette smoking is probably one of the most powerful etiologic risk factors for PAD. Smoking is associated with a 2- to 6- fold increased risk of PAD and this association is known to be dose-dependent with the risk being increased with the number of cigarettes smoked and the number of pack years.17-20 Other powerful risk factors that have been associated with PAD include Black ethnicity,7, 21 advanced age, and diabetes mellitus.17, 22 Furthermore, the association between hyper-tension, lipid abnormalities, elevated levels of homocysteïne, elevated levels of C-reactive protein, chronic renal insufficiency and PAD have been repeatedly demonstrated.1, 3, 17, 20, 23, 24


Prognosis

Since PAD is an indicator for the presence of systemic atherosclerotic disease throughout the vascu-lar system, it is not surprising that all PAD patients have an increased risk of experiencing ischemic events in other vascular beds. This risk is far higher than the risk of deteriorating to critical leg isch-emia or gangrene (Figure 1), with major amputation rates that are relatively rare (1 to 3.3% of patients with intermittent claudication will need an amputation over a 5-year period).1, 3, 11, 25 Coexistence of other cardiovascular conditions is common among PAD patients: rates up to 60 to 80% of PAD pa-tients having significant coronary artery disease of at least one coronary artery have been reported.26 In addition, about 12 to 15% of PAD patients presents with significant carotid artery stenosis.27, 28 Consequently, PAD patients will have high cardiovascular morbidity and mortality rates. The annual mortality rate in patients with lower extremity PAD is estimated to be 4 to 6%,29, 30 although more re-cent numbers indicate an event rate around 4 to 5% for the combined endpoint cardiovascular death, myocardial infarction, and stroke.26, 31-33

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PAD management: from Charcot to the latest TASC and AHA/ACC guidelines

Since its first description in 1858 by Jean-Martin Charcot34 to the latest TASC and AHA/ACC reports, PAD management guidelines have evolved at a great pace. Whereas a report in 1955 in Circulation35

still asserted that the disability in most patients with intermittent claudication is not profound and that smoking abstinence in PAD should be considered as unnecessary from the organic point of view as well as for emotional reasons, there is now a whole range of preventive strategies and interventions aimed at atherosclerotic risk reduction and alleviating patients’ burden. Recent guidelines recom-mend timely identification of PAD in certain risk groups in the population allowing for adequate treat-ment of atherosclerotic risk factors. Non-invasive screening for PAD is recommended in patients aged 50 to 69 who present with an atherosclerotic risk factor, in elderly (aged ≥70 years) and especially in patients with diabetes mellitus and in patients with atherosclerotic risk factors.

PAD management is primarily aimed at modification of atherosclerotic risk factors, relieving patients’ symptoms, and improving their functioning and quality of life. Key factors of atherosclerotic risk man-agement include smoking cessation, lipid lowering, diabetes and hypertension control, weight reduc-tion in obese patients, and antiplatelet therapy. Exercise rehabilitation programs – preferably super-vised exercise protocols - should be made available as part of the initial treatment for all patients with PAD. Patients that are offered the option of endovascular or surgical treatment should have significant disability, which either means that they are not capable of performing their normal work or that they have impairment in other activities that are important for their quality of life. In case revascularization is considered a treatment strategy, there should be a balance between risk of a specific intervention and the degree and durability of the improvement that can be expected from the invasive treatment. Other factors like inadequate response to exercise therapy or the presence of concurrent conditions that limit exercise (e.g., angina or chronic lung disease), and type of lesion should be considered as well in the decision to offer a patient revascularization.1, 3

2


Outcome assessment in PAD

About saving lives and patency rates

Although it is of unquestioned importance to evaluate the safety and success of PAD treatment strate-gies in terms of mortality rates, complications, and hemodynamic success rates; most of the strategies offered to PAD patients are aimed at relieving their symptoms and improving their daily functioning. However, objective criteria based on non-invasive assessment of hemodynamic blood flow or criteria for technical success do not necessarily correlate with patients’ symptoms or disease burden. The ABI is known to have weak to moderate correlations with health status measures and even walking distance scores have been shown to share little overlap with health status measures.36-39 Therefore, it is recommended to combine both measures of medical effectiveness (e.g., ABI, patency rates), the walking performance of a patient, their symptoms, their functioning, and the degree to which patients are satisfied with their level of functioning.39, 40

Patient-centered outcomes

Since PAD management strategies are aimed at relieving patients’ symptoms and improving their daily functioning and because objective PAD disease indices do not necessarily correlate with pa-tients’ functioning, there is a need to evaluate PAD treatment strategies from a patient’s perspective. Patient-centered outcomes can be used to evaluate patients’ symptoms, their functioning, and quality of life. Although the latest TASC guidelines3 recommend the use of patient-centered outcomes – preferably a validated disease-specific health status questionnaire – to evaluate success of treat-ment, this recommendation received a grading B, which means that this advice is currently based on well-conducted studies but that no good quality randomized clinical trials are available on this topic to further prioritize this recommendation. In addition, the few PAD-specific health status instruments that are available are relatively new and their development and validation process is still ongoing. Although psychometrically sound generic health status instruments like the Short-Form (SF) 36,41,

42 SF-12,43 or the EQ-5D44, 45 are ready for use in PAD patients, these instruments are mainly useful when one wants to compare health status across different disease populations. When only used

3


within a PAD population, generic instruments may lack sensitivity and responsiveness. The ultimate goal is to have a reliable, valid, and sensitive PAD-specific health status instrument to serve the differ-ent applications of patient-centered health status measures: they can be used as tools for monitoring patients in routine clinical care; they can be utilized when evaluating outcomes of clinical trials, or as tools for quality assessment and improvement. Patient-centered health status instruments could also be applied in the context of patient-centered medical decision making and when operationalizing and evaluating disease management programs.46

The importance of psychological factors for patient outcomes in PAD

Documenting PAD outcomes in an extensive way becomes crucial when one wants to improve the quality of PAD care. It will be important to discern vulnerable patient groups in order to be able to offer more stringent and tailored follow-up to those patients. Therefore, we will need to identify reli-able indicators of both objective PAD outcomes and patient-centered outcomes. As traditional PAD severity indices and clinical indicators are known to be only modestly and not consistently associated with outcomes in PAD,36, 37, 47 other determinants of PAD outcomes should also be considered. Re-cently, efforts have been made to explore the contribution of psychological factors on objective PAD outcomes like patency rates48 and cardiovascular morbidity and mortality,48 lower-extremity function-ing,50, 51 and patient-centered health outcomes like quality of life and health status.51-53 Psychological characteristics like depressive symptoms, perceived stress, and a distressed (Type D) personality are all strong correlates of PAD outcomes, even when adjusting for traditional PAD indices.48-54


The current research: addressing two needs

Rationale

The previous findings on the psychological burden of PAD are highly relevant and raise questions on how to improve daily clinical care in PAD. However, the need to alleviate the psychological burden in PAD has not been formulated by any of the current PAD guidelines, and has not been endorsed by a large part of the community involved in clinical PAD care and research. Although the need to evaluate PAD outcomes from a patient’s perspective has been advocated by the TASC community, the instru-ments for this purpose are currently lacking or need further development. These two observations – the need to develop and distribute appropriate disease-specific health status instruments, and the unawareness of the psychological burden in PAD patients – have led to the current research (See Figure 2 for a layout of this thesis).

The need for a PAD-specific health status instrument

Currently, there is no internationally agreed-upon PAD-specific health status instrument available. Previous efforts have been performed to develop such instruments: the German Claudication-Scale (CLAU-S), the Intermittent Claudication Questionnaire, the Vascular Quality of Life Questionnaire (VascuQoL), or the Walking Impairment Questionnaire (WIQ) are all good examples of question-naires that specifically address the impact of PAD-specific burden on patients’ functioning. Although disease-specific, most instruments suffer from a number of potential limitations: questionnaires are too long, only highlight the physical functioning of the patient, or different language versions are not available.

The Peripheral Artery Questionnaire (PAQ) is a new multidimensional disease-specific health status instrument that has recently been validated in PAD patients undergoing a peripheral revasculariza-tion procedure.55 This instrument may be a good alternative to the aforementioned concerns that have been raised in previously developed instruments. The PAQ evaluates PAD patients’ symptoms, symptom stability, physical function, social limitations, treatment satisfaction, and quality of life and

4


has excellent psychometric properties. Therefore, one of the aims of this thesis was to further validate a Dutch version of this instrument to make its wider use possible in The Netherlands (Chapter 2).56 In addition, its clinical validity was established against traditional disease severity indices, such as walking distance scores and a cardiac risk score (Chapter 3).57


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The need to increase awareness of the psychological burden in PAD

DepressionIn chapters 4 and 5, further epidemiological data are provided on depressive symptoms in PAD: its persistence across time (Chapter 4) and its high prevalence among younger women with PAD depression (Chapter 5) are major concerns in this disease population. Furthermore, the associations between depressive symptoms and health status in PAD have not been addressed before. Chapter 6 provides new evidence from PAD patients that underwent peripheral endovascular revasculariza-tion and demonstrates that depressive symptoms are consistently associated with diminished health status benefits following revascularization. Chapter 7 illustrates how intertwined mood states are with PAD symptom reporting, and how this may complicate PAD diagnosis.

PersonalityIt is important to realize that the tendency to experience certain mood states – such as depressive symptoms – may be nested in patients’ personality. A growing body of literature in cardiovascular pop-ulations is available on the distressed personality type or Type D personality. This personality profile identifies a subgroup of patients at risk of a broad range of adverse outcomes. Patients with a Type D personality tend to experience a whole range of negative feelings and tend to bottle up these feelings in social interaction.58 Previous findings already indicated that this personality profile is associated with impaired quality of life and health status in patients with PAD.53, 59 Chapters 8 and 9 elaborate on these findings and examine the association between Type D personality and outcomes following supervised exercise therapy in PAD patients (Chapter 8), and all-cause mortality (Chapter 9).

Holding up a mirror: reflections of patient-centered research in cardiac diseaseIn order to move forward in a field that needs a firm research tradition in terms of patient-centered outcomes and psychological factors, it is important to hold up a mirror and look at similar research within the realm of cardiovascular disease. The research tradition on patient-centered outcomes and psychological factors in cardiac populations is more developed as compared to the amount and ex-tent of research that has been done within PAD. Chapter 10 contrasts PAD patients’ health status with the health status of patients with chronic heart failure, a condition that is known to have devastating implications for patients’ health status. Contrasting both patient groups may yield new insights that can stress the need to increase awareness of PAD patients’ disease burden.


Whereas PAD researchers are currently doing ‘the field work’ and describing basic epidemiologic findings related to impaired mood and other patient-centered outcomes, research in patients with an acute myocardial infarction (AMI) are passing this stage. Innovative research on mechanisms that may underlie the association between depression and cardiovascular disease and studies question-ing the quality of care for depressed patients are currently underway in other cardiac populations. As an example of this movement, and to illustrate the different pace of development in cardiac and PAD research, Chapter 12 further breaks down the phenomenological diversity of depressive symptoms and discriminates between somatic and cognitive depressive symptoms and evaluates which symp-tom dimension facilitates depression recognition in hospitalized AMI patients, and examines which symptom dimension is most closely associated with AMI prognosis.


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21. Collins TC, Petersen NJ, Suarez-Almazor M, Ashton CM. The prevalence of peripheral arterial disease in a racially diverse population. Arch Intern Med 2003;163:1469-74.

22. Kullo IJ, Bailey KR, Kardia SL, Mosley TH, Jr., Boerwinkle E, Turner ST. Ethnic differences in peripheral arterial disease in the NHLBI Genetic Epidemiology Network of Arteriopathy (GENOA) study. Vasc Med 2003;8:237-42.

23. Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Plasma concentration of C-reactive protein and risk of developing peripheral vascular disease. Circulation 1998;97:425-8.

24. O’Hare AM, Vittinghoff E, Hsia J, Shlipak MG. Renal insufficiency and the risk of lower extremity peripheral arterial disease: results from the Heart and Estrogen/Progestin Replacement Study (HERS). J Am Soc Nephrol 2004;15:1046-51.

25. Weitz JI, Byrne J, Clagett GP, Farkouh ME, Porter JM, Sackett DL, et al. Diagnosis and treatment of chronic arterial insufficiency of the lower extremities: a critical review. Circulation 1996;94:3026-49.


26. A randomised, blinded, trial of clopidogrel versus aspirin in patients at risk of ischaemic events (CAPRIE). CAPRIE Steering Committee. Lancet 1996;348:1329-39.

27. Klop RB, Eikelboom BC, Taks AC. Screening of the internal carotid arteries in patients with peripheral vascular disease by colour-flow duplex scanning. Eur J Vasc Surg 1991;5:41-5.

28. Cheng SW, Wu LL, Ting AC, Lau H, Wong J. Screening for asymptomatic carotid stenosis in patients with peripheral vascular disease: a prospective study and risk factor analysis. Cardiovasc Surg 1999;7:303-9.

29. Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann TJ, et al. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med 1992;326:381-6.

30. McDermott MM, Feinglass J, Slavensky R, Pearce WH. The ankle-brachial index as a predictor of survival in patients with peripheral vascular disease. J Gen Intern Med 1994;9:445-9.

31. Steg PG, Bhatt DL, Wilson PW, D’Agostino R, Sr., Ohman EM, Rother J, et al. One-year cardiovascular event rates in outpatients with atherothrombosis. JAMA 2007;297:1197-206.

32. Yusuf S, Dagenais G, Pogue J, Bosch J, Sleight P. Vitamin E supplementation and cardiovascular events in high-risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med 2000;342:154-60.

33. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet 2002;360:7-22.

34. Charcot J. Sur la claudication intermittente observée dans un cas d’oblitération complète de l’une des artères iliaques primitives. CR Soc Biol Paris 2e série 1858;5:225-37.

35. Wessler S. Intermittent claudication. Circulation 1955;11:806-18.36. Long J, Modrall JG, Parker BJ, Swann A, Welborn MB, 3rd, Anthony T. Correlation between ankle-brachial

index, symptoms, and health-related quality of life in patients with peripheral vascular disease. J Vasc Surg 2004;39:723-7.

37. Barletta G, Perna S, Sabba C, Catalano A, O’Boyle C, Brevetti G. Quality of life in patients with intermittent claudication: relationship with laboratory exercise performance. Vasc Med 1996;1:3-7.

38. Arfvidsson B, Karlsson J, Dahllof AG, Lundholm K, Sullivan M. The impact of intermittent claudication on quality of life evaluated by the Sickness Impact Profile technique. Eur J Clin Invest 1993;23:741-5.

39. Currie IC, Wilson YG, Baird RN, Lamont PM. Treatment of intermittent claudication: the impact on quality of life. Eur J Vasc Endovasc Surg 1995;10:356-61.

40. Dormandy J. Management of PAD. J Vasc Surg 2000;31:s1-296.41. Ware JE, Jr., Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual frame-

work and item selection. Med Care 1992;30:473-83.42. McHorney CA, Ware JE, Jr., Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36): II. Psy-

chometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 1993;31:247-63.


43. Ware J, Jr., Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and pre-liminary tests of reliability and validity. Med Care 1996;34:220-33.

44. Brooks R. EuroQol: the current state of play. Health Policy 1996;16:53-72.45. Euroquol G. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy

1990;16:199-208.46. Spertus JA. Evolving applications for patient-centered health status measures. Circulation 2008;118:2103-

10.47. Breek JC, Hamming JF, De Vries J, Aquarius AE, Berge Henegouwen DP. Quality of life in patients with

intermittent claudication using the World Health Organisation (WHO) questionnaire. Eur J Vasc Endovasc Surg 2001;21:118-122.

48. Cherr GS, Wang J, Zimmerman PM, Dosluoglu HH. Depression is associated with worse patency and recurrent leg symptoms after lower extremity revascularization. J Vasc Surg 2007;45:744-50.

49. Cherr G, Zimmerman P, Wang J, Dosluoglu H. Patients with depression are at increased risk for secondary cardiovascular events after lower extremity revascularization. J Gen Intern Med 2008;23:629-34.

50. McDermott MM, Greenland P, Guralnik JM, Liu K, Criqui MH, Pearce WH, et al. Depressive symptoms and lower extremity functioning in men and women with peripheral arterial disease. J Gen Intern Med 2003;18:461-7.

51. Ruo B, Liu K, Tian L, Tan J, Ferrucci L, Guralnik JM, et al. Persistent depressive symptoms and functional decline among patients with peripheral arterial disease. Psychosom Med 2007;69:415-24.

52. Aquarius AE, Denollet J, Hamming JF, Van Berge Henegouwen DP, De Vries J. Type D personality and ankle brachial index as predictors of impaired quality of life and depressive symptoms in peripheral arterial disease. Arch Surg 2007;142:662-7.

53. Aquarius AE, Denollet J, de Vries J, Hamming JF. Poor health-related quality of life in patients with pe-ripheral arterial disease: Type D personality and severity of peripheral arterial disease as independent predictors. J Vasc Surg 2007;46:507-12.

54. Aquarius AE, De Vries J, Henegouwen DP, Hamming JF. Clinical indicators and psychosocial aspects in peripheral arterial disease. Arch Surg 2006;141:161.

55. Spertus J, Jones P, Poler S, Rocha-Singh K. The Peripheral Artery Questionnaire: a new disease-specific health status measure for patients with peripheral arterial disease. Am Heart J 2004;147:301-8.

56. Smolderen KG, Hoeks SE, Aquarius AE, Scholte op Reimer WJ, Spertus JA, van Urk H, et al. Further validation of the Peripheral Artery Questionnaire: results from a peripheral vascular surgery survey in The Netherlands. Eur J Vasc Endovasc Surg 2008;36:582-91.

57. Hoeks SE, Smolderen KG, Scholte Op Reimer WJ, Verhagen HJ, Spertus JA, Poldermans D. Clinical validity of a disease-specific health status questionnaire: the Peripheral Artery Questionnaire. J Vasc Surg 2009;49:371-7.


58. Denollet J. DS14: Standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosom Med 2005;67:89-97.

59. Aquarius AE, Denollet J, Hamming JF, De Vries J. Role of disease status and Type D personality in out-

comes in patients with peripheral arterial disease. Am J Cardiol 2005;96:996-1001.

Th e need for a PAD-specifi c health status instrument

Part I

Chapter 2

Further validation of the Peripheral Artery Questionnaire: results from a peripheral

vascular surgery survey in Th e Netherlands

2

32 Chapter 2 – Validation PAQ

Smolderen KG, Hoeks SE, Aquarius AE, Scholte op Reimer WJ, Spertus JA, van Urk H, Denollet J, Poldermans D. Further Validation of the Peripheral Artery Questionnaire: Results from a Peripheral Vascular Surgery Survey in The Netherlands. Eur J Vasc Endovasc Surg 2008;36:582-91.

ABSTRACT

Objectives: Peripheral arterial disease (PAD) is associated with adverse cardiovascular events and can significantly impair patients’ health status. Recently, marked methodological improvements in the measurement of PAD patients’ health status have been made. The Peripheral Artery Questionnaire (PAQ) was specifically developed for this purpose. We validated a Dutch version of the PAQ in a large sample of PAD-patients.

Design: Cross-sectional study.

Methods: The Dutch PAQ was completed by 465 PAD patients (70% men, mean age 65±10 years) participating in the Euro Heart Survey Programme. Principal component analysis and reliability analyses were performed. Convergent validity was documented by comparing the PAQ with EQ-5D scales.

Results: Three factors were discerned; Physical Function, Perceived Disability, and Treatment Satis-faction (factor loadings between 0.50 and 0.90). Cronbach’s α values were excellent (mean α=0.94). Shared variance of the PAQ domains with EQ-5D scales ranged from 3 to 50%.

Conclusions: The Dutch PAQ proved to have good measurement qualities; assessment of Physi-cal Function, Perceived Disability, and Treatment Satisfaction facilitates the monitoring of patients’ perceived health in clinical research and practice. Measuring disease-specific health status in a reli-able way becomes essential in times were a wide array of treatment options are available for PAD patients.


INTRODUCTION

Patients with peripheral arterial disease (PAD) constitute a high-risk group that needs stringent risk management and monitoring. Atherosclerotic processes underlying the disease affect different vas-cular beds simultaneously and predispose PAD patients to a variety of cardiovascular conditions such as claudication, myocardial infarction, and stroke.1 Increasing awareness of PAD and its con-sequences is especially needed in lower extremity PAD.2, 3 Apart from the disease burden itself,4 patients are confronted with multiple challenges due to the chronic nature of their disease and the multifaceted risk management and treatment options that are available to them. PAD patients should be routinely offered stringent risk management treating associated conditions such as hypertension and hyperlipidemia and, where indicated, endovascular procedures and surgery may bring relief.1 When it comes to the evaluation of medical therapy and existing revascularization procedures, quan-tifying PAD patients’ health status becomes an important issue.5 In fact, unlike the use of percutane-ous revascularization in the setting of an acute myocardial infarction where treatment may improve survival, the primary goal of revascularization procedures in PAD is to improve patients’ symptoms, function, and quality of life. In order to monitor patients’ health status in a reliable way, a sensitive disease-specific instrument is needed.

Recently, marked methodological improvements in the measurement of PAD patients’ health status (their symptoms, function, and quality of life) have been made. The psychometrically-sound Periph-eral Artery Questionnaire (PAQ), a disease-specific measure, was developed for this purpose.6 This instrument already proved to be useful to quantify improvement in health status after peripheral endo-vascular revascularization.5 However, the PAQ is only available in an English-language version, and the dimensions it measures were created to represent a clinical framework for quantifying patients’ health status and no empiric data supporting a patient-centered framework of the data has been performed. In order to make wider use of the PAQ possible, and to facilitate comparisons of PAD care and outcomes across different healthcare systems, we translated and validated a Dutch version of the PAQ in a large sample of Dutch PAD patients. More specifically, its validity and reliability was examined; convergent validity was tested against the EQ-5D, a standardized and widely used health outcome instrument.7, 8


METHODS

Participants and design

This study was part of a survey of clinical practice that was conducted between May and December 2004 in 11 hospitals across The Netherlands. The study was performed within the infrastructure of the Euro Heart Survey Programme, a project that evaluates the implementation of guidelines in daily clini-cal practice. Details of the participating centers and information about data collection are described elsewhere.9 All consecutive patients included in this survey were seen at the participating vascular surgery departments and were undergoing noncardiac elective vascular repair (endovascular or open procedures). Endovascular procedures included aortic endograft procedures and peripheral angio-plasties with and without stenting. Open procedures included: elective abdominal aortic surgery, ca-rotid endarterectomy, or infrainguinal arterial reconstruction. Patients below the age of 18 years and patients undergoing thoracic or brain surgery were excluded. The study was approved by the local ethics committees of the participating centers and all patients provided informed consent. After three years, information on vital status was obtained from the Civil Registries. All survivors were contacted to complete health status questionnaires.

Translation of the instrument

Forward and backward translation according the World Health Organization translation method was applied.10 Forward translations were made by two different translators whose native language was Dutch. These translations were combined for making a first agreed-upon forward translation. Two other members of the bilingual group then evaluated the quality of this first version regarding clar-ity and readability, and checked for further inconsistencies in the translation. Adaptations upon this evaluation were amended where appropriate. Next, monolingual individuals were asked to read the first forward translation version through and check for comprehensibility. These individuals were PAD patients recruited at the vascular outpatient clinic of a teaching hospital at the St. Elisabeth Hospital, The Netherlands. Comments of the monolingual group that were compatible with the meaning of the original document were inserted in the first forward translation version. Subsequently, a back-trans-lated version was obtained from a professional translator. Finally, the original and back-translated


documents were set side by side by the bilingual expert group and were reviewed for accuracy and equivalence of the translation. The final version of the Dutch translation is presented in Appendix A and information about the interpretation of scores is added in Appendix B.

Measures

Demographic and clinical variablesDemographic variables included age and sex. Patients’ medical history was documented by their hospital charts at the time of inclusion and included previous cardiovascular history (angina pectoris, myocardial infarction, heart failure, stroke/transient ischemic attack, arrhythmia, valvular disease, and previous revascularization), clinical risk factors (obesity, current smoking, hypertension, diabetes mellitus, renal insufficiency, and chronic obstructive pulmonary disease), and type of surgery (endo-vascular, open). Obesity was defined as having a Body Mass Index ≥30. Hypertension was recorded in patients presenting with a blood pressure of ≥140/90 mm Hg or who were treated for hyperten-sion. Diabetes mellitus was recorded if patients had a fasting glucose level of ≥7.0 mmol/l, or if they received treatment for diabetes. Renal insufficiency was recorded in patients with a serum creatinine level ≥2.0 mg/dl or in those who required dialysis.

Health statusDisease-specific health status was measured by the translated Dutch version of the PAQ; the instru-ment consists of 20 items with one item identifying the most symptomatic leg and the other items being answered along variable Likert response scales with equidistant gradations of response. Six domains were initially discerned in the PAQ: Physical Function, Symptoms, Symptom Stability, So-cial Limitation, Treatment Satisfaction, and Quality of Life.6 Given that the response categories are different across items, standardized scoring algorithms are applied to obtain scale scores ranging from 0 to 100, with high scores indicating good health status. A Summary score can be derived by combining the Physical Limitation, Symptom Frequency/Burden, Social Function, and Quality of Life domains.6 Previously, the instrument proved to be internally reliable (Cronbach’s α ranging from 0.80 to 0.94) and sensitive to clinical improvement in a study with patients undergoing elective percu-taneous peripheral revascularization.6 The convergent validity of the PAQ was established against existing health status questionnaires, including the Walking Impairment Questionnaire, the 36-item Short-Form Health Survey (SF-36), and an exercise treadmill test.6


To assess the convergent validity of the Dutch PAQ, the Dutch version of the EQ-5D was used, a standardized, generic instrument for describing and valuing health that was designed by the EuroQol Group (an international research network established in 1987).11, 12 The EQ-5D consists of a descrip-tive system that defines health along five dimensions and a visual analogue scale (EQ VAS). The five dimensions include: mobility, self-care, usual activities, pain or discomfort, and anxiety or depression. Each dimension can be rated on three levels, ranging from no problems to extreme problems and this score can be dichotomized. The EQ VAS asks respondents to rate their perception of their overall health on a vertical visual analogue scale with the endpoints ranging from 0 to 100 (0=‘worst imag-inable health state’ and 100=‘best imaginable health state’). In this study, the EQ VAS, the EQ-5D Index, and the dichotomous dimension scores (1=no problems, 0=some or extreme problems) were used in the analyses.13 The EQ-5D Index, a single summary index, calculated in this study was based on value sets derived from the Dutch population.14, 15

Statistical analysis

Baseline characteristics were described for the total sample and differences between responders and non-responders regarding these variables were examined using Student’s t-tests for continuous variables and Chi-square tests for dichotomous variables to assess for potential selection biases among those who participated in the current study. Missing values were also checked on item-level for the PAQ. To assess the suitability of the data for factor analysis, Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin measure of sampling adequacy were checked. Principal component analysis (PCA) was applied to determine the number of factors present in the PAQ. Factors with an eigen-value of 1.0 or more were retained for further investigation. Varimax rotation was used to interpret the pattern of loadings on the identified factors. Internal consistency of the factors was examined by performing reliability analyses. Cronbach’s alpha coefficients were used as indicators of internal con-sistency. Convergent validity of the PAQ was evaluated by correlating the extracted PAQ subscales and Summary score with the dichotomized subscales of the EQ-5D (point-biserial correlations), the EQ VAS, and the EQ-5D Index and by calculating the shared variance (r2 in %) between the PAQ and the EQ domains. In addition, PAQ Summary and domain scores were stratified by dichotomized EQ-5D subscales (Student’s t-tests). All analyses were performed using SPSS for Windows, version 14.0.1 (SPSS Inc., Chicago, Illinois).


RESULTS

The total study population consisted of 711 patients. Patient status could be determined in 701 (99%) of the original 711 respondents revealing that 149 (21%) of patients died in the 3-year period since the original survey. All 552 survivors were contacted to complete health status questionnaires (EQ-5D and PAQ), 465 (84%) of whom responded and comprised the final study group. The current sample (n=465) included 70% (n=323) male patients and the mean age was 65 years (SD=10 years). There were 245 (52.7%) of patients who underwent an endovascular procedure; 27 patients underwent an aortic endograft procedure, 216 peripheral angioplasties with or without stenting, and 2 others. A total of 220 (47.3%) patients underwent an open procedure; 22 patients underwent carotid endar-terectomy, infrainguinal arterial reconstruction n=101, abdominal aortic surgery n=88 and 9 other open procedures. Information about associated risk factors and procedure information is presented in Table 1.

Responders did not differ from non-responders, except for current smoking (52.9% in non-responders vs. 35.5% in responders, P=.002) and the presence of arrhythmia (16.1% in non-responders vs. 6.5% in responders, P=.002). The total of missings on the PAQ items ranged from 2.8 to 14.2 % (mean=5.5%), with the questions concerning treatment satisfaction yielding the largest amount of missings.


Table 1 – Characteristics of the total sample (n=465).

Abbreviations: TIA, transient ischemic attack; COPD, chronic obstructive pulmonary disease.

Demographics

Mean age (SD), year 65 (10)

Male sex, n (%) 323 (70)

Cardiovascular history, n (%)

Angina pectoris 73 (16)

Myocardial infarction 67 (14)

Heart failure 18 (4)

Stroke or TIA 69 (15)

Arrhythmia 30 (7)

Valvular disease 23 (5)

Previous revacularization 77 (17)

Clinical risk factors, n (%)

Obesity 57 (12)

Current smoker 165 (36)

Hypertension 177 (38)

Diabetes mellitus 96 (21)

Renal insufficiency 24 (5)

COPD 49 (11)

Surgical procedure, n (%)

Endovascular 245 (53)

Open 220 (47)


Measurement qualities of the PAQ

Factor analyses were performed on all PAQ items (except for the first item that indicates the most symptomatic leg) for the total sample (n=465). Three factors explained the most of the variance in the observed data (using the criterion of eigenvalues above 1.0) and therefore three factors were retained in the final model (Table 2). The first factor explained 58%, the second 10%, and the third 5%. A more than three factor solution did not significantly add to the interpretability of the data (explaining only residual variance between 4 and 0.4%). Items are presented and numbered according to the order of the original instrument. All PAQ items had factor loadings ranging from 0.50 to 0.90. Two out of three factors corresponded almost exactly with the original Physical Function domain (items 2a-2f) and exactly with the Treatment Satisfaction scale (items 7-9). The new factor was a combination of the original Symptom, Symptom Stability, Social Limitation, and Quality of Life domains (items 3-13c). This new domain was called ‘Perceived Disability’ because these items require patients to evaluate their disabilities. Items with double loadings (4, 11, 13 a, b, c) were allocated according to their original domain in order to preserve the ‘clinical’ framework of the original instrument (Table 2).6

Table 2 – Sample pattern matrices of PAQ scale Items as indicated by principal component analyses.*

*Varimax rotation; loadings of items assigned to a factor are presented in bold face.

Total (n=465)

Factor IPhysicalFunction

Factor II PerceivedDisability

Factor III Treatment

Satisfaction

Physical Function2a-Walking around your home 0.70 0.34 0.19

2b-Walking 1-2 blocks on level ground 0.85 0.30 0.16

2c-Walking 1-2 blocks up a hill 0.88 0.22 0.19

2d-Walking 3-4 blocks on level ground 0.88 0.24 0.15

2e-Hurrying or jogging 0.87 0.15 0.20

2f-Vigorous work or exercise 0.87 0.19 0.19

Perceived Disability

3-Symptoms of PAD have changed 0.29 0.66 0.01

4-How often PAD symptoms 0.54 0.54 0.31

5-How much has PAD bothered you 0.55 0.63 0.31

6-Awakened with PAD symptoms 0.26 0.56 0.28

10-Limited enjoyment of life 0.42 0.63 0.42

11-Spend rest of life with PAD like it is now 0.41 0.50 0.50

12-Felt discouraged or down in the dumps 0.38 0.62 0.40

13a-Limited participation in hobbies, recreation 0.59 0.57 0.32

13b-Limited participation in visiting family, friends 0.56 0.59 0.18

13c-Limited participation in working or doing household chores

0.62 0.56 0.23

Treatment Satisfaction

7-Satisfied that everything possible is being done 0.19 0.21 0.85

8-Satisfied with explanations 0.14 0.10 0.90

9-Satisfied with current treatment 0.19 0.21 0.85


Reliability was documented using Cronbach’s α; Cronbach’s α for the Physical Function domain was 0.95, for the Perceived Disability domain 0.93, and for the Treatment Satisfaction domain 0.91. The Cronbach’s α for the Summary scale was 0.96. Mean inter-item correlation for the Physical Function domain was 0.76, for the Perceived Disability 0.58, for Treatment Satisfaction 0.78, and for the Sum-mary score 0.71.

Table 3 – Correlation matrix of the PAQ scales and EQ-5D scales (n=465).

*All correlations were significant at the 0.01 level. Abbreviations: PAQ, Peripheral Artery Questionnaire; EQ-5D, EuroQol, VAS, visual analogue scale.

Correlation matrix*

PAQPhysicalFunction

PAQPerceivedDisability

PAQTreatment

Satisfaction

PAQSummary

Score

PAQ

Physical Function -

Perceived Disability 0.78 -

Treatment Satisfaction 0.43 0.60 -

Summary Score 0.96 0.93 0.54 -

EQ-5D

Mobility 0.66 0.59 0.36 0.64

Daily Activities 0.67 0.65 0.35 0.66

Self Care 0.40 0.38 0.18 0.38

Pain 0.61 0.61 0.42 0.62

Anxiety/Depression 0.32 0.38 0.17 0.35

EQ-5D Index 0.65 0.67 0.38 0.66

EQ-VAS 0.70 0.71 0.47 0.71


Convergent validity of the PAQ

Correlations between the PAQ subscales, PAQ Summary score, and the dichotomized subscales of the EQ-5D, the EQ VAS, and the EQ-5D Index are presented in Table 3. Shared variance between the PAQ Physical Function domain and the EQ-5D scales ranged from 10 to 49%. The shared variance of the Perceived Disability domain scores of the PAQ and the EQ-5D scores ranged from 14 to 50%. The Treatment Satisfaction domain and the EQ-5D domains only shared 3 to 22% of variance. The shared variance between the Summary PAQ score and the EQ-5D scores ranged from 12 to 50%. The intercorrelations of the PAQ are also presented in Table 3 (shared variance between 18 and 92%). The intercorrelations with the Treatment Satisfaction scale, were relatively smaller (0.43 to 0.60) as compared with the intercorrelations of the other domains and the Summary score (0.78-0.96). Mean PAQ Summary scores and PAQ domain scores were significantly different (P<.0001) for high vs. low health status patients groups that were created by stratifying the total sample according to the five dichotomized subscales of the EQ-5D (Figure 1).


Figure 1 – Mean PAQ domain and Summary scores and standard deviations stratified by di-chotomized EQ-5D subscales (n=465). All differences were significant at the P<.0001 level. (1) Mobility, (2) Daily Activities, (3) Self Care, (4) Pain, (5) Anxiety/Depression.

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DISCUSSION

In order to make wider use of the PAQ possible, the questionnaire was translated into Dutch and validated in a study of Dutch PAD patients that was performed within the infrastructure of the Euro Heart Survey. It is the first translated version of the PAQ that was developed and the first study that evaluated its factorial structure within a relatively large study sample. A high response rate and the missing analysis on item-level showed that the PAQ was well accepted in the current sample of PAD patients. Unlike in the original instrument, three factors were discerned in the Dutch version of the PAQ, explaining most of the variance in the observed data. Two factors overlapped completely with the previously proposed Physical Function and Treatment Satisfaction scales of the original instru-ment. The other original domains (Symptom, Symptom Stability, Social Limitation, and Quality of Life) were combined in a new domain, which we labeled the Perceived Disability domain in our study. As we chose to stay close to the clinically interpretable domains that were defined in the original instru-ment, we accordingly allocated double-loaded items. Future studies therefore need to replicate our work in both American and European samples to get an internationally agreed-upon factor structure. The three domains identified in this study were internally reliable. The convergent validity was es-tablished using a well standardized generic health status questionnaire, the EQ-5D.7 Convergent validity of the PAQ domains was documented by medium to large correlations with the EQ-5D and by comparisons of the mean scores of the PAQ scales with the stratified EQ-5D domains. Both the intercorrelations of the PAQ domains and the correlations of the Treatment Satisfaction domain with the EQ-5D scales pointed to the uniqueness of the Treatment Satisfaction domain. Intercorrelations of the PAQ domains Perceived Disability and Physical Function were all high, indicating that the domains were strongly related to the construct that the questionnaire purported to measure, namely disease-specific health status.

Measuring disease-specific health status in a reliable way becomes essential in times were a wide array of treatment options are available for PAD patients. Recent technological advances have also resulted in a shift from open surgical procedures toward lower-morbidity catheter-based interventional therapies.16, 17 Although the use of these catheter-based interventions has increased significantly, the results regarding long-term patency rates of these interventions are mixed.18 Due to the variety in treatment options and their variable success rates, PAD management has become a complex and challenging task. Treatment should therefore be tailored to the individual patient and should take into account the patients’ perspective. To facilitate such discussions with patients, patient-based outcomes


also need to be included in randomized trials evaluating revascularization procedures and medication use in PAD patients. Generic health status instruments are not sensitive enough to provide clinicians and researchers with useful information that makes adequate evaluation of PAD treatments pos-sible.6, 19, 20 Several disease-specific health status measures are developed for this purpose, with the PAQ being an excellent example of a valid and sensitive instrument that could be used both in clinical practice and as a treatment outcome in clinical PAD trials.5, 6

The term ‘health status’ was chosen to refer to the construct that the PAQ intends to measure. How-ever, the items that are contained in the PAQ do not all fully correspond with the definition of health status: “physical, mental, and social functioning assessment, but without the subjective evaluation of the patient”.21 The questionnaire is actually a mixture of items that deal with patients’ health status and items that assess quality of life, with quality of life referring to patients’ personal evaluation of their functioning, disease, and treatment.22, 23

The Physical Function domain of the PAQ is an example of a scale measuring health status; it indi-cates whether PAD caused limitations and classifies the levels of such limitations.22 In the second do-main, called Perceived Disability in our study, a more subjective and evaluative character is attributed to items 10 to 13c (e.g., If you had to spend the rest of your life with your PAD the way it is right now, how would you feel about this?). The third domain in our study also refers to the personal evaluation of the treatment that the patient received and is therefore more related to the genuine quality of life concept.23 For clinical decision making, both health status or the registration of limitations, and quality of life, the extent to which these limitations actually hamper the patient, need to be considered and in this respect, the PAQ may offer insight in both. Other disease-specific outcome measures that are available suffer from predominantly focussing on the registration of limitations and do not stress the subjective experience of the disease and its limitations. The Walking Impairment Questionnaire, for example, only assesses the degree of physical limitation that the PAD patient experiences24 and although the developers of the Intermittent Claudication Questionnaire claim to measure quality of life, thirteen out of sixteen items only register limitations with physical, mental and social functioning and do not evaluate the degree of dissatisfaction with these limitations.25 The Vascular Quality of Life Questionnaire, on the other hand, contains items that tap both the patients’ health status and quality of life, but the instrument contains both questions for PAD patients with intermittent claudication and critical leg ischemia, making this instrument more generic.26


This study has some limitations that should be considered when interpreting our results. The most important limitation is the cross-sectional nature of this study. We only assessed patients’ health status with the PAQ on a single point of time and issues regarding reproducibility and sensitivity to change were not examined. On the other hand, previous studies with the PAQ convincingly showed that the instrument had a good test-retest reliability and that the instrument was sensitive to clinical improvement.5, 6 Another limitation is that our study population only consisted of PAD patients that un-derwent vascular surgery, which may limit the generalizability of scores to PAD patients that received conservative treatment. In spite of these limitations, potential strengths of our study were the large sample size and the fact that our study population consisted of patients of different hospitals across The Netherlands. Furthermore, this study was the first to extensively document on the factorial valid-ity of the PAQ and was able to reduce the number of factors from six to three, further facilitating its use in clinical practice.

In sum, the Dutch version of the PAQ was found to be a reliable and valid instrument to assess the health status of PAD patients. In contrast with the six domains of the original instrument, a three-factor solution was sufficient to explain most of the variance in the health status scores of the present study. The next step is to perform additional research to establish the validity of the PAQ with relevant clinical indices, such as walking performance and standardized disease-specific risk classifications, and to monitor the performance of the questionnaire in evaluating the benefit of PAD treatments, as perceived by the individual patient. These efforts should all contribute to the tailor-made management of PAD patients, in this era of multifaceted risk management and treatment options that are available to them.


REFERENCES


2. McDermott MM, Hahn EA, Greenland P, Cella D, Ockene JK, Brogan D, et al. Atherosclerotic risk fac-tor reduction in peripheral arterial diseasea: results of a national physician survey. J Gen Intern Med 2002;17:895-904.

3. Al-Omran M, Lindsay TF, Major J, Jawas A, Leiter LA, Verma S. Perceptions of Canadian vascular sur-geons toward pharmacological risk reduction in patients with peripheral arterial disease. Ann Vasc Surg 2006;20:555-63.

4. Aquarius AE, De Vries J, Henegouwen DP, Hamming JF. Clinical indicators and psychosocial aspects in peripheral arterial disease. Arch Surg 2006;141:161-6.

5. Safley DM, House JA, Laster SB, Daniel WC, Spertus JA, Marso SP. Quantifying improvement in symptoms, functioning, and quality of life after peripheral endovascular revascularization. Circulation 2007;115:569-75.


7. Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001;33:337-43.

8. Kind P. The EuroQol instrument: an index of health related quality of life. In: Spilker B, editor. Quality of Life and Pharmacoeconomics in Clinical Trials. 2nd ed. Philadelphia, PA: Lippincott-Raven Publishers; 1996. p. 191-201.

9. Hoeks SE, Scholte op Reimer WJ, Lenzen MJ, van Urk H, Jorning PJ, Boersma E, et al. Guidelines for cardiac management in noncardiac surgery are poorly implemented in clinical practice: results from a peripheral vascular survey in The Netherlands. Anesthesiology 2007;107:537-44.

10. WHOQOLgroup. Development of the WHOQOL: rationale and current status. Int J Ment Health 1994;23:24-56.

11. Brooks R. EuroQol: the current state of play. Health Policy 1996;37:53-72.12. EuroQol--a new facility for the measurement of health-related quality of life. The EuroQol Group. Health

Policy 1990;16:199-208.13. EQ-5D value sets: Inventory, comparative review and user guide. Eds. Szende A, Oppe M, Devlin N.

EuroQoL Group Monographs Volume 2. Springer, 2006. 14. Lamers LM, McDonnell J, Stalmeier PF, Krabbe PF, Busschbach JJ. The Dutch tariff: results and argu-

ments for an effective design for national EQ-5D valuation studies. Health Econ 2006;15:1121-32.


15. Dolan P. Modelling valuations for health states: the effect of duration. Health Policy 1996;38:189-203.16. Anderson PL, Gelijns A, Moskowitz A, Arons R, Gupta L, Weinberg A, et al. Understanding trends in inpa-

tient surgical volume: vascular interventions, 1980-2000. J Vasc Surg 2004;39:1200-8.17. White CJ, Gray WA. Endovascular therapies for peripheral arterial disease: an evidence-based review.

Circulation 2007;116:2203-15.18. Beckman JA. Peripheral endovascular revascularization: some proof in the pudding? Circulation

2007;115:550-2.19. de Vries M, Ouwendijk R, Kessels AG, de Haan MW, Flobbe K, Hunink MG, et al. Comparison of generic

and disease-specific questionnaires for the assessment of quality of life in patients with peripheral arterial disease. J Vasc Surg 2005;41:261-8.

20. Mehta T, Venkata Subramaniam A, Chetter I, McCollum P. Assessing the validity and responsiveness of disease-specific quality of life instruments in intermittent claudication. Eur J Vasc Endovasc Surg 2006;31:46-52.

21. De Vries J, Drent M. Quality of life and health status in interstitial lung diseases. Curr Opin Pulm Med 2006;12:354-8.

22. Hamming JF, De Vries J. Measuring quality of life. Br J Surg 2007;94:923-4.23. The World Health Organization Quality of Life Assessment (WHOQOL): development and general psycho-

metric properties. Soc Sci Med 1998;46:1569-85.24. Regensteiner JG, Hiatt WR. Current medical therapies for patients with peripheral arterial disease: a criti-

cal review. Am J Med. 2002;112:49-57.25. Chong PF, Garratt AM, Golledge J, Greenhalgh RM, Davies AH. The intermittent claudication question-

naire: a patient-assessed condition-specific health outcome measure. J Vasc Surg 2002;36:764-71; dis-cussion 863-4.

26. Morgan MB, Crayford T, Murrin B, Fraser SC. Developing the Vascular Quality of Life Questionnaire: a new disease-specific quality of life measure for use in lower limb ischemia. J Vasc Surg 2001;33:679-87.

De volgende vragen hebben betrekking op verstoppingen in de bloedvaten in uw lichaam, in het bijzonder de benen, en hoe dat uw leven zou kunnen beïnvloeden. Wilt u a.u.b. de volgende vragen lezen en beantwoorden. Er zijn geen juiste of foute antwoorden. Duidt u a.u.b. het antwoord aan dat het beste op u van toepassing is.

1. Verstoppingen in de bloedvaten, vaak perifeer vaatlijden genoemd, treft verschillende mensen op verschillende manieren. Sommigen voelen krampen of pijn terwijl anderen vermoeidheid voelen. Welk been (of bil) veroorzaakt voor u het meest ernstige ongemak, vermoeidheid, pijn, zeurende pijn of krampen?

het rechterbeen

(of bil) het linkerbeen (of

bil) beide zijn gelijk geen van beide

□ □ □ □

2. Bekijkt u a.u.b. onderstaande lijst en geef aan in welke mate u beperkt was door uw perifeer vaatlijden (ongemak, vermoeidheid, pijn, zeurende pijn of krampen in uw kuiten (of billen) in de afgelopen 4 weken.

Plaatst u a.u.b. een X in één hokje op elke lijn.

Activiteit

Ernstig beperkt

Nogal beperkt

Matig beperkt

Licht beperkt

Helemaal niet

beperkt

Beperkt door andere redenen of heb de

activiteit niet uitgevoerd

a. Rondlopen in huis

□

□

□

□

□

□

b. 100 à 200 meter lopen

op een vlakke ondergrond

□

□

□

□

□

□

c. 100 à 200 meter bergop

lopen

□

□

□

□

□

□

d. 300 à 400 meter op een vlakke ondergrond lopen

□

□

□

□

□

□

e. Haasten of joggen (alsof u de bus moet halen)

□

□

□

□

□

□

f. Zwaar werk of lichamelijke inspanning

□

□

□

□

□

□

3. Vergeleken met 4 weken geleden, zijn uw klachten die te maken hebben met uw perifeer vaatlijden (ongemak, vermoeidheid, pijn,

zeurende pijn of krampen in uw kuiten (of billen) veranderd? Mijn klachten zijn...

Veel verergerd Een beetje verergerd

Onveranderd gebleven

Een beetje verbeterd

Veel verbeterd Ik heb geen klachten gehad in

de afgelopen 4 weken

□ □ □ □ □ □

4. In de afgelopen 4 weken, hoeveel keer had u ongemak, vermoeidheid, pijn, zeurende pijn of krampen in uw kuiten (of billen)?

Altijd Meerdere keren per dag

Minimaal 1 keer per dag

3 of meer keer per week, maar

niet elke dag

1 à 2 keer per week

Minder dan 1 keer per week

Geen enkele keer in de

afgelopen 4 weken

□ □ □ □ □ □ □

Appendix A – The Dutch version of the Peripheral Artery Questionnaire.


5. In de afgelopen 4 weken, hoeveel hinder heeft uw ongemak, vermoeidheid, pijn, zeurende pijn of krampen in uw kuiten (of billen) u bezorgd?

Het bezorgde me...

Ernstige hinder Matige hinder Enigszins hinder Lichte hinder

Helemaal geen hinder

Ik heb geen ongemak in mijn

benen gehad □ □ □ □ □ □

6. In de afgelopen 4 weken, hoe vaak bent u wakker geworden met pijn, zeurende pijn of krampen in uw benen of voeten?

Elke nacht 3 of meer keer per week, maar niet

elke nacht

1 à 2 keer per week

Minder dan 1 keer per week

Nooit in de afgelopen 4 weken

□ □ □ □ □

7. Hoe tevreden bent u dat al het mogelijke voor u wordt gedaan om uw perifeer vaatlijden te behandelen?

Helemaal niet tevreden

Grotendeels ontevreden

Een beetje tevreden

Grotendeels tevreden

Helemaal tevreden

□ □ □ □ □

8. Hoe tevreden bent u met de uitleg die uw dokter u heeft gegeven over uw perifeer vaatlijden?



Een beetje tevreden


Helemaal tevreden

□ □ □ □ □

9. Over het algemeen, hoe tevreden bent u over de huidige behandeling van uw perifeer vaatlijden?



Een beetje tevreden


Helemaal tevreden

□ □ □ □ □

10. In de afgelopen 4 weken, hoeveel heeft uw perifeer vaatlijden u beperkt in uw levensvreugde?

Het heeft mijn levensvreugde

heel veel beperkt

Het heeft mijn levensvreugde veel beperkt

Het heeft mijn levensvreugde matig beperkt

Het heeft mijn levensvreugde een

beetje beperkt

Het heeft mijn levensvreugde niet

beperkt □ □ □ □ □

11. Als u de rest van uw leven verder moest leven met uw perifeer vaatlijden zoals het op dit ogenblik is, hoe zou u zich hierover

voelen?



Een beetje tevreden


Helemaal tevreden

□ □ □ □ □


12. In de afgelopen 4 weken, hoe vaak heeft u zich ontmoedigd gevoeld of in de put gezeten vanwege uw perifeer vaatlijden?

Ik voelde me zo

heel de tijd Ik voelde me zo

meestal Ik voelde me soms

zo Ik voelde me

zelden zo Ik voelde me nooit

zo □ □ □ □ □

13. In hoeverre beïnvloedt uw perifeer vaatlijden uw levensstijl? Geef aan hoe uw ongemak, vermoeidheid, pijn, zeurende pijn of krampen in uw kuiten (of billen) u van deelname aan de volgende activiteiten hebben beperkt in de afgelopen 4 weken.

Plaatst u a.u.b. een X in één hokje op elke lijn.

Activiteit

Ernstig beperkt

Nogal beperkt

Matig beperkt

Licht beperkt

Helemaal niet

beperkt

Niet van toepassing of nam niet deel door

andere redenen

a. Hobby’s, ontspannende activiteiten

□

□

□

□

□

□

b. Familie of vrienden gaan

bezoeken

□

□

□

□

□

□

c. Werken of huishoudelijke

taken verrichten

□

□

□

□

□

□


APPENDIX B – Interpretation of raw scores – patients undergoing vascular surgery in The Netherlands (n=465). The following table can be used for the interpretation of raw scores on the PAQ scales.

Mean (SD) 33 Percentile cut-off scores

to indicate poor health status

Physical Function 56.4 (33.5) ≤33

Perceived Disability 67.2 (25.9) ≤57

Treatment Satisfaction 77.4 (27.5) ≤75

Summary Score 62.0 (28.2) ≤47

Chapter 3

Clinical validity of a disease-specifi c health status questionnaire:

the Peripheral Artery Questionnaire

3

56 Chapter 3 – Clinical validity PAQ

Hoeks SE, Smolderen KG, Scholte op Reimer WJM, Spertus JA, Verhagen HJM, Poldermans D. Clinical validity of a disease-specific health status questionnaire: the Peripheral Artery Questionnaire. J Vasc Surg 2009;49:371-7.

ABSTRACT

Background: Measuring patient-centered outcomes is becoming increasingly important in patients with peripheral arterial disease (PAD), both as a means of determining the benefits of treatment and as an aid for disease management. In order to monitor health status in a reliable and sensitive way, the disease-specific measure Peripheral Artery Questionnaire (PAQ) was developed. However, to date, its correlation with traditional clinical indices is unknown. The primary aim of this study was to better establish the clinical validity of the PAQ by examining its association with functional indices re-lated to PAD. Furthermore, we hypothesized that the clinical validity of this disease-specific measure is better as compared with the EQ-5D, a standardized generic instrument.

Methods: Data on 711 consecutive PAD patients undergoing surgery were collected from 11 Dutch hospitals in 2004. At 3-year follow-up, questionnaires including the PAQ, EQ-5D and Visual Analogue Scale (EQ VAS) were completed in 84% of survivors. The PAQ was analyzed according to three domains, as established by a factor analysis in the Dutch population, and the Summary score. Base-line clinical indices included the presence and severity of intermittent claudication (IC) and the Lee Cardiac Risk Index.

Results: All three PAQ domains (Physical Function, Perceived Disability, Treatment Satisfaction) were significantly associated with IC symptoms (P values <.001-.008). Patients with claudication had significant lower PAQ Summary scores as compared with asymptomatic patients (58.6±27.8 vs. 68.6±27.8, P≤.001). Furthermore, the PAQ Summary score and the subscale scores for Physical Functioning and Perceived Disability demonstrated a clear dose-response relationship for walking distance and the Lee Risk Index (P values <.001-.031). With respect to the generic EQ-5D, the EQ-5D Index was associated with IC (0.81±0.20 vs. 0.76±0.24, P=.031) but not with walking distance (P=.128) nor the Lee Risk Index (P=.154). The EQ VAS discriminated between the clinical indices (P values <.01), although a clear dose-response relationship was lacking.


Conclusions: The clinical validity of the PAQ proved to be good as the PAQ subscales discriminated well between patients with or without symptomatic PAD and its severity as defined by walking dis-tance. Furthermore, the PAQ subscales were directly proportional to the presence and number of risk factors relevant for PAD. For studying outcomes in PAD patients, the disease-specific PAQ is likely to be a more sensitive measure of treatment benefit as compared with the generic EQ VAS, although the latter may still be of value when comparing health status across different diseases. Regarding disease management, we advocate the use of the disease-specific PAQ as its greater sensitivity and validity will assist its translation into clinical practice.


INTRODUCTION

Peripheral arterial disease (PAD) is a common chronic condition and is associated with increased car-diovascular morbidity and mortality.1 The global aging phenomenon will further increase the burden of cardiovascular diseases, including PAD.2 It is well accepted that PAD adversely affects patients’ health status and quality of life (QoL).3 Patients not only perceive that their physical functioning is affected by lower extremity symptoms, but a PAD diagnosis and its associated symptoms also affect patients’ psychological well-being and mental health.4-6

The primary treatment goals of patients with PAD are to relieve pain, to improve health status and QoL, and to prolong survival. Measuring sensitive patient-centered outcome measures is becoming increasingly used in order to quantify the benefits of different treatment strategies and their cost-effectiveness.7 From a methodological perspective, these measures are important because the dis-criminative power of mortality as an outcome measure is poor, especially in PAD where mortality is more often due to the associated coronary and cerebrovascular disease rather than the PAD itself. As such, treatment of PAD is more often directed towards the goal of improving symptoms and its as-sociated health impact, rather than survival. In addition to using health status in outcomes research, health status measurements can be used in disease management as a tool to identify patients who are suffering more from their PAD or who are at higher risk for adverse outcomes.8 Identification of these high-risk patients may lead to more aggressive treatment and more intensive follow-up.

Health status and QoL can be assessed using either generic or disease-specific instruments. Avail-able data suggest a better construct validity of disease-specific instruments as compared with generic instruments.9 Key advantages of disease-specific instruments are the focus on specific symptoms of a disease and their correspondingly greater sensitivity and responsiveness to clinical changes. Furthermore, the information received from disease-specific instruments can also be more easily translated into clinical practice as compared with information derived from generic questionnaires. On the other hand, advantages of using generic instruments are their simplicity and the ability of compar-ing patients’ health status across different diseases.

In order to monitor health status in a reliable way, a new disease-specific measure, the Peripheral Artery Questionnaire (PAQ), was developed in US patients undergoing percutaneous peripheral revascularization and afterwards translated and validated in Dutch using a vascular surgery popula-


tion in The Netherlands.10, 11 Although its psychometric properties10, 11 and sensitivity to change after revascularization12 were adequately documented, there is limited insight into the ability to discrimi-nate between asymptomatic and symptomatic disease and its correlation with traditional clinical in-dices of disease severity.10, 12 This study was designed to further document its validity by contrasting PAQ scores in patients with asymptomatic and symptomatic disease and by comparing PAQ scores with PAD related indices, such as walking disease and an established cardiac risk algorithm. More specifically, clinical validity was studied both in this disease-specific instrument and the EQ-5D, a standardized generic instrument applicable in a wide range of medical conditions, containing a five dimensional descriptive health status system (EQ-5D) and a visual analogue scale (EQ VAS).13, 14 We hypothesized that the clinical validity of the disease specific PAQ would be better than the generic EQ-5D.


METHODS

Study population

Between May and December 2004, a survey of clinical practice was conducted in 11 hospitals in The Netherlands.15 This survey was an integral part of the infrastructure of the survey program supported by the Netherlands Heart Foundation in the context of the Euro Heart Survey Programme. All con-secutive patients included in this survey were seen at the participating vascular surgery departments and were undergoing noncardiac vascular repair (endovascular or open procedures). Endovascular procedures included aortic endograft procedures and peripheral angioplasties with and without stent-ing. Open procedures included: abdominal aortic surgery, carotid endarterectomy, or infrainguinal arterial reconstruction. Patients below the age of 18 years and patients undergoing thoracic or brain surgery were excluded. The total study population consisted of 711 consecutively enrolled patients undergoing peripheral vascular repair. After three years follow-up, information on survival status was obtained through the Civil Registries. Patient status could be determined in 701 (99%) of the original 711 respondents revealing that 149 (21%) of patients had died in the 3-year period since the original survey. All 552 survivors were contacted to complete health status questionnaires (EQ-5D and PAQ), 465 (84%) of whom responded and comprised the final study group.

Data collection

Clinical characteristicsTrained research assistants obtained data on patient characteristics, cardiac treatments and the sur-gical procedure from the patients’ hospital charts. We determined the cardiac risk score for each patient in our dataset, according to the Lee-Index,16 in which one point is assigned to each of the following characteristics: open vascular surgery, history of ischemic heart disease, history of conges-tive heart failure, history of cerebrovascular disease, insulin therapy for diabetes and renal failure. Furthermore, the presence of claudication and its severity were assessed by quantifying patients’ maximum walking distance. Walking distance was scored as <50 meter, 50-100 meters or >100 me-ters. More details on the study population and methods of data collection can be found in an earlier publication on this survey.15


Health statusHealth status was measured at three years of follow-up by the translated Dutch version of the PAQ, a disease-specific instrument for assessing health status in patients with PAD.11 The instrument consists of 20 items with one item identifying the most symptomatic leg and the other items being answered along variable Likert scales with equidistant gradations of response. Although the term ‘health status’ was chosen to refer to the construct that the PAQ intends to measure, the questionnaire contains both items that assess health status (i.e. registration of limitations) and QoL (patients’ personal evaluation of their functioning, disease, and treatment). A previous validation study of the Dutch PAQ revealed three overarching domains: Physical limitation (corresponding to the original PAQ Physical Limitation Domain), Perceived Disability (corresponding to the original PAQ Symptom, Symptom Stability, So-cial Limitation and Quality of Life domains), and Treatment Satisfaction (corresponding to the original PAQ treatment satisfaction domain). Given that the response categories are different across items, standardized scoring algorithms are applied to obtain scale scores ranging from 0 to 100, with high scores indicating good health status.10 A Summary score can be derived by combining the original Physical Limitation, Symptom Frequency/Burden, Social Function, and Quality of Life domains.10 The PAQ and its scoring instructions can be obtained from http://www.cvoutcomes.org/.

The Dutch version of the EQ-5D was used as a standardized, generic instrument for describing and valuing health.13, 14 This instrument was developed by the EuroQol group and has been used to as-sess health status across a wide range of chronic conditions, including cardiovascular disease.17 The EQ-5D contains both a EQ-5D descriptive system that defines health along five dimensions and a EQ visual analogue scale (EQ VAS). The five dimensions of the descriptive system consist of Mobility, Self-Care, Usual Activities, Pain or Discomfort, and Anxiety/ Depression and each of these dimen-sions has three levels of severity, corresponding to “no problems”, “moderate problems” and “severe problems”. Theoretically, 243 different health states can be generated by the descriptive system. A single Summary Index (EQ-5D Index) representing the patient’s self-rated health can be calculated by applying scores from a standard set of general population weights. The ratings can be analyzed on an individual level using health-state utility scores. Scores <0 are regarded as worse than death and 1 representing full health, from the perspective of the general population. The EQ-5D index in this study was obtained on value sets derived from the Dutch population by the time trade-off valuation technique.14 In addition, the EQ VAS asks respondents to rate their perception of their overall health on a vertical visual analogue scale with the endpoints ranging from 0 to 100 (0=‘worst imaginable health state’ and 100=‘best imaginable health state’). The EQ-5D and its scoring instructions can be


obtained from http://www.euroqol.org/. The results of the EQ-5D in this study will be presented using the weighted index of the 5-dimensional descriptive system (EQ-5D Index) and using the EQ VAS as a measure of overall self-rated health status.

Clinical validityClinical validity assesses the ability of scores to discriminate among groups of patients defined ac-cording to clinical severity. Patients who have a good clinical status (i.e., asymptomatic disease, fewer risk factors, and longer walking distance) should score well on the questionnaire, and patients who have a poor clinical status (i.e., symptomatic disease, more risk factors, and shorter walking distance) should score poorly. A high degree of clinical validity is suggested by a high correlation between health status and clinical indicators.

Statistical analyses

Baseline characteristics were described as numbers and percentages. Health status scores were described as means and standard deviations and compared using t-tests for dichotomous data and ANOVA for multiple categories. Linear regression analysis was used to assess multivariable associa-tion between the clinical indicators for PAD and health status scores. For all tests, a P value <0.05 (two-sided) was considered significant. All statistical analyses were performed using SPSS 15.0 (SPSS for Windows, Chicago: SPSS Inc).


RESULTS

Of the 465 participating patients, 454 had sufficient health status information to generate PAQ Sum-mary Scores with a mean score of 62.0±28.2. Missing data analysis showed that respondents did not differ significantly from non-respondents with regard to age, sex and Lee Risk Index. As shown in Table 1, most cardiovascular risk factors compromising the Lee-Index were associated with lower PAQ Summary scores. Furthermore, the presence of COPD (53.3±26.8 vs. 63.0±28.2, P=.024) and obesity (50.8±29.0 vs. 63.6±27.8, P=.001) was associated with lower PAQ Summary scores.

Table 1 – Baseline characteristics.

Abbreviations: PAQ, Peripheral Artery Questionnaire; N, number; SD, standard deviation; TIA, transient ischemic attack; COPD, chronic obstructive pulmonary disease.

PAQ Summary score n (%) Mean SD P value

465

Age (yrs) <.001 <70 years 307 (66.0) 66.0 27.4 ≥70 years 158 (34.0) 54.1 28.2 Gender .086 male 323 (69.5) 63.5 28.3 Female 142 (30.5) 58.6 27.8 Diabetes mellitus .001 No 369 (79.4) 64.2 28.0 Yes 96 (20.6) 53.4 27.6 Renal insufficiency .035 No 441 (91.8) 62.7 28.1 Yes 24 (5.2) 50.2 27.9 Angina pectoris .005 No 392 (84.3) 63.6 27.6 Yes 73 (15.7) 53.6 29.9 Myocardial infarction .036 No 398 (85.6) 63.2 27.9 Yes 67 (14.4) 55.2 29.5 Heart failure .001 No 447 (96.1) 62.9 27.9 Yes 18 (3.9) 39.8 27.7 Stroke or TIA .172 No 356 (85.2) 62.8 27.9 Yes 69 (14.8) 57.8 29.6 Previous revascularisation .048 No 388 (83.4) 63.2 28.4 Yes 77 (16.6) 56.2 26.5 Hypertension .830 No 288 (61.5) 61.8 27.7 Yes 177 (38.1) 62.4 29.1 Current smoker .554 No 300 (64.5) 62.6 27.5 Yes 165 (35.5) 61.0 29.4 COPD .024 No 416 (89.5) 63.0 28.2 Yes 49 (10.5) 53.3 26.8 Obesity .001 No 408 (87.7) 63.6 27.8 Yes 57 (12.3) 50.8 29.0 Intermittent claudication <.001 No 160 (34.4) 68.6 27.8 Yes 305 (65.6) 58.6 27.8 Lee-Index .007 0 risk factors 141 (30.3) 86.1 25.4 1 risk factor 157 (33.8) 61.8 28.6 2 risk factors 131 (28.2) 57.8 29.2 ≥3 risk factors 36 (7.7) 54.7 29.4


As shown in Table 1 and Figure 1, patients with claudication had significantly lower PAQ Summary scores as compared with asymptomatic patients (58.6±27.8 vs. 68.6±27.8, P≤.001). The differences in the PAQ Summary score reflect the observed differences in the underlying PAQ domains Physical Functioning and Perceived Disability. Furthermore, the Treatment Satisfaction domain successfully discriminated between those who were symptomatic and those with asymptomatic PAD (75.0±28.1 vs. 82.5±25.7, P=.008). With respect to the generic EQ-5D, both the EQ-5D Index and the EQ VAS scores were lower for patients with claudication.


Figure 1 – Health status according to the presence of intermittent claudication sym

ptoms. Abbreviations: PAQ, Peripheral Artery Question-

naire; EQ-5D, EuroQol-5-dimensions; EQ-VAS, EuroQol visual analogue scale.

EQ

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Ind

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20

40

60

80

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Of the 305 patients with claudication, information on walking distance was available in 202 (73%) patients with 25% classified as 0-50 meters, 29% 50-100 meters and 46% more than 100 meters. As shown in Figure 2, PAQ scores were proportional higher with increasing walking ability. The EQ VAS did also differ significantly between the groups, while the differences in EQ-5D Index lacked significance.


Figure 2 – Health status according to walking distance. Information on walking distance was available in 202 (73%) of the 305 patients with

intermittent claudication. Abbreviations: PAQ, Peripheral Artery Questionnaire; EQ-5D, EuroQol-5-dimensions; EQ-VAS, EuroQol visual analogue scale.

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PAQ Summary score and subscale scores for the Physical Functioning domain and the Perceived Disability domain demonstrated a clear dose-response relationship with the Lee Risk Index, i.e. PAQ scores were lower with increasing cardiac risk (Figure 3). The Treatment Satisfaction domain was not associated with the Lee Risk Index. The EQ-5D Index did not differ significantly between the risk groups; while the EQ VAS did (P=.008); although the clear dose-response relationship was lacking.

In addition, multivariable linear regression analysis revealed that after adjusting for other clinical characteristics the independent association between IC, Lee Risk Index and PAQ scores (Physical Functioning, Perceived Disability and PAQ Summary score) remained (all P values <.05).


Figure 3 – Health status according to the Lee Cardiac Risk Index. Abbreviations: PAQ, Peripheral Artery Questionnaire; EQ-5D, EuroQol-5-dimensions; EQ-VAS, EuroQol visual analogue scale.

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DISCUSSION

This study demonstrated good clinical validity of the PAQ with traditional clinical indices of PAD sever-ity. Specifically, all PAQ subscales discriminated well between patients with or without symptomatic PAD and its severity. Moreover, it was sensitive to the presence of risk factors relevant for PAD and demonstrated a clear dose-response relationship between the number of risk factors and patients’ experienced health status. Although the EQ-5D Index and EQ VAS scale could differentiate between asymptomatic and symptomatic disease, the EQ indices were not able to display the clear dose-response relationship between the number of risk factors and worsening of health status. These findings have important potential implications for disease management programs and future clinical trials.

An important issue to be addressed regarding the development and use of health status instruments in vascular medicine are their reliability and validity. Internal reliability of the three domains quantified by Cronbach’s alpha was reported high for the Dutch PAQ (mean α=0.94) and the original instru-ment.10 Previous studies also showed that the PAQ had a good test-retest reliability and sensitivity to change.10, 12 In addition, an important issue for the use of disease-specific measures in clinical prac-tice is that they focus on aspects that are relevant for a specific patient population. Our results of the PAQ instrument clearly show the disease-specific nature of this measure, with the PAQ discriminating well between different clinical indices. The strongest association of PAD symptoms that we observed were with pain and physical limitations, i.e. the PAQ sub domains of Physical Functioning and Per-ceived Disability. This observation confirms earlier research demonstrating the impact of symptomatic disease on physical health and QOL in PAD patients.5, 18 PAD is also often accompanied by comor-bid diseases, which may pose an extra burden on patients’ health status. The results in this report showed that the cardiac risk profile of PAD patients, as described by the Lee Cardiac Risk Index, was highly correlated with patients’ health status. Increasing risk was proportionally reflected in decreas-ing PAQ scores on the Physical Functioning and Perceived Disability domains, and Summary score.

The management of patients with PAD has changed in the last decade with the introduction of en-dovascular techniques and other treatment modalities.19 In general, the principal aim of medical treatment is to relieve symptoms related to the specific disease and to improve the patient’s health status and prognosis. Traditionally, treatment success is measured with clinical measures, such as the ankle-brachial index, patency rates, and survival. The question regarding the impact of the in-


tervention on the patient’s ability to function in daily life remains, however, when only relying upon these technical measures.7 Since patients’ main concerns are for symptom relief and improvement in their daily functioning, treatment should also be assessed by its success in improving patients’ health status. Furthermore, clinical measures as the ankle-brachial index are known to correlate poorly with changes in health status scores,9, 20 which also supports the use of direct, patient-centered assessments of the effects of treatment on patients’ health status. As such, health status is increas-ingly being assessed in clinical research studies comparing different treatment options.20, 21 Moreover, patient-centered outcome measures can provide substantial insights into related clinical factors and processes of care that are useful in assessing healthcare quality.22 Traditional metrics for evaluating healthcare have been mortality and morbidity, but these measures often lack the sensitivity to differ-entiate providers and omit a major outcome from the perspective of patients.

While there is a choice in how best to quantify patients’ health status, important advantages of dis-ease-specific, as compared with generic, instruments are their focus on specific symptoms of a dis-ease and the sensitivity and responsiveness to clinically relevant changes conferred by treatment. Previous studies have demonstrated a better discriminative ability of disease-specific versus generic questionnaires to detect changes in QOL in PAD patients,23 congruent with the findings of our study, which demonstrated that the PAQ discriminated better between the clinical indices than the generic EQ-5D Index. The EQ-5D is known for its ceiling effect, i.e the score distribution tends to be skewed to higher scores, which could potentially be related to having only three response categories and its ge-neric character. In our study 25% of the patients had a maximum score. Except for patients with more than three risk factors according to Lee Risk Index, mean scores of the EQ-5D were all higher than 0.75 and did not differ substantially. On the other hand, the EQ VAS was more sensitive for clinical indices, although its discriminative ability appeared to be less than the PAQ in this study. For studying outcomes in PAD patients, the disease-specific PAQ therefore seems to be the preferred choice. The EQ VAS may still be a valuable secondary choice, as generic health status questionnaires are known to be broad and multidimensional instruments and therefore apt for use when comparing health status across different diseases or when calculating utility values in economic analysis are important study goals.

In addition to using health status measures as outcome measure, health status measurements may provide prognostic information to guide clinical decision-making. In this way, impaired health status has been shown to be an independent predictor of mortality in cardiac patients24-26 and predicted


invasive treatment in a prospective PAD population.27 Health status measurements can therefore potentially be used in clinical practice to identify patients who are at relatively high risk for adverse outcomes. These patients may benefit from more aggressive treatment, including pharmacological, invasive or behavioral interventions. Of note, the performance of the EQ VAS score was acceptable when discriminating between symptomatic vs. asymptomatic disease and suboptimal when relating the index to walking distance and the presence of risk factors. Although it seems attractive in terms of time, effort and resources to use this simple instrument to assess the patient’s health status, its role in disease management is minor. The PAQ describes clear and clinically relevant domains that can give clinicians important insights with which to better manage patients’ PAD; including patients’ physical limitations due to their PAD and their personal evaluation of their limitations related to PAD. These nuances can not be captured by generic questionnaires and by instruments that only focus on physical limitations, rather than concentrating on the subjective evaluations of patients’ physical func-tioning. Although information received from generic instruments are hard to interpret and to translate into clinical practice, the EQ VAS may be used as an initial screening tool to further identify vulnerable patients with disease-specific questionnaires, such as the PAQ.

The limitations of this study are those inherent to observational studies and the fact that all patients underwent vascular interventions. Although the study cohort seems to be a relatively high risk popu-lation, the PAQ was still able to discriminate well between the clinical indices. Moreover, it has to be noted that compared to clinical trials, our study comprises a rather heterogeneous population and is more representative of daily clinical practice. Further research has to be performed to ascertain the clinical validity of PAQ in an overall PAD population treated with a range of therapeutic options. An-other potential limitation of our work is that the response rate of our study was not 100%. A response rate of 84%, however, is regarded as quite good and importantly, non-responder analyses revealed no differences between the patients who responded and those who did not. Furthermore, it should be noted that the assessment of the validity of questionnaires is not straightforward as there is no gold standard for outcome measurement in PAD patients. In this study, we used clinical indices retrospec-tively obtained from chart-review, including the presence of claudication and the Lee Risk Index, as criterion measures for clinical validity. This limitation should be kept in mind together with the fact that no baseline health status measurements were available, when interpreting our results. Future studies using the PAQ, should further elaborate on the clinical relevance of this disease-specific instrument tracking clinical indices, such as the ankle-brachial index, and aspects of lower extremity functioning together with patients’ health status.


In conclusion, this study demonstrated good clinical validity of the PAQ as the instrument discrimi-nated well between patients with or without symptomatic PAD and its severity and was sensitive to the presence of risk factors relevant for PAD. We would like to strengthen the importance of disease-specific health status measures like the PAQ and advocate their use as outcome measure and dis-ease management tool in PAD management, rather than relying on clinical measures alone. After all, outcome and risk assessment should be evaluated from the patient’s perspective. Health status measures will play an increasingly important role in the evaluation of diverse therapeutic strategies and in clinical decision making in the field of vascular medicine.


REFERENCES

1. Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann TJ, et al. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med 1992;326:381-6.


3. Nehler MR, McDermott MM, Treat-Jacobson D, Chetter I, Regensteiner JG. Functional outcomes and quality of life in peripheral arterial disease: current status. Vasc Med 2003;8:115-26.

4. Pell JP. Impact of intermittent claudication on quality of life. The Scottish Vascular Audit Group. Eur J Vasc Endovasc Surg 1995;9:469-72.

5. Breek JC, Hamming JF, De Vries J, van Berge Henegouwen DP, van Heck GL. The impact of walking impairment, cardiovascular risk factors, and comorbidity on quality of life in patients with intermittent clau-dication. J Vasc Surg 2002;36:94-9.


7. McDaniel MD, Nehler MR, Santilli SM, Hiatt WR, Regensteiner JG, Goldstone J, et al. Extended outcome assessment in the care of vascular diseases: revising the paradigm for the 21st century. Ad Hoc Commit-tee to Study Outcomes Assessment, Society for Vascular Surgery/International Society for Cardiovascular Surgery, North American Chapter. J Vasc Surg 2000;32:1239-50.

8. Krumholz HM, Peterson ED, Ayanian JZ, Chin MH, DeBusk RF, Goldman L, et al. Report of the National Heart, Lung, and Blood Institute working group on outcomes research in cardiovascular disease. Circula-tion 2005;111:3158-66.

9. Mehta T, Venkata Subramaniam A, Chetter I, McCollum P. Assessing the validity and responsiveness of disease-specific quality of life instruments in intermittent claudication. Eur J Vasc Endovasc Surg 2006;31:46-52.


11. Smolderen KG, Hoeks SE, Aquarius AE, Scholte op Reimer WJ, Spertus JA, van Urk H, et al. Further validation of the Peripheral Artery Questionnaire: results from a peripheral vascular surgery survey in the Netherlands. Eur J Vasc Endovasc Surg 2008;36:582-91.



13. EuroQol--a new facility for the measurement of health-related quality of life. The EuroQol Group. Health Policy 1990;16:199-208.

14. Lamers LM, McDonnell J, Stalmeier PF, Krabbe PF, Busschbach JJ. The Dutch tariff: results and argu-ments for an effective design for national EQ-5D valuation studies. Health Econ 2006;15:1121-32.

15. Hoeks SE, Scholte op Reimer WJ, Lenzen MJ, van Urk H, Jorning PJ, Boersma E, et al. Guidelines for cardiac management in noncardiac surgery are poorly implemented in clinical practice: results from a peripheral vascular survey in The Netherlands. Anesthesiology 2007;107:537-44.

16. Lee TH, Marcantonio ER, Mangione CM, Thomas EJ, Polanczyk CA, Cook EF, et al. Derivation and pro-spective validation of a simple index for prediction of cardiac risk of major noncardiac surgery. Circulation 1999;100:1043-9.

17. Xie J, Wu EQ, Zheng ZJ, Sullivan PW, Zhan L, Labarthe DR. Patient-reported health status in coronary heart disease in the United States: age, sex, racial, and ethnic differences. Circulation 2008;118:491-7.

18. Dumville JC, Lee AJ, Smith FB, Fowkes FG. The health-related quality of life of people with peripheral arterial disease in the community: the Edinburgh Artery Study. Br J Gen Pract 2004;54:826-31.

19. Anderson PL, Gelijns A, Moskowitz A, Arons R, Gupta L, Weinberg A, et al. Understanding trends in inpa-tient surgical volume: vascular interventions, 1980-2000. J Vasc Surg 2004;39:1200-8.

20. Bosch JL, van der Graaf Y, Hunink MG. Health-related quality of life after angioplasty and stent placement in patients with iliac artery occlusive disease: results of a randomized controlled clinical trial. The Dutch Iliac Stent Trial Study Group. Circulation 1999;99:3155-60.

21. Mukherjee D, Munir K, Hirsch AT, Chetcuti S, Grossman PM, Rajagopalan S, et al. Development of a multicenter peripheral arterial interventional database: the PVD-QI2. Am Heart J 2005;149:1003-8.

22. Rectenwald JE, Upchurch GR, Jr. Impact of outcomes research on the management of vascular surgery patients. J Vasc Surg 2007;45 Suppl A:A131-40.

23. de Vries M, Ouwendijk R, Kessels AG, de Haan MW, Flobbe K, Hunink MG, et al. Comparison of generic and disease-specific questionnaires for the assessment of quality of life in patients with peripheral arterial disease. J Vasc Surg 2005;41:261-8.

24. Lenzen MJ, Scholte op Reimer WJ, Pedersen SS, Boersma E, Maier W, Widimsky P, et al. The additional value of patient-reported health status in predicting 1-year mortality after invasive coronary procedures: a report from the Euro Heart Survey on coronary revascularisation. Heart 2007;93:339-44.

25. Spertus JA, Jones P, McDonell M, Fan V, Fihn SD. Health status predicts long-term outcome in outpatients with coronary disease. Circulation 2002;106:43-9.

26. Soto GE, Jones P, Weintraub WS, Krumholz HM, Spertus JA. Prognostic value of health status in patients with heart failure after acute myocardial infarction. Circulation 2004;110:546-51.

27. Aquarius AE, Denollet J, Hamming JF, Breek JC, De Vries J. Impaired health status and invasive treatment in peripheral arterial disease: a prospective 1-year follow-up study. J Vasc Surg 2005;41:436-42.

Th e need to increase awareness of the psychological burden in peripheral arterial disease

Part II

Chapter 4

Depressive symptoms in peripheral arterial disease: a follow-up study on prevalence,

stability, and risk factors

4

82 Chapter 4 - Depressive symptoms trajectories

Smolderen KG, Aquarius AE, De Vries J, Smith ORF, Hamming JF, Denollet J. Depressive symptoms in peripheral arterial disease: a follow-up study on prevalence, stability, and risk factors. J Affect Disord 2008;110:27-35.

ABSTRACT

Background: Depressive symptoms are associated with poor prognosis in coronary artery disease, but there is a paucity of research on these symptoms in peripheral arterial disease (PAD). We exam-ined the clinical correlates and 18-month course of depressive symptoms in PAD patients.

Methods: A totl of 166 patients with symptomatic lower extremity PAD (39% women; M age=64.9±10 years) completed the 10-item Center for Epidemiological Studies Depression scale. A score ≥4 indi-cates clinically relevant depressive symptoms. Depressive symptoms were re-assessed at six, 12, and 18 months follow-up. Ankle-brachial index (ABI) and treadmill walking distance were used to assess PAD severity.

Results: At baseline, depressive symptoms (CES-D ≥4) were present in 16% of the patients. De-pressed patients performed worse regarding pain-free (P=.003) and maximum (P=.005) walking dis-tance. After adjusting for age, sex, education, ABI, psychotropic medication use, cardiovascular risk factors, and comorbidity, depressive symptoms remained stable in initially depressed patients. Using mixed modelling, three subgroups were identified in the total sample. The majority of PAD patients did not have depressive symptoms (58%), but there were two groups who persistently experienced either subclinical (27%) or clinically manifest (15%) depressive symptoms.

Limitations: Only baseline data of ABI and treadmill walking performance were available.

Conclusions: Depressive symptomatology was present in a substantial number of PAD patients, tended to be stable, and was associated with reduced walking distance. These apparently evident results are overlooked thus far in this patient group and deserve further attention in research and clinical care.


INTRODUCTION

Lower extremity peripheral arterial disease (PAD) occurs as a result of arterial narrowing that restricts blood flow to the lower limbs and is an important indicator for the presence of systemic atherosclerotic disease that leads to an increased risk of cardiovascular morbidity and mortality.1, 2 Manifestations of PAD include (i) asymptomatic arterial insufficiency, (ii) symptomatic disease presenting as intermittent claudication (IC), and (iii) critical leg ischemia.1 PAD requires antiplatelet therapy1 and aggressive risk factor modification, such as addressing smoking cessation, and treating associated conditions, like hyperlipidemia and hypertension.3 In addition to traditional risk factors, there is increasing evidence that psychological risk factors such as major depression and even subclinical depressive symptoms are important determinants of prognosis in patients with ischemic heart disease4 and other vascu-lar diseases, e.g., stroke and vascular dementia, especially in the elderly.5 Plausible mechanisms by which depression may lead to worse prognosis are raised cortisol levels, platelet and clotting changes, reduced heart rate variability, and unhealthy lifestyle choices.5 There is a vast literature that demonstrates that the relationship between depression and vascular disease should be understood as bi-directional. Depression predisposes to later vascular disease and may worsen pre-existing dis-ease; moreover, vascular disease may lead to or aggravate depressive symptoms.5 Recent findings in myocardial infarction patients6 and in older adults suggest that course (i.e., increase of depres-sive symptoms, persistence) rather than baseline levels of depression seem to matter in terms of cardiovascular prognosis and mortality.7 In contrast to the literature found in old age, coronary heart disease, stroke, and vascular dementia, little is known about the presence and course of depressive symptoms and their possible role for health status and prognosis in PAD.

Preliminary evidence suggests that depressive symptoms may be common among patients with PAD8, 9 and may be associated with functional impairment,9 worse patency rates,8 and poor quality of life.10 However, longitudinal research on the prevalence and course of depressive symptoms in PAD is lacking.8 Studying the course of depressive symptomatology, together with its clinical correlates, may unravel the range of mood problems in PAD, possibly associated with the burden of lower extremity PAD. Therefore, the aim of the present study was (i) to examine the 18-month course of clinically relevant depressive symptoms in relation to important clinical correlates in PAD patients and (ii) to identify distinctly different trajectories of depressive symptoms within the continuum of depressive scores rather than concentrating on trajectories based on baseline depressive scores alone using a mixed modelling procedure.


METHODS

Patients

Between September 2001 and March 2004, 251 patients with IC, a common form of PAD, presented at the vascular outpatient clinic of the department of surgery of the St. Elisabeth Hospital in Tilburg, The Netherlands. Inclusion criteria were IC diagnosis, which was defined as pain occurring during exertion when blood flow velocity increases across a stenotic lesion in the legs, and an abnormal resting Ankle-Brachial Index (ABI) (<0.90) or an abnormal post-exercise ABI (ABI decrease of 15% after exercise).11 An ABI value of <0.90 is 95% sensitive to detect PAD.1 Patients received the advice to start exercise training and to quit smoking. No supervised exercise-training programs were used.

Exclusion criteria were cognitive impairment, the presence of severe psychopathological (e.g., psy-chosis, suicidal ideation) or invalidating somatic comorbidities (e.g., cancer), participation in another study, and insufficient knowledge of the Dutch language. Of 251 patients with PAD, 8 (3%) were ex-cluded due to cognitive impairment (n=4), recent myocardial infarction (n=1), visual problems (n=1), influenza (n=1), and participation in another study (n=1). Of the remaining patients, 195 (80%) agreed to participate. Four patients (2%) did not complete the baseline measurement of depressive symp-toms and 25 (13%) patients had two or more assessment points that were lacking [deceased (n=8), hospitalized (n=2), refused follow-up (n=15)], leaving 166 patients (39% women; M age=64.9±10.0 years). No significant differences were present between the patients who refused further follow-up (n=15) and the total sample, except for maximum walking distance (M drop-outs=388.5m vs. M total sample=196.2m, P<0.0001). The study was approved by the local ethics committee. The study was conducted conform to the Helsinki Declaration and all participants signed informed consent. All 166 PAD patients completed a measure of depressive symptoms at baseline and six, 12, and 18 months follow-up.


Measures

Disease severityResting ABI and pain-free (PFWD) and maximum-walking distance (MWD) were determined in all patients at baseline as indices of PAD severity. The ABI is defined as the ratio of the ankle systolic blood pressure to the brachial systolic blood pressure and has a normal resting value of about 1.0 to 1.5.12 The ABI is sensitive to identify patients with PAD and is an important predictor of future car-diovascular events.12 A handheld Doppler device (Imexlab 9000; Imex Medical Systems Inc, Golden Colorado) was utilized to obtain systolic pressures in the right and left brachial and posterior tibial and dorsalis arteries. The ABI was calculated by dividing the highest of posterior tibial and dorsalis pedis ankle pressures in each leg by the highest brachial pressure. The ABI at rest was measured while the patient was lying in the supine position. PFWD and MWD were determined by means of a treadmill exercise test; during this test, patients had to walk 3.5 km/h on a 5% incline, with a maximum of 1000 meter (m).13 A decrease in ABI of 15%–20% after exercise is diagnostic of PAD.11 Mild and moderate/severe claudication was defined using the Fontaine Stages IIa and IIb.11

Cardiovascular risk factors and comorbidityIn the present study, diabetes mellitus, smoking, hypertension, hyperlipidemia, and cardiac, carotid, renal, and pulmonary status were measured at baseline in all patients according to the Society for Vascular Surgery/North American chapter of the International Society for Cardiovascular Surgery (SVS/ISCVS) recommended standards14 (Appendix). Because of its known association with depres-sive symptoms,15 information about smoking abstinence at baseline was documented by patients’ medical records. The presence of back, knee or hip symptoms, unrelated to vascular disease (e.g., knee or hip arthritis) was documented from patients’ medical files because these symptoms are im-portant for patient-based outcomes in patients with intermittent claudication.13 In addition to age and educational level, information about marital status was obtained from the participants.

Depressive symptomsDepressive symptoms were measured using a Dutch version of the Center for Epidemiological Stud-ies Depression Scale (CES-D); the CES-D was originally developed to assess the present levels of depressive symptoms in the general population.16 In this questionnaire, the focus is on the affective component, the depressive mood.16 The CES-D questionnaire is widely used and easy to administer, especially in older adults.17 In the present study, a simplified and abbreviated version of the original


CES-D – the Boston 10-item form - was used.18 This version was developed to reduce response bur-den and consists of 10 dichotomous response options. Patients were asked to indicate (yes or no) if they had experienced each symptom “much of the time during the past week”.18 The CES-D 10-item version has good reliability (Cronbach’s α=0.88) and shows an excellent sensitivity (97%) to detect major depression according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edi-tion criteria.19 The Cronbach’s α in the present study also proved to be good (α=0.83). A cut-off score ≥4 indicates clinically relevant depressive symptoms without losing specificity and sensitivity; using this cut-off score, the sensitivity and specificity for the diagnosis of major depression in persons 60 years and older was 100% and 92% respectively.20 Test-retest reliability of the CES-D 10-item version is high (Pearson r=0.83).17

Medication Participants listed their psychotropic medication use at baseline because of their possible interactions with the cardiovascular system and their known effects on depressive mood.21 All reported medica-tions were reviewed and classified according to their psychotropic function. Use of psychotropic medi-cation was conceptualized as the intake of benzodiazepines or other anxiolytics, selective serotonin reuptake inhibitors, and tricyclic antidepressants. Because of persistent concerns that exist regarding the adverse neuropsychological side effects (e.g., depression) that may be caused by beta-blockers, beta-blocker therapy was also documented by patients at baseline.22


Baseline characteristics of participants were examined stratifying by baseline presence of clinically relevant depressive symptoms (cut-off ≥4). ABI, PFWD, and MWD were used as continuous variables and cardiovascular risk factors and use of psychotropic medication were analyzed as binary vari-ables. We recoded the variables of the appendix into absence of the risk factor (=0) and all the other values (mild, moderate, severe) into presence of the risk factor (=1). Chi-square tests and Student’s t-tests were used to check for significant univariate differences.

Using the CES-D cut-off score of ≥4 to indicate clinically relevant depressive symptoms, two groups (baseline depressive symptoms versus no depressive symptoms) were compared with regard to their mean depression scores during 18 months follow-up. Analysis of covariance (ANCOVA) with repeat-


ed measures were used for this purpose, adjusting for age, sex, educational level, ABI, psychotropic medication use, beta-blocker use, smoking abstinence, comorbidity, and cardiovascular risk factors. These analyses were done using SPSS for Windows, version 14.0.1. P values <.05 were considered as statistically significant.

To identify subgroups with distinctly different trajectories of depressive symptoms within the whole continuum of depressive scores over an 18-month time period, SAS procedure TRAJ was used. TRAJ combines hierarchical modelling and latent growth curve modelling and fits a mixture model to identify groups of individuals following similar patterns of behavior over time.23 To determine the optimal number of trajectories, the Bayesian Information Criterion (BIC) was used, with a higher BIC indicating a better fit. In addition, associations between group membership and covariates were determined. Multinomial logistic regression was used to determine the group characteristics of the derived trajectories.


RESULTS

Clinical correlates of baseline depressive symptoms

Depressive symptoms (cut-off score ≥4 on the CES-D scale) were present in 16% (n=26) of the patients at baseline. Stratifying baseline characteristics of participants by depressive symptoms (Table 1), yielded significant differences with regard to PFWD (Mean [M] Depressive Symptoms Group=73.6m vs. M No Depressive Symptoms Group=124.7m, P=.003) and MWD (M Depressive Symptoms Group=258.4m vs. M No Depressive Symptoms Group=412.4m, P=.005). Patients who experienced depressive symptoms had shorter PFWD and MWD than their non-depressed counter-parts. To evaluate whether the relationship between depressive symptoms and walking performance remained significant after statistically controlling for confounding factors, ANCOVA was applied. Using ANCOVA, the association between depressive symptoms and MWD remained significant (P=.03) and showed a trend for PFWD (P=.13) after controlling for confounding factors which may impair lower-extremity functioning (ABI, sex, diabetes, back symptoms)24 (Figure 1). ABI did not differ between patients with and without baseline depressive symptoms.

Patients with depressive symptoms more often had no partner (57.7% in Depressive Symptoms Group vs. 30.7% in No Depressive symptoms Group, P=.008) and used more psychotropic medica-tion (30.8% in Depressive Symptoms Group vs. 5.0% in No Depressive symptoms Group, P<.0001) than their non-depressed counterparts.

Table 1 – Baseline characteristics stratified by the presence of clinically relevant depressive symptoms.*

*Data are presented as %, unless otherwise specified. Abbreviations: CES-D, Center for Epidemiological Studies Depression Scale; SD, standard deviation; ABI, ankle brachial index; PFWD, pain-free walking distance; MWD, maximum walking distance.

Ces-D<4

(n=140)

CES-D≥4

(n=26)

P value

Mean age, years (SD) 64.9 (10.0) 64.8 (10.1) .96

Females, % 37.9 46.2 .43

Low educational level, % 72.1 84.6 .18

Having no partner, % 30.7 57.7 .008

Mean ABI (SD) 0.61 (0.15) 0.64 (0.14) .44

Mean PFWD, meter (SD) 124.7 (159.9) 73.6 (48.9) .003

Mean MWD, meter (SD) 412.4 (348.5) 258.4 (212.9) .005

Moderate/severe claudication, % 47.1 53.8 .53

Diabetes mellitus, % 17.9 26.9 .28

Current smoking, % 52.1 61.5 .38

Smoking abstinence, % 33.1 24.0 .37

Hypertension, % 45.0 50.0 .64

Hyperlipidemia, % 48.6 53.8 .62

Cardiac risk factor, % 29.3 19.2 .29

Carotid risk factor, % 10.0 15.4 .42

Renal disease, % 2.9 3.8 .79

Pulmonary disease, % 6.4 7.7 .81

Back symptoms, % 12.1 15.4 .65

Hip or knee symptoms, % 9.3 7.7 .80

Psychotropic medication use, % 5.0 30.8 <.0001

Beta blocker use, % 22.1 30.8 .34


Figure 1 – Mean pain-free walking distance (PFWD) and maximum walking distance (MWD) for PAD patients, stratified by baseline depressive symptoms. Cut-off score ≥4 on CES-D scale; adjusted for ABI, sex, diabetes mellitus, and back symptoms.

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MWD


18-Month course of clinically relevant depressive symptoms

A one-way repeated measures ANCOVA was conducted to compare mean CES-D scores at baseline, six months, 12, and 18 months of patients with baseline depressive symptoms (using the cut-off ≥4) versus non-depressed patients. Depression scores of patients with baseline depressive symptoms significantly differed as compared with their non-depressed counterparts (Between-subjects effect: F=65.4, P<.0001). There was no main-effect of time (F=0.76, P=.52). Despite a slight decrease in severity of depressive symptoms over time in the baseline Depressive Symptoms Group (M=5.2±1.0 SD at baseline, M=4.4±2.0 SD at six months, M=5.0±1.9 SD at 12 months, and M=4.5±2.2 SD at 18-months, F time*baseline depression=3.4, P=.03), most patients who were having depressive symptoms at baseline had depressed feelings at all time points. In contrast, patients who were not experiencing depressive symptoms at baseline (M=0.9±1.0 SD), did not have clinically relevant de-pressive symptoms at six months (M=1.4±1.7 SD), 12 months (M=1.3±1.8 SD), and 18 months (M=1.2±1.7 SD).

Trajectories of depressive symptoms: subclinical and clinical depressive symptoms subgroups

Using SAS procedure TRAJ, three relevant patient subgroups with regard to depressive symptoms were identified in the whole data distribution of depressive scores during follow-up. The level of de-pressive symptoms over time was rather stable for all identified subgroups of PAD patients (Figure 2). The majority of the patients did not experience depressive symptoms (n=96, 58%), with a predicted mean CES-D score of 0.43 (95%CI: 0.41-0.45). The level of depressive symptoms of the second group (n=45, 27% of the patients) was higher compared to the first group with a mean CES-D score of 2.64 (95%CI: 1.89-3.53), and was therefore classified as patients with subclinical depressive symp-toms. Clinically relevant CES-D scores were observed in the third group (n=25, 15% of the patients). This group had a predicted mean CES-D score of 5.75 (95%CI: 5.13-6.37). Accordingly, these pa-tients were classified as experiencing depressive symptoms.


0 2 4 6 8

06

12

18

CES-D score

Mo

nth

s a

fter in

clu

sio

n

= O

bs

erv

ed

= P

red

icte

d

De

pre

ss

ive

sy

mp

tom

s (1

5%

)

Su

bc

linic

al d

ep

res

siv

e s

ym

pto

ms

(27

%)

No

de

pre

ss

ive

sy

mp

tom

s (5

8%

)

Figure 2 – Trajectories of depressive symptom

s in PAD patients. The solid lines represent the observed trajectories, whereas the dashed lines represent the predicted trajectories.


Univariate associates of depressive symptoms trajectories are presented in log odds, using the non-depressed group as reference category; patients with Subclinical Depressive Symptoms were more likely to be female (lo=1.23; P=.005) and to have a shorter PFWD (lo=-.49; P=.02), shorter MWD (lo=-.77; P<.001). Moreover, the Subclinical Depressive Symptoms Group more often had no partner (lo=0.90; P=.04), had hyperlipidemia (lo=0.86; P=.05), failed to quit smoking (lo=-4.45; P=.02), and tended to have hypertension (lo=0.77; P=.07). Furthermore, patients in the Depressive Symptoms Group were also more likely to have no partner (lo=1.21; P=.02) and to have shorter MWD (lo=-0.47; P=.05), and PFWD (lo=-0.40; P=.08). In addition, these patients reported an increased intake of psy-chotropic medication (lo=2.52; P=.003) and tobacco (lo=1.39; P=.02) and were more likely to report back symptoms (lo=1.22; P=.05).


DISCUSSION

The present study showed that the prevalence of depressive symptoms in PAD patients is high. When presenting themselves for a first visit at the vascular outpatient clinic, 16% of patients reported clini-cally relevant depressive symptoms (CES-D≥4). This finding is in accordance with previous findings.8,

9 But most important, depressive symptoms in PAD tended to be stable during a follow-up period of 18 months. Future research regarding the stability of depressive symptomatology is needed to elabo-rate on these findings and to clarify the possible effect of chronic depressive symptoms on long term outcomes. Cherr et al. (2007) already indicated that the presence of depression was associated with worse patency rates and recurrent leg symptoms after lower extremity revascularization.8

Depressed PAD patients performed worse on the treadmill exercise test; i.e., they had a significantly shorter PFWD and MWD; this association remained significant for MWD and showed a trend for PFWD, after adjusting for ABI, back symptoms, hip or knee symptoms, impaired pulmonary status, and the presence of a cardiac risk factor. In contrast, ABI did not differ between patients with and without depressive symptoms. Depressive symptomatology may have impaired treadmill exercise test performances in PAD patients with depressive mood, potentially affecting the reliability of the treadmill-walking test in this particular subset of patients. Lavoie et al.25 found evidence for this hy-pothesis in myocardial ischemia patients with depressive symptomatology who underwent exercise stress tests. On the other hand, worse performance on the treadmill exercise test may be indica-tive for poor daily functioning and more functional decline.26 Improvement of daily functioning and more specifically walking behavior seem to be of vital importance to help reduce the cardiovascular complications and mortality, even in populations with severe limitations.27 Of note, decreased walk performance at baseline predicted less accelerometer-measured physical activity and mortality in PAD at 57-month follow-up.28

PAD patients with depressive symptoms tend to use more psychotropic medication and they were also less likely to have a partner. These results are in line with previous studies; sociodemographic variables, such as marital status, appear to be concomitant risk factors for depressive symptoms.29 Furthermore, direct favorable effects on depressive symptoms were found for having a partner in various chronic diseases.


Depressive symptoms remained stable when using the recommended threshold of ≥4 for catego-rizing significant depressive symptoms;20 stratifying by baseline CES-D depressive symptoms and controlling for cardiovascular risk factors, patients who experienced clinically relevant depressive symptoms at baseline, were also having these depressive feelings at six, 12, and 18 months. In other words, depressive symptoms seemed to persist up to 18 months of follow up; the chronicity of depres-sive symptomatology is also found in post-myocardial infarction patients and in old age and seems to be associated with worsening functional disability.31, 32

When the whole continuum of depressive symptom scores was analyzed, a more differentiated clini-cal picture appeared. The majority of PAD patients (58%) did not have depressive symptoms during 18 months follow-up, while 15% persistently had clinically relevant depressive symptoms. Moreover, one third of PAD patients chronically experienced subclinical depressive symptoms. All these tra-jectories were stable during follow-up. These persistent trajectories of depressive symptoms might point towards the possible shared vascular pathophysiology underlying depression and PAD.5 The term ‘vascular depression’ refers to a range of late-life depressive syndromes due to a variety of pos-sible vascular mechanisms, e.g., thromboembolism, that leads to cerebral ischemia in key circuitry underpinning depressive symptomatology, such as frontal-subcortical circuits and the hippocampus.5 There is some evidence that a poor cardiovascular risk profile is associated with more depressive symptomatology,33, 34 which is in line with the present findings of our study. Patients with stable sub-clinical and clinical depressive symptoms had more cardiovascular risk factors as compared with the non-depressed group. Correlates for the Depressive Symptoms group were shorter PFWD and MWD, having no partner, current smoking, having back symptoms, and psychotropic medication use. PAD patients experiencing subclinical depressive symptoms more often had no partner, failed to quit smoking, tended to be female, and had worse treadmill walking performance compared with their counterparts who did not have depressive feelings. In addition, they were more likely to suffer from hypertension and hyperlipidemia. The association between the aforementioned clinical correlates and depressive symptoms might also be interpreted against the findings that depressive symptoms are associated with poor adherence to recommended behavior and lifestyle changes,15 which may in turn contribute to adverse outcomes in depressed patients with PAD.

This study has some limitations. First, depressive symptoms were assessed by means of a self-report questionnaire and consequently, no diagnosis of a major depressive disorder could be established. Therefore, the use of diagnostic interviews should be incorporated in future research. Second, al-


though ABI and treadmill walking performance were assessed at baseline, no longitudinal data of these measures were available. Therefore, future studies are warranted to show the long-term clinical consequences of our findings with regard to disease severity and adverse medical outcomes. Third, patients with more than two assessment points lacking were left out of the analyses. Although pa-tients who refused further follow-up did not differ much regarding baseline characteristics, we exclude the possibility that this might have influenced our results. Last, only three substantial subgroups with stable trajectories could be discerned with the mixed modelling procedure in this study. That means that there were not much individuals in the current sample that developed significantly lower or higher scores during follow-up. Studying the course of depressive symptoms in larger samples of PAD pa-tients in the future, would provide opportunities to look at groups of patients with changing depression scores and to concentrate on the predictors of these changes.

This study adds to growing data that prevalence of depressive symptoms is high in patients with PAD and that these symptoms are associated with walking performance. The new finding in this study refers to the chronicity of depressive symptoms in this patient group. Given the chronicity and extent of depressive symptomatology in the subgroups of patients that experienced either depressive symptoms or subclinical depressive symptoms, and given the association we found between some important clinical correlates of PAD, further consideration of the impact of depressive symptoms on prognosis in PAD is needed in research and clinical practice.


APPENDIX Society for Vascular Surgery/International Society for Cardiovascular Surgery (North Ameri-can chapter) grading system for cardiovascular risk factors and comorbidity.14*

0=no risk factor1=mild2=moderate3=severe

Diabetes mellitus: 0, none; 1, adult onset, controlled by diet or oral agents; 2, adult onset, insulin controlled; 3, juvenile onset.

Tobacco use: 0, none or none for last 10 years; 1, none current, but smoked in last 10 years; 2, current (includes abstinence for less than 1 year), less than 1 pack per day; 3, current, more than 1 pack per day.

Hypertension: 0, diastolic usually lower than 90 mm Hg; 1, controlled with a single drug; 2, controlled with 2 drugs; 3, requires more than 2 drugs or is uncontrolled.

Hyperlipidemia: 0, cholesterol (low-density lipoprotein and total) and triglyceride levels within normal limits for age; 1, readily controllable by diet; 2, requires strict dietary control; 3, same as mild, but severe enough to require dietary and drug control.

Cardiac status: 0, asymptomatic with normal electrocardiogram; 1, asymptomatic but with remote myocardial infarction by electrocardiogram, or fixed defect on dipyridamole thallium or similar scan; 2, any one of the following: stable angina, no angina (but significant reversible perfusion defect on dipyridamole thallium scan), significant silent ischemia (≥1% of the time) on Holter monitoring, ejec-tion fraction 25% to 45%, controlled ectopy or asymptomatic arrhythmia, or history of congestive heart failure that is now well compensated; 3, any one of the following: unstable angina, symptomatic or poorly controlled ectopy/arrhythmia (chronic/recurrent), poorly compensated or recurrent congestive heart failure, ejection fraction less than 25%, or myocardial infarction within 6 months.

Carotid disease: 0, no symptoms and no evidence of disease; 1, asymptomatic but with evidence of


disease determined by duplex scan or other accepted non-invasive test or arteriogram; 2, transient or temporary stroke; 3, completed stroke with permanent neurological deficit or acute stroke.

Renal status: (refers to stable levels, not transient decreases or increases in response to intravenous medication, hydration, or contrast media): 0, no known renal disease, normal serum creatinine level; 1, moderately increased creatinine level, as high as 2.4 mg/dL; 2, creatinine level of 2.5 to 5.9 mg/dL; 3, creatinine level greater than 6.0 mg/dL or on dialysis or with kidney transplant.

Pulmonary status: 0, asymptomatic, normal chest x-ray film, pulmonary function tests within 20% of predicted; 1, asymptomatic or mild dyspnea on exertion, mild chronic parenchymal x-ray changes, pulmonary function tests 65% to 80% of predicted; 2, between 1 and 3; 3, vital capacity less than 1.85 L, forced expiratory volume in 1 second less than 1.2L or less than 35% of predicted, maximal voluntary ventilation less than 50% of predicted, Pco2 greater than 45 mm Hg, supplemental oxygen use medically necessary, or pulmonary hypertension.

*We dichotomized the cardiovascular risk factors in our analyses into absence of the risk factor (=0) and all the other values (mild, moderate, severe) into presence of the risk factor (=1).


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2. Meru AV, Mittra S, Thyagarajan B, Chugh A. Intermittent claudication: an overview. Atherosclerosis 2006;187:221-37.

3. De Backer G, Ambrosioni E, Borch-Johnsen K, Brotons C, Cifkova R, Dallongeville J, et al. European guidelines on cardiovascular disease prevention in clinical practice. Third Joint Task Force of European and other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representa-tives of eight societies and by invited experts). Atherosclerosis 2004;173:381-91.

4. Vaccarino V, Kasl SV, Abramson J, Krumholz HM. Depressive symptoms and risk of functional decline and death in patients with heart failure. J Am Coll Cardiol 2001;38:199-205.

5. Thomas AJ, Kalaria RN, O’Brien JT. Depression and vascular disease: what is the relationship? J Affect Disord 2004;79:81-95.

6. Kaptein KI, de Jonge P, van den Brink RH, Korf J. Course of depressive symptoms after myocardial infarc-tion and cardiac prognosis: a latent class analysis. Psychosom Med 2006;68:662-8.

7. Geerlings SW, Beekman AT, Deeg DJ, Twisk JW, Van Tilburg W. Duration and severity of depression predict mortality in older adults in the community. Psychol Med 2002;32:609-18.





12. Heald CL, Fowkes FG, Murray GD, Price JF. Risk of mortality and cardiovascular disease associated with the ankle-brachial index: systematic review. Atherosclerosis 2006;189:61-9.



14. Rutherford RB, Baker JD, Ernst C, Johnston KW, Porter JM, Ahn S, et al. Recommended standards for reports dealing with lower extremity ischemia: revised version. J Vasc Surg 1997;26:517-38.

15. Kronish IM, Rieckmann N, Halm EA, Shimbo D, Vorchheimer D, Haas DC, et al. Persistent depression affects adherence to secondary prevention behaviors after acute coronary syndromes. J Gen Intern Med 2006;21:1178-83.

16. Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1977;1:385-401.

17. Irwin M, Artin KH, Oxman MN. Screening for depression in the older adult: criterion validity of the 10-item Center for Epidemiological Studies Depression Scale (CES-D). Arch Intern Med 1999;159:1701-4.

18. Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES-D (Center for Epide-miological Studies Depression) depression symptoms index. J Aging Health 1993;5:179-93.

19. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Washington, DC: American Psychiatric Publishing; 1994.

20. Cheng ST, Chan AC. The Center for Epidemiologic Studies Depression Scale in older Chinese: thresholds for long and short forms. Int J Geriatr Psychiatry 2005;20:465-70.

21. Roose SP, Miyazaki M. Pharmacologic treatment of depression in patients with heart disease. Psychosom Med 2005;67 Suppl 1:S54-7.

22. van Melle JP, Verbeek DE, van den Berg MP, Ormel J, van der Linde MR, de Jonge P. Beta-blockers and depression after myocardial infarction: a multicenter prospective study. J Am Coll Cardiol 2006;48:2209-14.

23. Jones B, Nagin D, Roeder K. A SAS procedure based on mixture models for estimating developmental trajectories. Sociol Method Res 2001;29:374-93.

24. McDermott MM, Guralnik JM, Ferrucci L, Criqui MH, Greenland P, Tian L, et al. Functional decline in lower extremity peripheral arterial disease: associations with comorbidity, gender, and race. J Vasc Surg 2005;42:1131-7.

25. Lavoie KL, Fleet RP, Lesperance F, Arsenault A, Laurin C, Frasure-Smith N, et al. Are exercise stress tests appropriate for assessing myocardial ischemia in patients with major depressive disorder? Am Heart J 2004;148:621-7.

26. McDermott MM, Liu K, Ferrucci L, Criqui MH, Greenland P, Guralnik JM, et al. Physical performance in pe-ripheral arterial disease: a slower rate of decline in patients who walk more. Ann Intern Med 2006;144:10-20.

27. Smith TC, Wingard DL, Smith B, Kritz-Silverstein D, Barrett-Connor E. Walking decreased risk of cardio-vascular disease mortality in older adults with diabetes. J Clin Epidemiol 2007;60:309-17.

28. Garg PK, Tian L, Criqui MH, Liu K, Ferrucci L, Guralnik JM, et al. Physical activity during daily life and mortality in patients with peripheral arterial disease. Circulation 2006;114:242-8.


29. Osborn DP, Fletcher AE, Smeeth L, Stirling S, Bulpitt CJ, Breeze E, et al. Factors associated with depres-sion in a representative sample of 14 217 people aged 75 and over in the United Kingdom: results from the MRC trial of assessment and management of older people in the community. Int J Geriatr Psychiatry 2003;18:623-30.

30. Havranek EP, Spertus JA, Masoudi FA, Jones PG, Rumsfeld JS. Predictors of the onset of depressive symptoms in patients with heart failure. J Am Coll Cardiol 2004;44:2333-8.

31. Lenze EJ, Schulz R, Martire LM, Zdaniuk B, Glass T, Kop WJ, et al. The course of functional decline in older people with persistently elevated depressive symptoms: longitudinal findings from the Cardiovascu-lar Health Study. J Am Geriatr Soc 2005;53:569-75.

32. Penninx BW, Deeg DJ, van Eijk JT, Beekman AT, Guralnik JM. Changes in depression and physical decline in older adults: a longitudinal perspective. J Affect Disord 2000;61:1-12.

33. Lyness JM, King DA, Conwell Y, Cox C, Caine ED. Cerebrovascular risk factors and 1-year depression outcome in older primary care patients. Am J Psychiatry 2000;157:1499-501.

34. Van den Berg MD, Oldehinkel AJ, Bouhuys AL, Brilman EI, Beekman AT, Ormel J. Depression in later life:

three etiologically different subgroups. J Affect Disord 2001;65:19-26.

Chapter 5

Younger women with peripheral arterial disease are at increased risk

of depressive symptoms

5

104 Chapter 5 - Younger women, depressive symptoms, PAD

Smolderen KG, Spertus JA, Vriens PW, Kranendonk S, Nooren M, Denollet J. Younger women with peripheral arterial disease are at increased risk of depressive symptoms. Submitted.

ABSTRACT

Background: Gender disparities, particularly among young women with cardiovascular disease, are a growing cause for concern. Depression is a prevalent and prognostically important comorbidity in peripheral arterial disease (PAD), but its prevalence has not been described as a function of gender and age. Therefore, we compared depressive symptoms at the time of diagnosis and six months later by gender and age in PAD patients.

Methods: In this multi-center observational follow-up study, a total of 444 newly diagnosed PAD patients (32% females) from two Dutch vascular outpatient clinics completed the 10-item CES-D at baseline and six months later (significant depressive symptoms indicated CES-D scores ≥4).

Results: Initially, 33% of women <65 years had significant depressive symptoms, and six months later, 19% of the other younger women developed significant depressive symptoms; rates much higher than other gender-age groups (range at baseline=11-16%, 6-month incidence=6-10%; P≤.03). Adjusting for demographics and clinical factors, women <65 years experienced a 4-fold greater odds of baseline (OR=4.3 [95%CI 2.2-8.7]) and follow-up depressive symptoms (OR=4.1 [2.0-8.4]) com-pared with men ≥65 years, whereas other gender-age groups were not at risk. Additional adjustment for change in ankle-brachial index did not explain the increased risk in younger women (OR=3.5 [1.2-10.2]).

Conclusions: Significant depressive symptoms are more common in younger women with PAD than in other gender-age groups, both at the time of diagnosis and six months later. To eradicate gender-based disparities in PAD, depression screening and monitoring in younger women may be an impor-tant direction for future research and intervention.


BACKGROUND

Morbidity and mortality rates in patients afflicted with peripheral arterial disease (PAD) range from 30% to 70% over the 5 to 15 years following their diagnosis.1 PAD greatly impacts physical function-ing, with PAD patients having greater functional impairment and more rapid functional decline than patients without PAD.2 Preliminary findings suggest that women with PAD are at particularly high risk to experience leg pain on exertion and rest, to have poorer functioning, and greater walking impair-ment than men with PAD.3

Apart from the physical burden, depression is a common comorbidity in PAD patients, affecting ap-proximately one out of five PAD patients.4-7 Depressive symptoms among cardiovascular patients are associated with substantially compromised functional status8 and poor prognosis.9 Research in patients with coronary artery disease, and in the general population, suggests that younger women, in particular, may be at increased risk of experiencing significant depressive symptoms as compared with other gender-age groups.10 The degree to which depressive symptoms differ as a function of gender and age has not been examined in PAD, but is important to establish since it may mediate the worse health status and poorer outcomes of young women and may emerge as an important potential target for intervention.

The objective of the current study was to examine baseline and six months follow-up rates of sig-nificant depressive symptoms according to gender and age groups in a prospective registry of PAD patients. This comparison was performed to identify potentially actionable targets to improve the prognosis of young women, a particularly vulnerable group of PAD patients.


METHODS

Participants and study design

PAD patients presenting with symptomatic disease were consecutively enrolled from two vascular outpatient clinics of the St. Elisabeth Hospital (between September 2001-June 2008) and the Twee Steden Hospital (March 2006-May 2008) in Tilburg, The Netherlands. Patients were included if they had an abnormal resting ankle-brachial index (ABI) (≤0.90) or an abnormal post-exercise ABI (ABI decrease of 15% after exercise).11 Patients with critical leg ischemia, significant cognitive impairment, severe psychiatric comorbidities (e.g., psychosis), insufficient knowledge of the Dutch language, or life-threatening conditions were excluded. All participating patients received a diagnostic work-up, including vascular laboratory assessment, and completed self-report questionnaires at baseline and at six months follow-up. Information about clinical factors was obtained from medical chart abstraction at baseline. A subset of patients (patients enrolled after March 2006), underwent repeated vascular laboratory assessment at six months follow-up. The study was approved by the institutional review board of each participating hospital and all participants provided written informed consent.

Data collection

Assessment of depressive symptomsDepressive symptoms were evaluated with an abbreviated 10-item version of the Center for Epidemi-ological Studies Depression Scale (CES-D).12, 13 This measure has good reliability with a Cronbach’s alpha of 0.88. Using an optimal cut-off score of ≥4, the 10-item CES-D has a sensitivity of 97% and a specificity of 84% for a diagnosis of major depression using the DSM-IV criteria14 in younger individu-als and a sensitivity of 100% and specificity of 93% in adults older than 60.12

Vascular laboratory assessmentA handheld Doppler ultrasonic instrument (Imexlab 9000; Imex Medical Systems Inc, Golden Colo-rado) was used by trained technicians to obtain systolic blood pressure readings in the right and left brachial arteries, right and left dorsalis pedis arteries, and right and left posterior tibial arteries. The ABI at rest and after walking on a treadmill was registered according to the current TASC guidelines.11


In addition, walking distance until pain occurred (pain-free walking distance) and maximum walking distance was registered in all patients.


Baseline characteristics were compared by four gender-age groups (women <65 years, women ≥65 years, men <65 years, and men ≥65 years, with the latter serving as the referent group). Mean de-pressive symptom scores and depressive symptom rates (CES-D ≥4) were compared between these four gender-age groups using ANOVA for continuous variables and Chi-square tests for categorical variables. Bonferroni correction was used in post hoc analyses to control for Type I errors. Three pairwise comparisons between men ≥65 years and the other gender-age categories were performed. Assuming an alpha of .05 and three pairwise comparisons, a P value of .02 was considered statisti-cally significant in post hoc analyses.

To compare the relative strength of the association between patient characteristics and baseline de-pressive symptoms, we compared standardized measures of effect using Cohen’s d (mean1 - mean2 /pooled standard deviation). This was calculated for those patient characteristics that were felt to be clinically important (gender-age groups, partner status, education, working status, hypercholes-terolemia, hypertension, diabetes mellitus, cardiac disease, cerebrovascular disease, chronic renal failure, chronic lung disease, chronic back pain, hip or knee osteoarthritis, smoking, body mass index, ABI, and pain-free walking distance).

Multiple logistic regression models were then constructed to evaluate the unadjusted and adjusted relationship between the four gender-age groups (men ≥65 years were used as reference category) and baseline and six months follow-up depressive symptoms. Baseline and six months follow-up de-pressive symptoms were defined as CES-D scores ≥4. Follow-up depressive symptoms consisted of both patients with persistent depressive symptoms (CES-D score ≥4 at baseline and follow-up) and incident depressive symptoms (CES-D score <4 at baseline, but ≥4 at follow-up). Multivariable analy-ses were performed with adjustment for disease severity (ABI), clinical factors (diabetes mellitus, prior cardiac disease, prior cerebrovascular disease, chronic lung disease, chronic back pain), and sociodemographics (marital status, education, working status). Follow-up analyses were additionally adjusted for baseline depressive symptoms and whether or not patients received peripheral revas-


cularization within the 6-month follow-up period. Secondary analyses were performed in patients with repeated vascular laboratory assessment: change ABI scores were calculated and added as a covariate in the model to evaluate whether changes in disease severity contributed to the association with six months follow-up depressive symptoms. All analyses were performed with SPSS 17.0 for Windows (SPSS inc., Chicago, Illinois) and P values <0.05 were considered statistically significant.


RESULTS

There were 634 eligible patients screened for depressive symptoms at baseline. At six months, 32 patients were not able to provide follow-up data on depressive symptoms (17 died, 7 had a life-threatening condition, 4 were hospitalized, and 4 could not be contacted) and 132 did not return the questionnaire, resulting in 470 (78.1%) patients. Of these, 26 had incomplete CES-D questionnaires that precluded derivation of a score, leaving 444 patients for our final analyses. Non-responders did not systematically differ from responders on baseline characteristics (including age and gender), ex-cept that non-responders were less likely to have a partner (35% vs. 26%, P=.01) and had a shorter maximum walking distance (329m vs. 378m, P=.04). Importantly, mean baseline depressive symp-toms were not significantly different between responders and non-responders (1.9 vs. 2.0, P=.60).

Gender-age groups

The cohort consisted of 14% female patients <65 years, 18% female patients ≥65 years, 34% male patients <65 years, and 34% male patients ≥65 years. Baseline characteristics, stratified by gender-age groups (men ≥65 years reference category), are presented in Table 1. There were significant dif-ferences between groups in marital status, education, working status, prior cardiac and cerebrovas-cular disease, smoking status, ABI, use of aspirin, calcium antagonists, beta blockers, and nitrates. Younger women with PAD were less likely to have prior cardiac disease and were less likely to be treated with cardioprotective medication as compared with men ≥65 years. Importantly, younger women were more likely to be active smokers (71%). Women ≥65 years were more likely to live without a partner as compared with men ≥65 years. Finally, younger men were more likely to be more educated, to be actively working and to be smokers, but were less likely to have a history of cardiac disease as compared with men ≥65 years.


Tabl

e 1 –

Base

line c

hara

cter

istics

of t

he to

tal s

ampl

e and

stra

tified

by g

ende

r and

age.

Wom

en

Men

<6

5 yea

rs

n=63

≥65 y

ears

n=

81

<65 y

ears

n=

150

≥65 y

ears

* n=

150

P va

lue

Demo

grap

hics

Age,

mean

(SD,

rang

e),y

ears

56.4

(6.1,

37-6

4)†

72.2

(6.0,

65-9

2)

57.5

(5.0,

39-6

4)†

72.6

(5.0,

65-8

5)

<.000

1So

cioec

onom

ic fac

tors

Nopa

rtner

, No.

(%)

17 (2

7)

39 (4

8)†

21 (1

4)†

36 (2

4)

<.000

1 Le

ss th

an hi

gh sc

hool

educ

ation

, No.

(%)

17 (2

7)

28 (3

5)

23 (1

5)†

52 (3

5)

.001

Wor

king f

ull- o

r par

t-tim

e, No

. (%

) 31

(49)

† 9 (

11)†

71

(47)

† 5 (

3)

<.000

1

Medic

al his

tory

Hype

rchole

stero

lemia,

No.

(%)

43 (6

8)

52 (6

4)

95(6

3)95

(63)

.91

Hype

rtens

ion, N

o. (%

)28

(44)

† 48

(59)

77

(51)

90 (6

0)

.10Di

abete

s mell

itus,

No. (

%)

11 (1

8)

17 (2

1)

30(2

0)39

(26)

.47

Prior

card

iac di

seas

e, No

. (%

)11

(18)

† 31

(38)

36

(24)

† 75

(50)

<.0

001

Prior

cere

brov

ascu

lar di

seas

e, No

. (%

)6 (

10)

4 (5)

† 22

(15)

32

(21)

<.0

1 Ch

ronic

rena

l failu

re, N

o. (%

)2 (

3)

8 (10

) 9 (

6)

14 (9

) .31

Chro

nic lu

ng di

seas

e, No

. (%

)9 (

14)

11 (1

4)

12 (8

) 22

(15)

.29

Chro

nic ba

ck pa

in, N

o. (%

)8 (

13)

15 (1

9)

16(1

1)22

(15)

.40

Knee

or hi

p oste

oarth

ritis,

No. (

%)

6 (10

) 15

(19)

18

(12)

29 (1

9)

.14Lif

e-sty

le fac

tors

Smok

ed w

ithin

last 3

0 day

s, No

. (%

)45

(71)

† 34

(42)

93

(62)

† 53

(35)

<.0

001

Body

mas

s ind

ex, m

ean (

SD)

26.9

(5.9)

26

.3 (5

.5)

26.7

(5.0)

26

.3 (4

.9)

.80Va

scula

r labo

rator

y ass

essm

ent

Ankle

-bra

chial

inde

x, me

an (S

D)0.6

6 (0.1

5)

0.59 (

0.15)

0.6

7 (0.1

7)

0.63 (

0.19)

.01

Pa

in-fre

e walk

ing di

stanc

e,me

an (S

D), m

97.3

(121

.1)

92.5

(106

.6)

124.5

(131

.8)

122.7

(151

.9)

.08

Maxim

um w

alking

dista

nce,

me

an (S

D), m

372.7

(307

.2)

266.6

(241

.8)

444.6

(321

.4)

370.0

(314

.0)

.001

Reva

scula

rizati

on da

ta PT

A, N

o. (%

)26

(41)

23

(28)

48

(32)

40 (2

7)

.19By

pass

surg

ery,

No. (

%)

3 (5)

4 (

5)

7 (5)

4 (

3)

.77En

darte

recto

my, N

o. (%

)2 (

3)

0 (0)

3 (

2)

6 (4)

.29

Medic

ation

use

Stati

ns, N

o. (%

)45

(71)

54

(66.7

) 88

(59)

105 (

70)

.14As

pirin,

No.

(%)

30 (4

8)†

52 (6

4)

87 (5

8)

103 (

69)

.03

Ace i

nhibi

tors,

No. (

%)

12 (1

9)

26 (3

2)

49(3

3)57

(38)

.06

Antic

oagu

lants,

No.

(%)

7 (11

) 15

(19)

17

(11)

28 (1

9)

.20Ca

lcium

antag

onist

s, No

. (%

)5 (

8)†

15 (1

9)

35 (2

3)

37 (2

5)

.04

Beta

block

ers,

No. (

%)

13 (2

1)†

36 (4

4)

40 (2

7)†

72 (4

8)

<.000

1 Di

ureti

cs, N

o. (%

)9 (

14)

18 (2

2)

26(1

7)30

(20)

.61

Nitra

tes, N

o. (%

)0 (

0)†

5 (6)

3 (

2)†

12 (8

) .02

Di

goxin

, No.

(%)

0 (0)

2 (

3)

1 (1)

3 (

2)

.45An

ti-arrh

ythmi

cs, N

o. (%

)0 (

0)

4 (5)

2 (

1)

8 (5)

.08

Depr

essio

n tre

atmen

t An

ti-dep

ress

ants,

No.

(%)

6 (10

) 3 (

4)

6 (4)

6 (

4)

.30Cu

rrentl

y rec

eiving

coun

selin

g,No

. (%

)‡

2 (4)

1 (

2)

4 (3)

1 (

1)

.35


*Ref

eren

ce g

roup

for t

he o

ther

thre

e ge

nder

-age

cate

gorie

s.†V

alues

are

sta

tistic

ally

signifi

cant

ly dif

fere

nt b

etwe

en m

en ≥

65 y

ears

and

gen

der-a

ge c

ateg

ory.

Thre

e pa

irwise

com

paris

ons

betw

een

men

≥65

yea

rs a

nd o

ther

ge

nder

-age

cate

gorie

s wer

e m

ade

using

ana

lysis

of va

rianc

e (B

onfe

rroni

corre

ction

). A

P va

lue o

f .02

was

use

d as

the

level

of st

atist

ical s

ignific

ance

for t

he p

airwi

se

com

paris

ons.

Abbr

eviat

ions:

PTA,

per

cuta

neou

s tra

nslum

inal a

ngiop

lasty;

SD,

stan

dard

dev

iation

. ‡Av

ailab

le in

253

patie

nts.

Wom

en

Men

<6

5 yea

rs

n=63

≥65 y

ears

n=

81

<65 y

ears

n=

150

≥65 y

ears

* n=

150

P va

lue

Demo

grap

hics

Age,

mean

(SD,

rang

e),y

ears

56.4

(6.1,

37-6

4)†

72.2

(6.0,

65-9

2)

57.5

(5.0,

39-6

4)†

72.6

(5.0,

65-8

5)

<.000

1So

cioec

onom

ic fac

tors

Nopa

rtner

, No.

(%)

17 (2

7)

39 (4

8)†

21 (1

4)†

36 (2

4)

<.000

1 Le

ss th

an hi

gh sc

hool

educ

ation

, No.

(%)

17 (2

7)

28 (3

5)

23 (1

5)†

52 (3

5)

.001

Wor

king f

ull- o

r par

t-tim

e, No

. (%

) 31

(49)

† 9 (

11)†

71

(47)

† 5 (

3)

<.000

1

Medic

al his

tory

Hype

rchole

stero

lemia,

No.

(%)

43 (6

8)

52 (6

4)

95(6

3)95

(63)

.91

Hype

rtens

ion, N

o. (%

)28

(44)

† 48

(59)

77

(51)

90 (6

0)

.10Di

abete

s mell

itus,

No. (

%)

11 (1

8)

17 (2

1)

30(2

0)39

(26)

.47

Prior

card

iac di

seas

e, No

. (%

)11

(18)

† 31

(38)

36

(24)

† 75

(50)

<.0

001

Prior

cere

brov

ascu

lar di

seas

e, No

. (%

)6 (

10)

4 (5)

† 22

(15)

32

(21)

<.0

1 Ch

ronic

rena

l failu

re, N

o. (%

)2 (

3)

8 (10

) 9 (

6)

14 (9

) .31

Chro

nic lu

ng di

seas

e, No

. (%

)9 (

14)

11 (1

4)

12 (8

) 22

(15)

.29

Chro

nic ba

ck pa

in, N

o. (%

)8 (

13)

15 (1

9)

16(1

1)22

(15)

.40

Knee

or hi

p oste

oarth

ritis,

No. (

%)

6 (10

) 15

(19)

18

(12)

29 (1

9)

.14Lif

e-sty

le fac

tors

Smok

ed w

ithin

last 3

0 day

s, No

. (%

)45

(71)

† 34

(42)

93

(62)

† 53

(35)

<.0

001

Body

mas

s ind

ex, m

ean (

SD)

26.9

(5.9)

26

.3 (5

.5)

26.7

(5.0)

26

.3 (4

.9)

.80Va

scula

r labo

rator

y ass

essm

ent

Ankle

-bra

chial

inde

x, me

an (S

D)0.6

6 (0.1

5)

0.59 (

0.15)

0.6

7 (0.1

7)

0.63 (

0.19)

.01

Pa

in-fre

e walk

ing di

stanc

e,me

an (S

D), m

97.3

(121

.1)

92.5

(106

.6)

124.5

(131

.8)

122.7

(151

.9)

.08

Maxim

um w

alking

dista

nce,

me

an (S

D), m

372.7

(307

.2)

266.6

(241

.8)

444.6

(321

.4)

370.0

(314

.0)

.001

Reva

scula

rizati

on da

ta PT

A, N

o. (%

)26

(41)

23

(28)

48

(32)

40 (2

7)

.19By

pass

surg

ery,

No. (

%)

3 (5)

4 (

5)

7 (5)

4 (

3)

.77En

darte

recto

my, N

o. (%

)2 (

3)

0 (0)

3 (

2)

6 (4)

.29

Medic

ation

use

Stati

ns, N

o. (%

)45

(71)

54

(66.7

) 88

(59)

105 (

70)

.14As

pirin,

No.

(%)

30 (4

8)†

52 (6

4)

87 (5

8)

103 (

69)

.03

Ace i

nhibi

tors,

No. (

%)

12 (1

9)

26 (3

2)

49(3

3)57

(38)

.06

Antic

oagu

lants,

No.

(%)

7 (11

) 15

(19)

17

(11)

28 (1

9)

.20Ca

lcium

antag

onist

s, No

. (%

)5 (

8)†

15 (1

9)

35 (2

3)

37 (2

5)

.04

Beta

block

ers,

No. (

%)

13 (2

1)†

36 (4

4)

40 (2

7)†

72 (4

8)

<.000

1 Di

ureti

cs, N

o. (%

)9 (

14)

18 (2

2)

26(1

7)30

(20)

.61

Nitra

tes, N

o. (%

)0 (

0)†

5 (6)

3 (

2)†

12 (8

) .02

Di

goxin

, No.

(%)

0 (0)

2 (

3)

1 (1)

3 (

2)

.45An

ti-arrh

ythmi

cs, N

o. (%

)0 (

0)

4 (5)

2 (

1)

8 (5)

.08

Depr

essio

n tre

atmen

t An

ti-dep

ress

ants,

No.

(%)

6 (10

) 3 (

4)

6 (4)

6 (

4)

.30Cu

rrentl

y rec

eiving

coun

selin

g,No

. (%

)‡

2 (4)

1 (

2)

4 (3)

1 (

1)

.35


Significant depressive symptoms

Of the 444 patients screened for depressive symptoms, 17% (75/444) were classified as having sig-nificant baseline depressive symptoms (CES-D≥4). Mean CES-D scores and depressive symptom rates (CES-D ≥4) are presented in Table 2. Depressive symptom rates at baseline were highest in women <65 years (33%), followed by women ≥65 years and male PAD patients (range 11-16%) (P=.001). Importantly, at 6-month follow-up, significant depressive symptoms affected up to 40% in women <65 years (17 to 21% in other gender-age groups, P=.001) and incidence of new, significant depressive symptoms at six months among patients who did not screen positive at baseline was significantly higher in women <65 years (19% in women <65 years vs. 6 to 10% in other gender-age groups, P=.03).


Tabl

e 2

– Me

an d

epre

ssive

sym

ptom

sco

res

and

depr

essiv

e sy

mpt

oms

rate

s at

bas

eline

and

6 m

onth

s fo

llow-

up b

y ge

nder

-age

gr

oups

.

*Ref

eren

ce g

roup

for t

he o

ther

thre

e ge

nder

-age

cate

gorie

s.†V

alues

are

sta

tistic

ally

signifi

cant

ly dif

fere

nt b

etwe

en m

en ≥

65 y

ears

and

gen

der-a

ge c

ateg

ory.

Thre

e pa

irwise

com

paris

ons

betw

een

men

≥65

yea

rs a

nd o

ther

ge

nder

-age

cate

gorie

s wer

e m

ade

using

ana

lysis

of va

rianc

e (B

onfe

rroni

corre

ction

). A

P va

lue o

f .02

was

use

d as

the

level

of st

atist

ical s

ignific

ance

for t

he p

airwi

se

com

paris

ons.

Abbr

eviat

ions:

PTA,

per

cuta

neou

s tra

nslum

inal a

ngiop

lasty;

SD,

stan

dard

dev

iation

. ‡A

vaila

ble in

253

pat

ients.

Wom

en

Men

<65 y

ears

n=

63

≥65 y

ears

n=

81

<65 y

ears

n=

150

≥65 y

ears

* n=

150

P va

lue

Base

line

CES-

D sc

ore,

mean

(SD)

2.7

(1.9)

† 2.0

(1.8)

1.8

(1.8)

1.8

(1.5)

.01

CE

S-D ≥4

, No.

(%)

21 (3

3.3)†

13

(16.0

) 24

(16.0

) 17

(11.3

) .00

1

6 Mon

ths fo

llow-

up

CES-

D sc

ore,

mean

(SD)

2.7

(1.8

) 2.4

(2.0)

1.9

(1.9)

2.0

(1.9)

.02

CE

S-D ≥4

, No.

(%)

25 (3

9.7)†

17

(21.0

) 26

(17.3

) 26

(17.3

) .00

1 Inc

ident

CES-

D ≥4

, No.

(%)

12 (1

9.0)†

8 (

9.9)

9 (6.0

) 14

(9.3)

.03


To facilitate the interpretation of these gender-age associations, Cohen’s d effect sizes were calculat-ed for the association between gender-age groups and baseline depressive symptoms, as well as for relevant sociodemographic and clinical factors, and disease severity indices (Figure 1). A much larger effect size was observed for the association between younger women and depressive symptoms as compared with the effect sizes for PAD severity indices. Other factors with moderate effect sizes with baseline depressive symptoms were having no partner and chronic lung disease.

Figure 1 – Effect sizes of patient characteristics associated with baseline depressive symp-toms. Abbreviations: ABI, ankle-brachial index; PFWD, pain-free walking distance.

0.0 0.1 0.2 0.3 0.4 0.5 0.6

PFWD (lowest 25%)

ABI (lowest 25%)

BMI (highest 25%)

Smoking

Hip or knee osteoarthritis

Chronic back pain

Chronic lung disease

Chronic renal failure

Cerebrovascular disease

Cardiac disease

Diabetes mellitus

Hypertension

Hypercholesterolemia

Not working

Low education

No partner

65 years≥≥≥≥Men

Men <65 years

65 years≥≥≥≥Women

Women <65 years

Cohen's d

0.2 = small effect0.5 = medium effect


Risk estimates for gender-age groups and baseline depressive symptoms

Risk estimates for the gender-age groups and baseline depressive symptoms (CES-D ≥4) are shown in Figure 2. Women <65 years had more than a 3-fold greater odds for experiencing baseline depres-sive symptoms (Unadjusted Odds Ratio [OR]=3.2, 95%CI 1.5-6.8) compared with men ≥65 years (reference group) (Figure 2 a, left). Other gender-age groups were not significantly associated with baseline depressive symptoms. After adjusting for disease severity and clinical factors in multivari-able models, women <65 years remained at increased risk of having significant depressive symptoms (Adjusted OR=4.3, 95%CI 2.2-8.7, P<.0001) (Figure 2a, right). Further adjustment for sociodemo-graphic variables did not change these results (Adjusted OR for women <65 years=5.4, 95%CI 2.6-11.4, P<.0001).

Risk estimates for gender-age groups and 6-month depressive symptoms

At six months follow-up, women <65 years had a 3-fold increased risk of experiencing depressive symptoms (Unadjusted OR=3.1, 95%CI 1.6-6.1) (Figure 2b, left). Other gender-age groups were not significantly associated with 6-month depressive symptoms. Adjusting for disease severity, clini-cal factors, revascularization, and baseline depressive symptoms, women <65 years remained at increased risk of having significant depressive symptoms (Adjusted OR=4.1, 95%CI 2.0-8.4, P=.03) (Figure 2 b, right). Further adjustment for sociodemographics did not change these results (Adjusted OR for women <65 years=2.9, 95%CI 1.2-7.2, P<.0001).


Figure 2 a, b – Model estimates–OR [95%

CI]–of risk for baseline depressive symptom

s (CES-D ≥4) and six months follow-up depressive sym

ptoms (CES-D

≥4) for gender-age groups. Abbreviations: CI, confidence interval; OR, odds ratio. *Multivariable analyses adjusted for: ankle-brachial index, diabetes mellitus, prior cardiac disease, prior cerebrovascular disease, chronic lung disease. Follow-up analysis was additionally adjusted for baseline depressive symptoms and peripheral revascularization during follow-up.

0.1

11

0

Me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤

Me

n

Wo

me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤W

om

en

Un

ad

jus

ted

Wo

me

n <

65

ye

ars

Le

ss

like

ly

Wo

me

n≥≥≥ ≥6

5 y

ea

rs

Me

n <

65

ye

ars

Me

n≥≥≥ ≥6

5 y

ea

rs

Mo

re lik

ely

3.2

[1.5

-6.8

]

1.4

[0.6

-3.3

]

1.4

[0.7

-2.8

]

1.0

[1.0

-1.0

]

OR

[95

% C

I]0

.11

10

Me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤

Me

n

Wo

me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤W

om

en

Ad

jus

ted

*

Wo

me

n <

65

ye

ars

Le

ss

like

ly

Wo

me

n≥≥≥ ≥6

5 y

ea

rs

Me

n <

65

ye

ars

Me

n≥≥≥ ≥6

5 y

ea

rs

Mo

re lik

ely

4.3

[2.2

-8.7

]

1.3

[0.6

-2.9

]

1.5

[0.8

-2.9

]

1.0

[1.0

-1.0

]

OR

[95

% C

I]

0.1

11

0

Me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤

Me

n

Wo

me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤W

om

en

Un

ad

jus

ted

Wo

me

n <

65

ye

ars

Le

ss

like

ly

Wo

me

n≥≥≥ ≥6

5 y

ea

rs

Me

n <

65

ye

ars

Me

n≥≥≥ ≥6

5 y

ea

rs

Mo

re lik

ely

3.1

[1.6

-6.1

]

1.3

[0.6

-2.5

]

1.0

[0.6

-1.8

]

1.0

[1.0

-1.0

]

OR

[95

% C

I)]0

.11

10

Me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤

Me

n

Wo

me

n >

65

ye

ars

65

ye

ars

≤≤≤ ≤W

om

en

Ad

jus

ted

*

Wo

me

n <

65

ye

ars

Le

ss

like

ly

Wo

me

n≥≥≥ ≥6

5 y

ea

rs

Me

n <

65

ye

ars

Me

n≥≥≥ ≥6

5 y

ea

rs

Mo

re lik

ely

4.1

[2.0

-8.4

]

1.3

[0.6

-2.7

]

1.2

[0.6

-2.3

]

1.0

[1.0

-1.0

]

OR

[95

% C

I]

≥≥≥ ≥

≥≥≥ ≥


Changes in PAD severity and depressive symptoms

To evaluate whether changes in PAD severity explained the association between gender-age and de-pressive symptoms at six months follow-up, change ABI scores were calculated. Repeated vascular laboratory assessment was available in 269 patients. Mean increase in ABI was 0.12 in women <65 years, 0.09 in women ≥65 years, 0.10 in males <65 years, and 0.05 in men ≥65 years (P=.18). Risk estimates of gender-age groups and depressive symptoms at six months follow-up were evaluated, while adding change ABI in the logistic regression model. A trend was observed for the association between increased ABI and a lower risk of follow-up depressive symptoms (OR=0.9, 95%CI 0.9-1.1, P=.13) but women <65 years remained at increased risk of experiencing depressive symptoms at six months follow-up (OR=3.5, 95%CI 1.2-10.2, P=.02), after adjusting for their greater improvements in ABIs.


DISCUSSION

In this prospective multi-center PAD registry, we found that depressive symptoms were significantly more common among young women at the time of PAD diagnosis, being present in up to a third of women aged <65 years, as compared with prevalence rates of 11 to 16% in other gender-age groups. Moreover, prevalence rates significantly increased over time, affecting 40% of younger women at six months follow-up. Even after adjustment for PAD severity, clinical factors, and sociodemograph-ics, younger women experienced a >4-fold increased risk of significant depressive symptoms both at baseline and at follow-up as compared with men ≥65 years. Other gender-age groups had no increased risk of having significant depressive symptoms neither at baseline, nor at follow-up. Im-portantly, the increased risk of depressive symptoms in younger women may represent a large dif-ference: point estimates for younger women were not overlapping with the estimates for the other gender-age groups with confidence intervals showing little overlap.

This is the first study that highlights the vulnerability of younger women with PAD in terms of their mental health. Although depressive symptoms have been previously demonstrated to be prevalent in PAD,5-7 they have never been specifically evaluated in the subgroup of younger women with PAD. Recently, there has been an increased awareness for the disproportionate high rates of depressive symptoms in female – especially younger - cardiac patients10 and gender disparities in terms of ad-verse outcomes15, 16 and impaired health status.17, 18 In contrast, there is a paucity of research describ-ing gender-specific differences in PAD.

Despite the fact that PAD is at least as common in women and men,19-21 PAD is typically considered as a disease that manifests itself in men22 and likewise women are often underrepresented in study reports on PAD. Preliminary findings, however, indicate that women with PAD are more likely to be undertreated,23 experience more physical disability,3 and have more adverse outcomes following revascularization.24 Our current findings support these prior reports of undertreatment, in that younger women were less likely to receive cardioprotective medication as compared with other gender-age groups.

It is not clear why younger women are more susceptible to depressive symptoms compared with other gender-age groups. Their cardiovascular profile or PAD severity did not explain the higher rates of depressive symptoms in the current study. In fact, PAD severity indices only accounted for a small


amount of the variation in baseline depressive symptoms, whereas the contribution of being a female aged below 65 years was associated with a much larger effect size. Moreover, while the change in ABI severity over six months was larger in young women, they had more persistent and new-onset depressive symptoms than other gender-age groups. Other factors that were substantially associated with depressive symptoms were having no partner and chronic lung disease. Adjusting for clinical factors and sociodemographic factors like education, working or marital status, however, did not alter our findings.

Alternative explanations for higher rates of depressive symptoms in younger women suggested in the literature include the differential social roles and demands they face; care responsibilities for their families, combining work and home responsibilities, lower income and job inequality, and being a single parent. All of these may partially explain the increased susceptibility of younger women to depressive symptoms and warrant further investigation.25 Evidence for biological mechanisms (hor-monal factors, gender differences in neurotransmitter systems or genetic factors) that might explain these gender differences is inconclusive and deserves further study.25 Finally, the tendency of females to report more depressive symptoms than males26 could not explain our findings because prevalence rates of depressive symptoms in elderly women were similar to men.

It is important to note the clinical profile of younger women with PAD in the current study, and espe-cially the observation that smoking rates were high in this group. Smoking is an important risk factor in PAD and the number of pack years is associated with disease severity, increased risk of amputation, peripheral graft occlusion, and mortality.11 Therefore, smoking cessation is considered a cornerstone of PAD risk management. From a clinical perspective, smoking cessation will be an enormous chal-lenge in those presenting with depressive symptoms because the two are often intertwined, and smoking may be considered as a way of self medicating patients’ levels of distress.27 Taking away this ‘medication’ in depressed patients will require intense follow-up, additional supportive strategies, and referral for counseling should be considered in order to prevent further exacerbation of depressive symptoms.27 Our results suggest that younger women in particular may benefit from such additional supportive measures.

Finally, despite the disproportionate distribution of depressive symptoms across gender-age groups, it is notable that receiving antidepressants or counseling for depressive symptoms did not signifi-cantly differ as a function of gender-age in the current study, suggesting undertreatment of depressive


symptoms in younger women. The low proportion of depression treatment in patients with significant depressive symptoms highlights a potential opportunity to improve their treatment, particularly given that previous reports have demonstrated that depressive symptoms are associated with greater phys-ical disability in men and women with PAD6, 7 and with poor prognosis in male PAD patients.9 Apart from the implications for prognosis, depressive symptoms deserve to be treated in their own right in order to reduce the burden of depression itself. Therefore, monitoring of depressive symptoms may be a useful part of standard care in PAD. In addition, close collaboration between treating clinicians and mental health professionals need to be supported as multidisciplinary treatment teams may be necessary to optimize risk management in PAD patients.

Our study results should be interpreted in the context of the following potential limitations: no sys-tematic depression screening protocol was implemented using a psychiatric interview. Therefore, no diagnosis of major depression according to DSM-IV criteria could be established. On the other hand, the brief self-report instrument that was used, can be easily implemented in clinical practice and has been shown to have high concordance with the diagnosis of major depression.12 Furthermore, our findings may not be generalizable to community-dwelling individuals with PAD or to PAD patients seen in primary care, as our patients represented only those that consulted a vascular surgeon for symptomatic PAD. As such, we may have underestimated the magnitude of the problem as PAD is of-ten underrecognized in women, possibly due to the atypical presentation of PAD symptoms.22 Finally, although we were able to adjust for clinically important confounders in our analyses, the possibility of residual confounding remains.

In conclusion, the present study suggests that younger women with PAD are more prone to significant depressive symptoms, as compared with other gender-age groups. Up to a third experienced depres-sive symptoms at baseline and these numbers increased to 40% at follow-up. Future research will need to further develop this body of research, examining explanations for these gender-age related differences. Meanwhile, opportunities to stimulate systematic screening and treatment facilities for depressed PAD patients need to be explored, as these strategies will be necessary to further optimize PAD management in all patients, but especially in younger women with PAD.


REFERENCES

1. Hirsch AT, Haskal ZJ, Hertzer NR, Bakal CW, Creager MA, Halperin JL, et al. ACC/AHA 2005 guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic): executive summary. J Am Coll Cardiol 2006;47:1239-312.

2. McDermott MM, Liu K, Greenland P, Guralnik JM, Criqui MH, Chan C, et al. Functional decline in peripheral arterial disease: associations with the ankle brachial index and leg symptoms. JAMA. 2004;292:453-61.

3. McDermott MM, Greenland P, Liu K, Criqui MH, Guralnik JM, Celic L, et al. Sex differences in peripheral arterial disease: leg symptoms and physical functioning. J Am Geriatr Soc 2003;51:222-28.

4. Smolderen KG, Aquarius AE, de Vries J, Smith OR, Hamming JF, Denollet J. Depressive symptoms in peripheral arterial disease: a follow-up study on prevalence, stability, and risk factors. J Affect Disord 2008;110:27-35.

5. Arseven A, Guralnik JM, O’Brien E, Liu K, McDermott MM. Peripheral arterial disease and depressed mood in older men and women. Vasc Med 2001;6:229-34.


7. Ruo B, Liu K, Tian L, Ferrucci L, Guralnik JM, et al. Persistent depressive symptoms and functional decline among patients with peripheral arterial disease. Psychosom Med 2007;69:415-24.

8. Vaccarino V, Kasl SV, Abramson J, Krumholz HM. Depressive symptoms and risk of functional decline and death in patients with heart failure. J Am Coll Cardiol 2001;38:199-205.


10. Mallik S, Spertus JA, Reid KJ, Krumholz HM, Rumsfeld JS, Weintraub WS, et al. Depressive symp-toms after acute myocardial infarction: evidence for highest rates in younger women. Arch Intern Med 2006;166:876-83.


12. Irwin M, Artin KH, Oxman MN. Screening for depression in the older adult: criterion validity of the 10-item Center for Epidemiological Studies Depression Scale (CES-D). Arch Intern Med 1999;159:1701-4.

13. Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES-D (Center for Epide-miological Studies Depression) depression symptoms index. J Aging Health 1993;5:179-93.



15. Akhter N, Milford-Beland S, Roe MT, Piana RN, Kao JK, Shroff A. Gender differences among patients with acute coronary syndromes undergoing percutaneous coronary intervention in the American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR). Am Heart J 2009;157:141-8.

16. Parashar S, Rumsfeld JS, Reid KJ, Buchanan D, Dawood N, Khizer S, et al. Impact of depression on sex differences in outcome after myocardial infarction. Circ Cardiovasc Qual Outcomes 2009;2:33-40.

17. Norris CM, Hegadoren K, Pilote L. Depression symptoms have a greater impact on the 1-year health-related quality of life outcomes of women post-myocardial infarction compared to men. Eur J Cardiovasc Nurs 2007;6:92-8.

18. Ruo B, Bertenthal D, Sen S, Bittner V, Ireland CC, Hlatky MA. Self-rated health among women with coro-nary disease: depression is as important as recent cardiovascular events. Am Heart J 2006;152:921 e921-7.



21. Sigvant B, Wiberg-Hedman K, Bergqvist D, Rolandsson O, Andersson B, Persson E, et al. A population-based study of peripheral arterial disease prevalence with special focus on critical limb ischemia and sex differences. J Vasc Surg 2007;45:1185-91.

22. McDermott MM, Kerwin DR, Liu K, Martin GJ, O’Brien E, Kaplan H, et al. Prevalence and significance of unrecognized lower extremity peripheral arterial disease in general medicine practice. J Gen Intern Med 2001;16:384-90.

23. Sigvant B, Wiberg-Hedman K, Bergqvist D, Rolandsson O, Wahlberg E. Risk factor profiles and use of cardiovascular drug prevention in women and men with peripheral arterial disease. Eur J Cardiovasc Prev Rehabil 2009;16:39-46.

24. Nguyen LL, Hevelone N, Rogers SO. Disparity in outcomes of surgical revascularization for limb salvage: race and gender are synergistic determinants of vein graft failure and limb loss. Circulation 2009;119:123-30.

25. Piccinelli M, Wilkinson G. Gender differences in depression. Critical review Br J Psychiatry. 2000;177:486-92.

26. Young MA, Fogg LF, Scheftner WA, Keller MB, Fawcett JA. Sex differences in the lifetime prevalence of depression: does varying the diagnostic criteria reduce the female/male ratio? J Affect Disord 1990;18:187-92.

27. Glassman AH, Helzer JE, Covey LS, Cottler LB, Stetner F, Tipp JE, et al. Smoking, smoking cessation, and major depression. JAMA 1990;264:1546-49.

Chapter 6

Lower-leg symptoms in peripheral arterial disease are associated with anxiety, depression, and anhedonia

6

126 Chapter 6 – Anxiety, depression, anhedonia, PAD symptoms

Smolderen KG, Hoeks SE, Pedersen SS, Van Domburg RT, De Liefde I, Poldermans D. Lower-leg symptoms in peripheral arterial disease are associated with anxiety, depression, and anhedonia. Vasc Med. In Press.

ABSTRACT

Background: Patients with peripheral arterial disease (PAD) report diverse clinical manifestations that are not always consistent with classic intermittent claudication. We examined the degree to which atypical exertional leg symptoms, intermittent claudication, and exertional leg symptoms that begin at rest were associated with mood states such as anxiety, depressive symptoms, and anhedonia (i.e., lack of positive affect).

Methods: A cohort of consecutive PAD patients (n=628) from the Erasmus Medical Center, Rot-terdam, The Netherlands, completed the Hospital Anxiety and Depression Scale and the San Diego Claudication questionnaire. The ankle-brachial index and clinical factors were assessed in all patients at baseline.

Results: Anxiety was present in 29%, depressive symptoms in 30%, and anhedonia in 28% of pa-tients. Pain at rest was independently associated with anxiety, depressive symptoms, and anhedonia (OR’s between 2.5-4.0, P≤.001), while there was no relationship between intermittent claudication and mood states. Patients with atypical leg symptoms had a 2-fold risk of anxiety (OR=1.9, 95%CI 1.1-3.5, P<.05). Adjusting for sex, age, ankle-brachial index, cardiovascular history, time since ankle-brachial index screening, clinical factors, and medication use, both pain at rest (OR=3.4, 95%CI 1.6-7.0, P=.001) and atypical leg symptoms (OR=2.3, 95%CI 1.1-4.9, P<.05) were associated with comorbid mood problems.

Conclusions: PAD patients with atypical leg symptoms or pain at rest reported more impaired mood than patients without those symptoms. These patients should be monitored closely in clinical practice, as previous research in cardiovascular patients has shown that mood disorders and sub-threshold symptoms predict poor prognosis.


INTRODUCTION

The classic symptomatic presentation of peripheral arterial disease (PAD) is intermittent claudication, characterized by muscle discomfort in the legs, reproducibly evoked by exercise and relieved at rest within 10 minutes.1 Besides typical claudication, many people with PAD are asymptomatic or report atypical leg symptoms.2 Functional impairment not only occurs in patients with claudication, but also in PAD patients presenting with different types of leg pain.3 The ankle-brachial index (ABI) is known to be highly sensitive and specific in detecting peripheral arterial disease (PAD), and has therefore be-come a standard assessment tool in evaluating patients with suspected PAD.1 Besides an abnormal ABI (≤0.90) confirming the existence of a hemodynamically significant occlusive disease between the heart and the ankle, the index also provides strong prognostic information.4 Recent findings, however, show that the ABI and other standard PAD-related outcome measures correlate poorly with the spec-trum of lower extremity symptoms associated with PAD.2, 5

Unlike in coronary artery disease (CAD), the relationship between psychological variables and atypi-cal symptom reporting has not been studied in PAD. Atypical symptoms in CAD are known to be related to elevated symptoms of anxiety6 and depression.7 Hence, in the current study, we examined the spectrum of leg symptoms in PAD in relation to mood states, such as anxiety, depressive symp-toms, and anhedonia (i.e., lack of positive affect). According to the work of McDermott8 and Criqui,9 we discerned four leg symptom categories: asymptomatic PAD, intermittent claudication, atypical exertional leg symptoms, and pain at rest, with the latter two categories indicating atypical presenta-tions of symptomatic PAD. Based on the literature on symptom reporting and mood states in CAD, we hypothesized that leg symptoms that are atypical from the classic description of intermittent claudica-tion were more strongly associated with symptoms of anxiety, depression, and lack of positive affect (i.e., anhedonia).


METHODS

This study was based on a cohort of consecutive PAD patients (n=1962) subject to cardiovascular screening at the anesthesia outpatient clinic of the Erasmus Medical Center, Rotterdam, The Nether-lands between July 1993 and December 2005. Diagnosis for PAD was based on a resting ABI ≤0.90 or a decrease in ABI of 15% after treadmill exercise.1 Patients were contacted again after a median follow-up of 4.3 years (interquartile range, 2.3-7.7 years), and were asked to complete standardized questionnaires about their current mood and leg symptoms. Of all patients, 111 patients were lost to follow-up due to somatic disease that prevented them from filling out the questionnaires (e.g., new onset breast cancer, stroke, Lyme disease) or due to other reasons (e.g., moving away); death was registered in 701 patients. Of the remaining patients, 628 returned the questionnaires.

Information about patients’ medical history was obtained from the hospital records. Diabetes mel-litus was recorded if patients received treatment for diabetes and/or had a fasting glucose level ≥7.0 mmol\L. Hypertension was recorded if patients presented with a blood pressure of ≥140/90 mm Hg or were treated for hypertension. Hypercholesterolemia was recorded if patients presented with a plasma cholesterol level of 5.5 mmol/L or more (≥212 mg/dL), or if they were prescribed lipid-lowering drugs. Patients were considered to have renal dysfunction if they presented with a serum creatinine level of 2.0 mg/dL or more (≥177 μmol/L) or required dialysis. Cigarette smoking included only current smoking. Patients were assessed for cardiac medication use, and a baseline ABI at rest and after exercise were determined.

Measurement of ABI and walking distance

Details of the ABI measurement have been described in a previous study.4 Of the ABI values obtained in each leg, the lowest rest value was used in all analyses. Pain-free walking distance (PFWD) and maximum walking distance (MWD) were also determined by means of the treadmill test in all pa-tients.


Leg symptoms

Patients’ leg symptoms at follow-up were classified using a self-administered version of the San Diego Claudication questionnaire based on previous work by Criqui et al.9 and McDermott et al.8 The following leg symptom categories were derived: (a) no exertional leg pain, which was defined as the absence of exertional leg pain, numbness, or discomfort; (b) atypical exertional leg pain, character-ized as either exertional calf symptoms that do not begin at rest but are otherwise not consistent with Rose intermittent claudication, or exertional leg symptoms that do not begin at rest and do not include the calves; (c) pain at rest: exertional leg symptoms that also begin at rest; and (d) Rose intermittent claudication: exertional calf symptoms that do not begin at rest, worsen when walking uphill or hurry-ing, and resolve within 10 minutes of rest. This definition of Rose claudication has a 91% sensitivity and 67.5% specificity for clinician-diagnosed claudication.10

Mood states

Symptoms of anxiety and depression were evaluated with the 14-item Hospital Anxiety and Depres-sion Scale (HADS).11 This self-report questionnaire contains two 7-item subscales designed to mea-sure symptoms of anxiety and depression. The scale was developed for use in patients suffering from bodily disease and therefore, symptoms of somatic reference such as pain and fatigue were exclud-ed.11 Cut-off scores of ≥8 are recommended to indicate clinically relevant symptoms of anxiety and depression; with this threshold, sensitivities and specificities for both subscales are approximately 0.80.12 Previous findings in cardiac patients have shown that the HADS consists of three distinct fac-tors;13 apart from anxiety and depression, (lack of) positive affect can be measured using four items of the HADS (i.e., “being cheerful”, “looking forward with enjoyment to things”, “still being able to enjoy things” and “seeing funny side of things”). A score of 7 or below (range 0-12) indicates anhedonia.14 Anhedonia (i.e., lack of positive affect) and anxiety or depressive symptoms are not merely opposites, as growing evidence shows that positive affect and negative emotions tend to function relatively inde-pendently.15, 16 The anxiety, depression, and positive affect subscales have good validity and internal consistency (Cronbach’s α 0.80-0.93).14, 17 The Cronbach’s alpha indices of the HADS subscales for the current study were 0.85 for anxiety, 0.84 for depression, and 0.77 for anhedonia.



Baseline characteristics of the sample were examined for the total sample and stratified by leg symp-tom categories. Chi-square tests were used for categorical variables and Student t-tests for continu-ous variables. Mean scores on the mood state dimensions were compared across leg symptom cat-egories using a multivariable analysis of variance (MANOVA). Mood states were dichotomized using the prescribed cut-off scores (≥8 for anxiety and depressive symptoms, and ≤7 for positive affect).11,

14 The prevalence (%) of impaired mood states was examined for the total group and per leg symptom category using Chi-square tests. Bonferroni correction was used in post hoc analyses to control for Type I errors. Three pairwise comparisons between no exertional leg pain and leg pain categories were performed using no exertional leg symptoms as the reference category. Assuming an α of .05 and three pairwise comparisons, a P value of .02 was considered statistically significant in post hoc analyses. Leg symptom categories (no exertional leg pain was used as reference category) were used as independent variables in multiple logistic regression analyses and impaired mood states as dependent variables. Logistic regression analyses were repeated adjusting for sex, age, ABI, cardio-vascular history, time since ABI screening, clinical factors, and medication. Finally, logistic regression analyses (both unadjusted and adjusted for sex, age, ABI, cardiovascular history, time since ABI screening, clinical factors, and medication) were performed using the endpoint of co-occurring anxi-ety, depressive symptoms, and anhedonia as dependent variable and leg symptoms as independent variables. Unless otherwise stated, a P value <.05 (two-tailed) was considered statistically significant. All analyses were performed using SPSS for Windows, version 16.0 (SPSS Inc., Chicago, Illinois).


RESULTS

In this study, 628 patients completed the questionnaires. Non-responders did not differ systematically from responders on baseline characteristics, except for a larger proportion of non-responders being female (38.4% vs. 31.9%, P<.05), having chronic obstructive pulmonary disease (14.8% vs. 9.4%, P<.01), and having longer mean maximum walking distances (550m vs. 540m, P<.01) compared with responders.


Tabl

e 1 –

Base

line c

hara

cter

istics

for t

he to

tal s

ampl

e (n=

628)

and

stra

tified

by l

eg sy

mpt

om ca

tego

ries.*

Char

acte

ristic

To

tal s

ampl

e(n

=628

) No

exer

tiona

l leg

sym

ptom

s (n

=162

)

Inte

rmitt

ent

claud

icatio

n (n

=138

)

Atyp

ical

exer

tiona

l leg

sym

ptom

s(n

=163

)

Pain

at re

st

(n=1

65)

P va

lue

Demo

grap

hics

Age,

mean

(SD)

62

.2 (1

0.8)

63.2

(11.5

) 62

.4 (9

.8)

62.2

(10.8

) 61

.1 (1

1.0)

.37

Male

sex

420 (

66.9)

11

6 (71

.6)

104 (

75.4)

10

9 (66

.9)

91 (5

5.2)

.001

Card

iovas

cular

histo

ry

An

gina p

ector

is 99

(15.8

) 21

(13.0

) 21

(15.2

) 26

(16.0

) 31

(18.8

) .58

My

ocar

dial in

farcti

on

119 (

18.9)

28

(17.3

) 33

(23.9

) 28

(17.2

) 30

(18.2

) .42

Co

nges

tive h

eart

failur

e 26

(4.1)

5 (

3.1)

6 (4.3

) 4 (

2.5)

11 (6

.7)

.24

Coro

nary

arter

y byp

ass s

urge

ry 71

(11.3

) 23

(14.2

) 20

(14.5

) 10

(6.1)

18

(10.9

) .06

Pe

rcutan

eous

coro

nary

inter

venti

on

61 (9

.7)

15 (9

.3)

18 (1

3.0)

14 (8

.6)

14 (8

.5)

.50

Stro

ke or

tran

sient

ische

mic

attac

k 47

(7.5)

12

(7.4)

13

(9.4)

12

(7.4)

10

(6.1)

.75

Clini

cal fa

ctors

Diab

etes m

ellitu

s 10

2 (16

.2)

19 (1

1.4)

33 (2

3.9)

22 (1

3.5)

28 (1

7.0)

<.05

Hype

rchole

stero

lemia

205 (

32.6)

57

(35.2

) 51

(37.0

) 45

(27.6

) 52

(31.5

) .28

Hy

perte

nsion

24

5 (39

.0)

59 (3

6.4)

62 (4

4.9)

68 (4

1.7)

56 (3

3.9)

.19

Ciga

rette

smok

ing

200 (

31.8)

49

(30.2

) 50

(36.2

) 51

(31.3

) 50

(30.3

) .67

Re

nal fa

ilure

45

(7.2)

3 (

1.9)

13 (9

.4)

16 (9

.8)

13 (7

.9)

<.05

COPD

62

(9.9)

12

(7.4)

18

(13.0

) 14

(8.6)

18

(10.9

) .36

Re

sting

ABI

, mea

n (SD

) 0.7

2 (0

.22)

0.73 (

0.22)

0.7

0 (0.1

9)

0.70 (

0.21)

0.7

7 (0.2

3)

<.05

Post-

exer

cise A

BI, m

ean (

SD)

0.49 (

0.26)

0.5

1 (0.2

7)

0.43 (

0.23)

0.4

7 (0.2

5)

0.56 (

0.27)

<.0

001

PFW

D, m

ean (

SD)

104.2

(57.5

) 10

9.0 (6

6.3)

106.5

(49.0

) 11

0.2 (6

2.0)

92.8

(51.6

) .06

MW

D me

an (S

D)

235.7

(93.2

) 24

6.9 (8

9.7)

236.9

(89.0

) 24

1.7 (9

2.0)

217.5

(100

.0)

<.05

Medic

ation

As

pirin

220 (

35.0)

59

(36.4

) 57

(41.3

) 45

(27.6

) 59

(35.8

) .08

AC

E-inh

ibitor

s 15

7 (25

.0)

46 (2

8.4)

38 (2

7.5)

33 (2

0.2)

40 (2

4.2)

.30

β-Bl

ocke

rs 22

1 (35

.2)

65 (4

0.1)

49 (3

5.5)

41 (2

5.2)

66 (4

0.0)

<.05

Calci

um ch

anne

l bloc

kers

118 (

18.8)

29

(17.9

) 30

(21.7

) 31

(19.0

) 28

(17.0

) .75

Di

ureti

cs

110 (

17.5)

28

(17.3

) 25

(18.1

) 25

(15.3

) 32

(19.4

) .82

Ni

trates

61

(9.7)

11

(6.8)

16

(11.6

) 15

(9.2)

19

(11.5

) .44


*Dat

a ar

e pr

esen

ted

as n

umbe

r (pe

rcen

tage

) of e

ach

grou

p, u

nless

oth

erwi

se in

dicat

ed. A

bbre

viatio

ns: S

D, st

anda

rd d

eviat

ion; C

OPD,

chro

nic o

bstru

ctive

pul-

mon

ary d

iseas

e; A

BI, a

nkle-

brac

hial in

dex;

PFW

D, p

ain-fr

ee w

alking

dist

ance

in m

eter

s; M

WD,

max

imum

walk

ing d

istan

ce in

met

ers;

ACE-

inhibi

tors

, ang

ioten

sin-

conv

ertin

g en

zym

e inh

ibito

rs.

Char

acte

ristic

To

tal s

ampl

e(n

=628

) No

exer

tiona

l leg

sym

ptom

s (n

=162

)

Inte

rmitt

ent

claud

icatio

n (n

=138

)

Atyp

ical

exer

tiona

l leg

sym

ptom

s(n

=163

)

Pain

at re

st

(n=1

65)

P va

lue

Demo

grap

hics

Age,

mean

(SD)

62

.2 (1

0.8)

63.2

(11.5

) 62

.4 (9

.8)

62.2

(10.8

) 61

.1 (1

1.0)

.37

Male

sex

420 (

66.9)

11

6 (71

.6)

104 (

75.4)

10

9 (66

.9)

91 (5

5.2)

.001

Card

iovas

cular

histo

ry

An

gina p

ector

is 99

(15.8

) 21

(13.0

) 21

(15.2

) 26

(16.0

) 31

(18.8

) .58

My

ocar

dial in

farcti

on

119 (

18.9)

28

(17.3

) 33

(23.9

) 28

(17.2

) 30

(18.2

) .42

Co

nges

tive h

eart

failur

e 26

(4.1)

5 (

3.1)

6 (4.3

) 4 (

2.5)

11 (6

.7)

.24

Coro

nary

arter

y byp

ass s

urge

ry 71

(11.3

) 23

(14.2

) 20

(14.5

) 10

(6.1)

18

(10.9

) .06

Pe

rcutan

eous

coro

nary

inter

venti

on

61 (9

.7)

15 (9

.3)

18 (1

3.0)

14 (8

.6)

14 (8

.5)

.50

Stro

ke or

tran

sient

ische

mic

attac

k 47

(7.5)

12

(7.4)

13

(9.4)

12

(7.4)

10

(6.1)

.75

Clini

cal fa

ctors

Diab

etes m

ellitu

s 10

2 (16

.2)

19 (1

1.4)

33 (2

3.9)

22 (1

3.5)

28 (1

7.0)

<.05

Hype

rchole

stero

lemia

205 (

32.6)

57

(35.2

) 51

(37.0

) 45

(27.6

) 52

(31.5

) .28

Hy

perte

nsion

24

5 (39

.0)

59 (3

6.4)

62 (4

4.9)

68 (4

1.7)

56 (3

3.9)

.19

Ciga

rette

smok

ing

200 (

31.8)

49

(30.2

) 50

(36.2

) 51

(31.3

) 50

(30.3

) .67

Re

nal fa

ilure

45

(7.2)

3 (

1.9)

13 (9

.4)

16 (9

.8)

13 (7

.9)

<.05

COPD

62

(9.9)

12

(7.4)

18

(13.0

) 14

(8.6)

18

(10.9

) .36

Re

sting

ABI

, mea

n (SD

) 0.7

2 (0

.22)

0.73 (

0.22)

0.7

0 (0.1

9)

0.70 (

0.21)

0.7

7 (0.2

3)

<.05

Post-

exer

cise A

BI, m

ean (

SD)

0.49 (

0.26)

0.5

1 (0.2

7)

0.43 (

0.23)

0.4

7 (0.2

5)

0.56 (

0.27)

<.0

001

PFW

D, m

ean (

SD)

104.2

(57.5

) 10

9.0 (6

6.3)

106.5

(49.0

) 11

0.2 (6

2.0)

92.8

(51.6

) .06

MW

D me

an (S

D)

235.7

(93.2

) 24

6.9 (8

9.7)

236.9

(89.0

) 24

1.7 (9

2.0)

217.5

(100

.0)

<.05

Medic

ation

As

pirin

220 (

35.0)

59

(36.4

) 57

(41.3

) 45

(27.6

) 59

(35.8

) .08

AC

E-inh

ibitor

s 15

7 (25

.0)

46 (2

8.4)

38 (2

7.5)

33 (2

0.2)

40 (2

4.2)

.30

β-Bl

ocke

rs 22

1 (35

.2)

65 (4

0.1)

49 (3

5.5)

41 (2

5.2)

66 (4

0.0)

<.05

Calci

um ch

anne

l bloc

kers

118 (

18.8)

29

(17.9

) 30

(21.7

) 31

(19.0

) 28

(17.0

) .75

Di

ureti

cs

110 (

17.5)

28

(17.3

) 25

(18.1

) 25

(15.3

) 32

(19.4

) .82

Ni

trates

61

(9.7)

11

(6.8)

16

(11.6

) 15

(9.2)

19

(11.5

) .44


The mean age of the total sample was 62 years and 67% was male. Baseline characteristics are presented in Table 1. Mean scores of mood states were compared as a function of leg symptoms, using no exertional leg symptoms as reference group (Table 2). Patient levels of anxiety, depres-sion and positive affect significantly differed according to their reported leg functioning (all P values <.0001). Patients who reported atypical exertional leg symptoms (mean=5.5, P<.05) or pain at rest (mean=7.3, P<.0001) experienced more anxiety as compared with patients who did not have leg symptoms (mean=4.1). Patients with intermittent claudication (mean=5.9, P<.05) and pain at rest (mean=7.5, P<.0001) experienced more depressive symptoms as compared with patients without exertional leg symptoms (mean=4.3). Levels of positive affect were lower in patients reporting pain at rest (mean=8.0) compared with asymptomatic patients (mean=9.7, P<.0001).


Tabl

e 2 –

Mean

(SD)

anxie

ty, d

epre

ssive

sym

ptom

s, an

d po

sitive

affe

ct sc

ores

, stra

tified

by l

eg sy

mpt

om ca

tego

ries (

n=62

8).

*Ref

eren

ce g

roup

for t

he o

ther

thre

e leg

pain

cate

gorie

s.†V

alues

are

stat

istica

lly si

gnific

antly

diffe

rent

bet

ween

no

exer

tiona

l leg

pain

and

leg sy

mpt

om ca

tego

ry. T

hree

pair

wise

com

paris

ons b

etwe

en n

o ex

ertio

nal le

g pa

in an

d leg

pain

cate

gorie

s wer

e mad

e usin

g ana

lysis

of va

rianc

e (Bo

nfer

roni

corre

ction

). A P

value

of .0

2 was

use

d as t

he le

vel o

f sta

tistic

al sig

nifica

nce f

or th

e pair

wise

co

mpa

rison

s. Ab

brev

iation

s: SD

, sta

ndar

d de

viatio

n.

Tota

lsam

ple

No ex

ertio

nal le

g sy

mpt

oms*

Inte

rmitt

ent

claud

icatio

n At

ypica

l exe

rtion

al leg

sym

ptom

s Pa

in at

rest

Anxie

ty(ra

nge 0

-21)

5.5

(4.3)

4.1

(3.7)

4.8

(3.8)

5.5

(4.4)

†7.3

(4.4)

†

Depr

essiv

esy

mpt

oms

(rang

e 0-2

1)

5.8 (4

.4)

4.3 (4

.1)

5.9 (4

.4)†

5.3 (4

.2)

7.5 (4

.5)†

Posit

ive af

fect

(ra

nge 0

-12)

8.9

(3.0)

9.7

(2.8)

8.7

(3.0)

9.2

(2.8)

8.0

(3.2)

†


In the total sample, the prevalence of anxiety symptoms was 28.8%, 30.4% for depressive symptoms, and 27.5% for anhedonia. Anxiety and depressive symptoms co-occurred in 17.7%, and anxiety, depressive symptoms, and anhedonia in 14.3% of patients. Figure 1 shows prevalence rates of im-paired mood states stratified by leg symptom category. Anxiety (range 16.8% to 46.8%) was less prevalent in asymptomatic patients, with prevalence rates gradually increasing along patients with intermittent claudication, atypical exertional leg symptoms, and patients reporting pain at rest. Pa-tients with no exertional leg symptoms had the lowest prevalence of depressive symptoms (17.1%), with a graded increase in prevalence rates (range 17.1% to 45.5%) in patients with atypical exertional leg symptoms, patients with claudication, and patients with pain at rest. The prevalence of anhedonia ranged from 17.8% to 35.2%, being lowest in patients with no exertional symptoms and increasing in a graded fashion in patients with atypical exertional leg pain, patients with intermittent claudication, and patients with pain at rest.

Figure 1 – Prevalence (%) of impaired mood (anxiety, depressive symptoms, and anhedonia) stratified by leg symptom categories.

Figure 2 - Odds ratios (OR) and 95% confidence intervals (CI) for the

association between leg symptom categories and (a) comorbid anxiety and

depressive symptoms and (b) comorbid anxiety, depressive symptoms, and

anhedonia. No exertional leg symptoms were used as reference category.

Anxiety Depression Anhedonia

0

10

20

30

40

50

No exertional leg symptoms

Atypical exertional leg symptoms

Intermittent claudication

Pain at rest

P<.001 P<.001 P<.01

Imp

air

ed

mo

od

(%

)

P<.001 P<.001 P<.01


Univariable logistic regression analyses (no exertional leg symptoms reference category) using the leg symptoms as independent variables and impaired mood variables as dependent variables revealed that both atypical exertional leg symptoms (OR=2.1, 95%CI 1.2-3.7, P<.01) and pain at rest (OR=4.4, 95%CI 2.6-7.5, P<.0001) were significantly associated with anxiety. Having intermittent claudication was not significantly associated with anxiety (OR=1.3, 95%CI 0.7-2.3, P=.46). All leg symptom cat-egories were significantly associated with depressive symptoms; intermittent claudication (OR=2.2, 95%CI 1.2-3.8, P<.01), atypical exertional leg symptoms (OR=1.8, 95%CI 1.1-3.2, P<.05) and pain at rest (OR=4.0, 95%CI 2.4-6.9, P<.0001). All types of leg symptoms were also significantly associ-ated with anhedonia; intermittent claudication (OR=1.9, 95%CI 1.1-3.3, P<.05), atypical exertional leg symptoms (OR=1.8, 95%CI 1.0-3.0, P<.05) and pain at rest (OR=4.4, 95%CI 2.6-7.5, P<.0001). Adjusting for sex, age, ABI, cardiovascular history, time since ABI screening, clinical factors, and medication, atypical exertional leg symptoms and pain at rest remained significantly associated with anxiety (Table 3). In the adjusted analyses with depressive symptoms and anhedonia as dependent variables, only pain at rest was independently associated with impaired mood (Table 3).


Table 3 – Leg symptom

categories and symptom

s of anxiety, depressive symptom

s, and anhedonia (n=628; logistic regression analy-ses).*

*Adjusted for sex, age, ankle-brachial index [ABI], cardiovascular history, time since ABI screening, clinical factors, and m

edication. No exertional leg symptom

s was used as reference category.

AnxietyDepressivesym

ptoms

Anhedonia

Leg symptom

s OR

[95% CI]

P value OR

[95% CI]

P value OR

[95% CI]

P value

No exertional leg symptoms

1.01.0

1.0

Intermittent claudication 1.1

[0.6-2.0].86

1.7[0.9-3.1]

.071.7

[0.9-3.0].08


1.9[1.1-3.5]

.031.5

[0.9-2.8].15

1.7[0.9-2.9]

.08

Pain at rest 4.0

[2.3-7.2]<.0001

3.8[2.1-6.7]

<.00012.5

[1.4-4.3].001


Atypical exertional leg symptoms (OR=2.1, 95%CI 1.1-4.1, P<.05) and pain at rest (OR=4.1, 95%CI 2.2-7.7, P<.0001) were significantly related to the co-occurrence of anxiety and depressive symptoms. Both atypical exertional leg symptoms (OR=2.4, 95%CI 1.2-5.0, P<.05) and pain at rest (OR=3.4, 95%CI 1.7-6.9, P=.001) were also significantly associated with comorbid anxiety, depressive symp-toms, and anhedonia. The results of the adjusted analyses are presented in Figure 2. Pain at rest was significantly associated with comorbid anxiety and depression (OR=4.0, 95%CI 2.1-7.8, P<.0001) and comorbid symptoms of anxiety, depression, and anhedonia (OR=3.4, 95%CI 1.6-7.0, P=.001) and atypical exertional leg symptoms was associated with comorbid anxiety, depression, anhedonia (OR=2.3, 95%CI 1.1-4.9, P<.05).


Figure 2 – Odds ratios (OR) and 95% confidence intervals (CI) for the association between leg symptom categories and (a) comorbid anxiety and depressive symptoms and (b) comorbid anxiety, depressive symptoms, and anhedonia. No exertional leg symptoms were used as refer-ence category.

0.1 1 10

Pain at Rest

Atypical Exertional Leg

Intermittent Claudication

Comorbid anxiety and depression



Pain at rest

OR (95% CI)

0.1 1 10

Atypical Exertional Leg

Pain at Rest

Intermittent Claudication

Comorbid anxiety, depression,anhedonia



Pain at rest

OR (95% CI)


DISCUSSION

To our knowledge, this is the first study in patients diagnosed with PAD to examine the association between self-reported leg symptoms and a broad range of mood states (i.e., anxiety, depressive symptoms, and anhedonia) and their co-occurrence. Rates of anxiety, depressive symptoms, and anhedonia were high and differed meaningfully as a function of leg symptom reporting, with patients having pain at rest typically experiencing the highest burden. In patients with atypical exertional leg symptoms, levels of anxiety were also higher as compared to asymptomatic patients. Having pain at rest was independently associated with all mood states and comorbid mood problems. Atypical exertional leg pain was independently associated with anxiety and comorbid mood states.

The prevalence of impaired mood was high in the current study, with prevalence rates between 28%-30%. The high depression rates found in our study replicates previous work of other groups.18-20 However, the current study is the first to document other impaired mood states in PAD (i.e., anxi-ety and anhedonia), which seem to be equal in magnitude to the previously documented problem of depressed mood in PAD.18-20 Recently, anxiety has received more attention in cardiac patients;21 both depression and anxiety are associated with adverse health outcomes in cardiac patients,21 and when both mood states are present in an individual patient, the risk of adverse outcomes may be enhanced.22, 23 Anhedonia or lack of positive affect has received less attention in the cardiovascular literature; positive affect reflects the extent to which a person feels enthusiastic, active, and alert, with lack of positive affect being characterized by sadness and lethargy. Positive affect and negative affect (e.g., depression and anxiety) comprise two distinct dimensions and not just opposites on a continuum.24 Preliminary evidence shows that anhedonia is also associated with poor prognosis in cardiac patients.14

Impaired mood differed as a function of self-reported leg symptoms, with atypical exertional leg pain and pain at rest being more closely related to impaired mood. In particular, there was a strong re-lationship between anxiety and atypical leg symptoms, showing a dose-response relationship, with the risk of anxiety symptoms increasing in a graded fashion from intermittent claudication to pain at rest. Managing symptoms other than classic intermittent claudication in patients with PAD in clinical practice is often complex, as atypical symptom reporting is not always related to actual vascular pathology and clinical indices.5 PAD patients often present with leg symptoms that are not typical for intermittent claudication. Comorbid disease (e.g., neuropathy and spinal stenosis) and activity levels


are partly responsible for the variation in reported leg symptoms in PAD, with patients reporting pain at rest having more comorbid conditions and asymptomatic patients being less active.2, 25 Having pain at rest should be distinguished from PAD-related rest pain typical for critical leg ischemia. In critical leg ischemia, pain increases when the affected leg is elevated.8 Patients categorized as having pain at rest in our study had pain in their legs while walking and reported that these symptoms even began at rest. The spectrum of PAD associated leg symptoms are all known to be associated with poor func-tioning, with patients reporting pain at rest being the most affected.3 Physicians involved in the clinical management of PAD patients should be aware of the fact that pain and symptom reporting are closely related with psychological factors such as impaired mood, as shown in the present study.

In CAD, other factors than comorbid conditions have been studied in relation to atypical symptom reporting, with impaired mood known to increase symptom reporting.6, 7 A potential explanation in-cludes the heightened sensory activity reflecting central processing errors associated with active anxiety or depression symptoms.7 Other explanations include the uncontrollability of pain, persis-tence of pain and associated disability leading to anxiety and depressed mood,26 or the possibility that general negative affectivity as an underlying personality disposition may explain the association between symptom reporting and impaired mood.27 The disposition of negative affectivity is known to be associated with more self-reported health complaints. Patients scoring high on this trait may be more likely to report somatic symptoms, experience impaired mood, and associated burden. Finally, the bidirectional relationship between the immune system and psychological factors may provide another alternative explanation of our results. The constellation of negative mood may be triggered by peripheral inflammation processes in atherosclerotic disease,28 and chronic negative mood states probably will further stimulate a cascade of inflammatory processes through mechanisms involved in sympathetic nervous system activation.29, 30

This study has several limitations; they may not be generalizable to patients who recently received a PAD diagnosis and to PAD patients seen in general practice, as our sample consisted of previously diagnosed patients with PAD seen in an academic hospital. However, time since ABI screening had no influence on mood states in the adjusted analyses. We also acknowledge the fact that our results need to be replicated adjusting for covariates that may alternatively explain our results, such as os-teoarthritis, spinal stenosis, and diabetes neuropathy. In addition, it would be interesting to compare our findings with a non-PAD control group. Unfortunately, we included only PAD patients in the current study, and as such, we cannot contrast our findings with associations between symptom reporting


and mood impairment in a non-PAD control group. Based on previous literature on symptom report-ing and negative affectivity,27 we might expect that the association between symptom reporting and impaired mood may also be found in the general population. Nevertheless, this would not trivialize our results because the concurrent occurrence of somatic disease and mood disorders may impact in a synergistic way on PAD patients’ functional status31 and possibly their prognosis,19 necessitat-ing that mood disorders, such as anxiety and depression, be dealt with in clinical practice in order to enhance secondary prevention. Finally, since this study was cross-sectional, we are not able to determine cause and effect. Therefore, future research needs to replicate our findings, addressing these shortcomings.

In conclusion, impaired mood was closely related to the way PAD patients present their leg symptoms. Our results suggest that patients with classical intermittent claudication, atypical symptoms, or pain at rest need to be followed closely in clinical practice and screened for impaired mood. Special attention should be given to patients reporting atypical leg symptoms, as the way these patient present their symptoms may be closely related to their mood. Since prior findings have pointed to the prognostic importance of psychological factors19, 20, 32 and because mood disorders deserve to be treated in their own right, more attention should be paid to the mood state of PAD patients in clinical practice. A short and easy questionnaire to administer, such as the HADS,11 may assist clinicians in this screening process. This information can be used to complement information obtained from objective measures, such as the ABI, as these measures do not correlate strongly with the clinical presentation of PAD.5 Further research is warranted to replicate our findings while adjusting for other than cardiovascular comorbid conditions, such as arthritis and neuropathy, and to study the link between symptom report-ing in PAD and impaired mood in association with short- and long-term prognosis.


REFERENCES


2. McDermott MM, Greenland P, Liu K, Guralnik JM, Criqui MH, Dolan NC, et al. Leg symptoms in peripheral arterial disease. Associated clinical characteristics and functional impairment. JAMA 2001;286:1599-606.

3. McDermott MM, Mehta S, Liu K, Guralnik JM, Martin GJ, Criqui MH, et al. Leg symptoms, the ankle-bra-chial index, and walking ability in patients with peripheral arterial disease. J Gen Intern Med 1999;14:173-181.


5. Gardner AW, Montgomery PS, Afaq A. Exercise performance in patients with peripheral arterial disease who have different types of exertional leg pain. J Vasc Surg 2007;46:79-86.

6. Grace SL, Abbey SE, Irvine J, Shnek ZM, Stewart DE. Prospective examination of anxiety persistence and its relationship to cardiac symptoms and recurrent cardiac events. Psychother Psychosom 2004;73:344-52.

7. Sheps DS, Creed F, Clouse RE. Chest pain in patients with cardiac and noncardiac disease. Psychosom Med 2004;66:861-7.

8. McDermott MM, Mehta S, Greenland P. Exertional leg symptoms other than intermittent claudication are common in peripheral arterial disease. Arch Intern Med 1999;159:387-92.

9. Criqui MH, Denenberg JO, Bird CE, Fronek A, Klauber MR, Langer RD. The correlation between symp-toms and non-invasive test results in patients referred for peripheral arterial disease testing. Vasc Med 1996;1:65-71.

10. Leng GC, Fowkes FG. The Edinburgh Claudication Questionnaire: an improved version of the WHO/Rose Questionnaire for use in epidemiological surveys. J Clin Epidemiol 1992;45:1101-9.

11. Zigmond A, Snaith R. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361-70.12. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression Scale.

An updated literature review. J Psychosom Res 2002;52:69-77.13. Denollet J. Emotional distress and fatigue in coronary heart disease: the Global Mood Scale (GMS). Psy-

chol Med 1993;23:111-21.14. Denollet J, Pedersen SS, Daemen J, de Jaegere P, Serruys PW, van Domburg RT. Reduced positive affect

(anhedonia) predicts major clinical events following implantation of coronary-artery stents. J Intern Med 2008;263:203-11.


15. Larsen JT, McGraw AP, Cacioppo JT. Can people feel happy and sad at the same time? J Pers Soc Psy-chol 2001;81:684-96.

16. Huppert FA, Whittington JE. Evidence for the independence of positive and negative well-being: implica-tions for quality of life assessment. Br J Health Psychol 2003;8:107-22.

17. Herrmann C. International experiences with the Hospital Anxiety and Depression Scale--a review of valida-tion data and clinical results. J Psychosom Res 1997;42:17-41.




21. Frasure-Smith N, Lesperance F. Depression and anxiety as predictors of 2-year cardiac events in patients with stable coronary artery disease. Arch Gen Psychiatry 2008;65:62-71.

22. Watkins LL, Blumenthal JA, Davidson JR, Babyak MA, McCants CB, Jr., Sketch MH, Jr. Phobic anxiety, depression, and risk of ventricular arrhythmias in patients with coronary heart disease. Psychosom Med 2006;68:651-6.

23. Pedersen SS, Denollet J, Spindler H, Ong AT, Serruys PW, Erdman RA, et al. Anxiety enhances the det-rimental effect of depressive symptoms on health status following percutaneous coronary intervention. J Psychosom Res 2006;61:783-9.

24. Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol 1988;54:1063-70.

25. Newman AB, Naydeck BL, Sutton-Tyrrell K, Polak JF, Kuller LH. The role of comorbidity in the assessment of intermittent claudication in older adults. J Clin Epidemiol 2001;54:294-300.

26. Chapman CR, Gavrin J. Suffering: the contributions of persistent pain. Lancet 1999;353:2233-7.27. Watson D, Pennebaker JW. Health complaints, stress, and distress: exploring the central role of negative

affectivity. Psychol Rev 1989;96:234-54.28. Gidron Y, Kupper N, Kwaijtaal M, Winter J, Denollet J. Vagus-brain communication in atherosclerosis-

related inflammation: a neuroimmunomodulation perspective of CAD. Atherosclerosis 2007;195:e1-9.29. Wright CE, Strike PC, Brydon L, Steptoe A. Acute inflammation and negative mood: mediation by cytokine

activation. Brain Behav Immun 2005;19:345-50.30. Vaccarino V, Johnson BD, Sheps DS, Reis SE, Kelsey SF, Bittner V, et al. Depression, inflammation, and

incident cardiovascular disease in women with suspected coronary ischemia: the National Heart, Lung, and Blood Institute-sponsored WISE study. J Am Coll Cardiol 2007;50:2044-50.



32. Wattanakit K, Williams JE, Schreiner PJ, Hirsch AT, Folsom AR. Association of anger proneness, de-pression and low social support with peripheral arterial disease: the Atherosclerosis Risk in Communities

Study. Vasc Med 2005;10:199-206.

Chapter 7

Peripheral endovascular revascularization: associations between depressive symptoms

and diminished health status benefi ts

7

150 Chapter 7 – Depressive symptoms, health status, PAD

Smolderen KG, Safley DM, House JA, Spertus JA, Marso SP. Peripheral endovascular revascularization: associations be-tween depressive symptoms and diminished health status benefits. Submitted.

ABSTRACT

Background: While depressive symptoms are known to compromise health status in cardiac dis-ease, this relationship has not been described in peripheral arterial disease (PAD).

Methods: Depressive symptoms (PHQ-9) and PAD-specific health status (Peripheral Artery Ques-tionnaire, PAQ) were assessed in 242 PAD patients undergoing peripheral endovascular revascular-ization (PER) at baseline and one year. Patients were classified by significant baseline (PHQ≥10) and follow-up depressive symptoms. Changes were categorized as no/improvement of depressive symptoms versus persistent/worsened depressive symptoms.

Results: At baseline, 20% of patients had significant depressive symptoms; they had lower PAQ scores compared to non-depressed patients, even after adjusting for relevant risk factors (β=-1.0 95%CI -1.4;-0.7, P<.0001). At one year, 17% of patients overall experienced persistent/worsened depressive symptoms. Although this group improved on most of the PAQ subscales, they improved to a lesser degree than those without depressive symptoms or improvement of their symptoms at one year (P values <.05). Adjusting for risk factors and baseline health status, changes in depres-sive symptoms were independently associated with changes in 1-year health status (β=-1.1, 95%CI -1.6;-0.8, P<0.0001).

Conclusions: Depressive symptoms are associated with worse health status at the time of PER and with less improvement in health status when compared with those having no symptoms or whose depressive symptoms improve. Efforts to stimulate depression screening and treatment in PAD pa-tients are needed to address their burden, and to identify possible alternative approaches to improve patients’ health status.


BACKGROUND

Peripheral arterial disease (PAD) is a common yet serious condition, affecting over 8 million people in the United States.1-2 It is associated with significant functional limitations.3 An important potential mediator of these limitations among patients with PAD is depression. Depression has been reported to occur in 22-26% of PAD patients, while the average prevalence of depression in later life has been estimated to be 13% in community-dwelling people.3-7 PAD patients with depressive symptoms have been described to have greater impairment in lower extremity functioning,5 more functional decline,6 and to be at greater risk for poor long-term outcomes.8, 9

Interventions in PAD are primarily aimed at relieving symptoms and disease burden. Over the last 20 years, peripheral endovascular revascularization (PER) has become the most common revascu-larization therapy for persons with symptomatic PAD.10 Although most patients improve in terms of health status following revascularization,11 there is substantial variation in the extent to which patients benefit from the procedure.12 Although depressive symptoms have been shown to compromise pa-tients’ health status in heart failure and coronary artery disease,13-15 this association has not been demonstrated in PAD. We therefore sought to explore the potential association between depressive symptoms and PAD-specific health status in patients that underwent PER; both cross-sectionally and at one year follow-up.


METHODS

This is a pre-specified sub-study of the Assessment of Lower Extremity rEvascularization outcomEs (ALEVE) Study, a single-center, prospective observational cohort study of consecutive patients un-dergoing PER. Details of the ALEVE study have been previously published.12 In brief, eligible patients underwent PER for symptomatic atherosclerotic infra-aortic PAD. Peripheral angiography and PER were performed using standard techniques,16 and data collection consisted of detailed chart abstrac-tions and standardized patient interviews at baseline. Chart abstractions were performed for baseline demographics and laboratory data. Transatlantic Inter-Society Consensus (TASC) definitions were used to classify iliac and femoropopliteal lesions as A, B, C, or D.17 Patient interviews were conducted by trained data collectors to assess patients’ depressive symptoms and PAD-specific health status. Serial follow-up phone interviews were performed throughout the 12 months after PER. Baseline and 12-month interview data were used for the current analysis. The local institutional review board ap-proved the ALEVE study protocol, and all patients provided written informed consent.

Assessment of depressive symptoms

Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ-9), an abbrevi-ated version of the Primary Care Evaluation of Mental Disorders questionnaire.18 The PHQ quantifies the frequency of each of 9 Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition19 criteria from “0” (not at all) to “3” (nearly every day). Patient responses are summed to create a score between 0 and 27 points. The PHQ-9 is recommended for screening purposes in medical settings in general20 and in cardiac disease in particular.21 The PHQ has a diagnostic sensitivity of 88% and a specificity of 88% for major depression when a cut-off of ≥10 is used.22, 23 This is the threshold we used in our analyses to discriminate between patients experiencing significant depressive symptoms and those who were not. Congruent with prior reports, we used a change of 5 points on the PHQ as a criterion for a clinically important difference in depressive symptom scores.24, 25


Peripheral Artery Questionnaire

The PAQ is a 20-item questionnaire that assesses PAD-specific health status and contains six sub-scales: Physical Limitation, Symptoms, Symptom Stability, Treatment Satisfaction, Quality of Life, and Social Functioning.26 Using a standardized scoring algorithm, a Summary score can be derived by combining the Physical Limitation, Symptom, Social Function, and Quality of Life subscales.26 A Sum-mary score ranges from 0-100, where higher values represent better health status. This instrument has been shown to be a valid, reliable (Cronbach’s α ranging from 0.84 to 0.94) and responsive mea-sure of PAD-specific health status in patients undergoing PER.12, 26 A clinically meaningful difference in health status scores was calculated using the difference between baseline and 1-year follow-up PAQ Summary score: patients with a change score of ≥8 points were considered as responders to treatment and patients with a change score <8 were classified as non-responder. This classification was consistent with previous work on the PAQ,12 in which a moderate clinically important difference corresponded with a medium effect size based on Cohen’s guidelines27 and according to the work of Sloan et al.28

Ankle-brachial index assessment

A handheld Doppler ultrasonic instrument (Omron, BP-203RPEII, Omron Healthcare Inc, Bannock-burn, IL) was used by trained technicians to obtain systolic blood pressure readings in the right and left brachial arteries and right and left posterior tibial arteries. The ankle-brachial index was calculated in each leg by dividing the ankle systolic pressure by the higher arm systolic pressure.

PER definitions

Procedural success was determined at time of discharge and was defined as angiographic success (<40% residual stenosis) of all attempted lesions without in-hospital major adverse cardiovascular event (including death, target lesion or target vessel revascularization, or amputation of the treated limb prior to discharge during the index hospitalization).



Baseline characteristics were described for the total cohort. Comparisons were made by baseline depressive symptoms (PHQ ≥10 vs. PHQ <10), using Student’s t-tests for continuous variables and Chi-square tests for categorical variables.

For the cross-sectional analyses, baseline PAD-specific health status (Physical Limitation, Symp-toms, Social Limitation, Treatment Satisfaction, Quality of Life subscales and Summary score) was compared between patients with and without significant baseline depressive symptoms using univari-ate analysis of variance. Unadjusted linear regression analysis with baseline PHQ score (continuous variable) was performed using PAQ Summary score as dependent variable. Multivariable regression analysis with the PAQ Summary score was repeated, adjusting for age, gender, diabetes, mellitus, coronary heart disease, chronic heart failure, and bilateral disease.

To explore the relationship between changes in depression scores with the PAD-specific health status benefits conferred by PER, patients were classified into two categories: patients that had no sig-nificant depressive symptoms or had a significant improvement in their depressive symptoms (PHQ score <10 at baseline and at one year follow-up or decrease by 5 points) versus patients with persis-tent or worsened depressive symptoms (PHQ score ≥10 both at baseline and one year or increase by 5 points). Baseline characteristics between these two groups were compared. Depressive symptoms at baseline and one year follow-up were compared by one year follow-up health status response (PAQ Summary change scores ≥8 indicate responders, scores <8 are non-responders) and depres-sion change status. Student’s t-tests were used for continuous variables and Chi-square tests for categorical variables. Paired t-tests were performed to evaluate the change in PAQ scores (baseline versus one year scores) for the five subscales and Summary score in both categories of depressive symptoms. Change PAQ scores were compared between the no /improved depressive symptoms group and the persistent/worsened depressive symptoms group with univariate analysis of variance. The relationship between the change in one year PAQ Summary scores (dependent) and change in one year depressive symptoms score (independent) were evaluated using a linear regression analy-sis. This model was further extended to adjust for the following covariates age, gender, diabetes, coronary heart disease, chronic heart failure, bilateral disease and baseline PAQ Summary score in a multivariable regression analysis. Ankle-brachial index measurement was not protocol-mandated, but values were available in a subset of patients (n=161, 67%). As a sensitivity analysis, linear regres-


sion analyses were replicated including ankle-brachial index as an extra covariate. All analyses were conducted with SPSS Version 16.0 (SPSS, Inc, Chicago, IL) using a P value of <0.05 as the criterion for statistical significance.


RESULTS

The indication for PER was intermittent claudication in the vast majority of patients (97%) and critical limb ischemia (rest pain, ulceration or gangrene) was present in only a few (3%). Procedural success was achieved in 98% (238/242) of attempted lesions. Complete PHQ and PAQ data were available for analysis in 242 individuals (81% of the entire ALEVE study population), 8 patients (2.7%) died within one year of PER, and could not provide one year follow-up and the remainder of eligible patients (n=50) did not complete depressive symptoms and health status follow-up interviews. There were no significant clinical or demographic differences between those with and without complete follow-up. Specifically, age, gender, race, comorbidities, arterial segment intervened upon, and, importantly, baseline depressive symptoms did not differ.

Baseline demographic data of those with follow-up are shown in Table 1 for the entire cohort and for patients with and without significant depressive symptoms. At baseline, 48 patients (20%) experi-enced clinically relevant depressive symptoms. There were significant differences between baseline depression groups regarding age, the ankle-brachial index, the number of total occlusions, lesions >50%, bilateral PAD, iliac lesions, TASC lesion types, lesions stented, number of stents, stent length, and stent diameter.


Tabl

e 1 –

Base

line c

hara

cter

istics

for t

he to

tal s

ampl

e and

stra

tified

by b

aseli

ne d

epre

ssive

sym

ptom

s.

Tota

l PH

Q de

pres

sive s

ympt

oms ≥

10

n=24

2 (10

0%)

Non=

194 (

80%

) Ye

sn=

48 (2

0%)

P va

lue

Demo

grap

hics

Age (

year

s), m

ean (

SD)

67.6

(11.2

) 68

.3 (1

1.5)

64.8

(9.5)

.05

Ca

ucas

ian, n

(%)

233(

96)

187(

96)

46(9

6).99

Male,

n (%

)14

7(61

)12

3(63

)24

(50)

.09Ma

rried

, n (%

)16

1(67

)12

5(64

)36

(75)

.21Me

dical

histor

yDi

abete

s mell

itus,

n (%

)93

(39)

69(3

6)24

(50)

.07H y

perte

nsion

, n (%

)16

5(68

)13

4(69

)31

(65)

.55Co

rona

r y ar

tery d

iseas

e, n (

%)

155(

64)

125(

64)

30(6

3).80

Con g

estiv

e hea

rt fai

lure,

n (%

)27

(11)

20(1

0)7(

15)

.40H y

perch

oleste

rolem

ia, n

(%)

161(

67)

133(

69)

28(5

8).18

Curre

nt tob

acco

use,

n (%

)*11

3(48

)93

(49)

20(4

3).40

Neph

ropa

thy, n

(%)†

6(2)

4(2)

2(4)

.34Hi

stor y

of pe

riphe

ral v

ascu

lar pr

oced

ures

Prior

PER

, n (%

)35

(14)

27(1

4)8(

17)

.63Pr

ior am

putat

ion, n

(%)

2(0.8

)2(

1.0)

0(0)

.48Pr

ior at

here

ctom y

, n (%

)4(

1.7)

4(2.1

)0(

0).47

Prior

b ypa

ss, n

(%)

18(7

.4)14

(7.2)

4(8.3

).70

Prior

enda

rtere

ctom y

, n (%

)6(

2.5)

4(2.1

)2(

4.2)

.41Di

seas

e sev

erit y

Ankle

-bra

chial

inde

x‡, m

ean (

SD)

0.43(

0.39)

0.40(

0.39)

0.60(

0.35)

.02

Total

occlu

sion,

n (%

)46

(19)

42(2

2)4(

8).04

Nu

mber

of le

sions

>50

%, m

ean (

SD)

1.8(1

.0)1.8

(0.9)

2.2(1

.2).01

Bi

later

al PA

D, n

(%)

53(2

2)36

(19)

17(3

5).01

Le

sion i

nform

ation

Le

sion l

ocati

on, n

(%)

Iliac

105(

43)

78(4

0)27

(56)

.05

Femo

ral

148(

61)

122(

63)

26(5

4).27

Popli

teal

34(1

4)28

(14)

6(13

).73

Othe

r belo

w kn

ee

8 (3)

7(4)

1(2)

.99Mo

st pr

oxim

al se

gmen

t, n (%

) Ilia

cFe

mora

lPo

plitea

lOt

her B

elow

105 (

43)

128 (

53)

6 (2)

3 (

1)

78 (4

0)

108(

56)

5 (3)

3 (

2)

27 (5

6)

20 (4

2)

1 (2)

0 (

0)

.23

TASC

lesio

n typ

e, n (

%)

A B C D

164 (

67.8)

63

(26.0

) 14

(5.8)

1 (

0.4)

139 (

71.6)

45

(23.2

) 10

(5.2)

1 (

0.5)

25 (5

2.1)

18 (3

7.5)

4 (8.3

) 0 (

0)

.04

Proc

edur

al inf

orma

tion

Patie

nts st

ented

, n (%

)19

4(80

)15

8(81

)36

(75)

.32Le

sions

sten

ted, m

ean (

SD)

1.3(1

.0)1.3

(0.9)

1.6(1

.5).04

Nu

mber

of st

ents,

mea

n (SD

)1.5

(1.2)

1.4(1

.0)1.9

(1.8)

.01

Sten

t leng

th(m

m), m

ean (

SD)

44.4

(27.5

)47

.9(2

7.5)

28.8

(22.2

)<.0

01

Sten

t diam

eter (

mm),

mean

(SD)

6.6(2

.3)6.9

(1.9)

5.3(3

.3).00

1 Pr

oced

ural

succ

ess,

n (%

)23

8(98

)19

0(98

)48

(100

).32

PHQ

scor

e, me

an (S

D)5.1

(6.0)

2.6(2

.8)15

.3(4

.2)


SD, s

tand

ard

devia

tion;

PHQ

, pat

ient h

ealth

que

stion

naire

; PAD

, per

ipher

al ar

teria

l dise

ase;

PER

, per

ipher

al en

dova

scula

r rev

ascu

lariza

tion;

mm

, milli

met

er; a

ll va

lues

expr

esse

d as

num

ber (

perc

ent)

unles

s ot

herw

ise n

oted

; *de

fined

as

any

smok

ing w

ithin

one

year

; †de

fined

as

seru

m c

reat

inine

>13

3 µm

ol/L

(1.5

mg/

dL);

‡ank

le-br

achia

l inde

x was

ava

ilable

in 1

61 p

atien

ts, o

f whic

h 21

clas

sified

as d

epre

ssed

.

Tota

l PH

Q de

pres

sive s

ympt

oms ≥

10

n=24

2 (10

0%)

Non=

194 (

80%

) Ye

sn=

48 (2

0%)

P va

lue

Demo

grap

hics

Age (

year

s), m

ean (

SD)

67.6

(11.2

) 68

.3 (1

1.5)

64.8

(9.5)

.05

Ca

ucas

ian, n

(%)

233(

96)

187(

96)

46(9

6).99

Male,

n (%

)14

7(61

)12

3(63

)24

(50)

.09Ma

rried

, n (%

)16

1(67

)12

5(64

)36

(75)

.21Me

dical

histor

yDi

abete

s mell

itus,

n (%

)93

(39)

69(3

6)24

(50)

.07H y

perte

nsion

, n (%

)16

5(68

)13

4(69

)31

(65)

.55Co

rona

r y ar

tery d

iseas

e, n (

%)

155(

64)

125(

64)

30(6

3).80

Con g

estiv

e hea

rt fai

lure,

n (%

)27

(11)

20(1

0)7(

15)

.40H y

perch

oleste

rolem

ia, n

(%)

161(

67)

133(

69)

28(5

8).18

Curre

nt tob

acco

use,

n (%

)*11

3(48

)93

(49)

20(4

3).40

Neph

ropa

thy, n

(%)†

6(2)

4(2)

2(4)

.34Hi

stor y

of pe

riphe

ral v

ascu

lar pr

oced

ures

Prior

PER

, n (%

)35

(14)

27(1

4)8(

17)

.63Pr

ior am

putat

ion, n

(%)

2(0.8

)2(

1.0)

0(0)

.48Pr

ior at

here

ctom y

, n (%

)4(

1.7)

4(2.1

)0(

0).47

Prior

b ypa

ss, n

(%)

18(7

.4)14

(7.2)

4(8.3

).70

Prior

enda

rtere

ctom y

, n (%

)6(

2.5)

4(2.1

)2(

4.2)

.41Di

seas

e sev

erit y

Ankle

-bra

chial

inde

x‡, m

ean (

SD)

0.43(

0.39)

0.40(

0.39)

0.60(

0.35)

.02

Total

occlu

sion,

n (%

)46

(19)

42(2

2)4(

8).04

Nu

mber

of le

sions

>50

%, m

ean (

SD)

1.8(1

.0)1.8

(0.9)

2.2(1

.2).01

Bi

later

al PA

D, n

(%)

53(2

2)36

(19)

17(3

5).01

Le

sion i

nform

ation

Le

sion l

ocati

on, n

(%)

Iliac

105(

43)

78(4

0)27

(56)

.05

Femo

ral

148(

61)

122(

63)

26(5

4).27

Popli

teal

34(1

4)28

(14)

6(13

).73

Othe

r belo

w kn

ee

8 (3)

7(4)

1(2)

.99Mo

st pr

oxim

al se

gmen

t, n (%

) Ilia

cFe

mora

lPo

plitea

lOt

her B

elow

105 (

43)

128 (

53)

6 (2)

3 (

1)

78 (4

0)

108(

56)

5 (3)

3 (

2)

27 (5

6)

20 (4

2)

1 (2)

0 (

0)

.23

TASC

lesio

n typ

e, n (

%)

A B C D

164 (

67.8)

63

(26.0

) 14

(5.8)

1 (

0.4)

139 (

71.6)

45

(23.2

) 10

(5.2)

1 (

0.5)

25 (5

2.1)

18 (3

7.5)

4 (8.3

) 0 (

0)

.04

Proc

edur

al inf

orma

tion

Patie

nts st

ented

, n (%

)19

4(80

)15

8(81

)36

(75)

.32Le

sions

sten

ted, m

ean (

SD)

1.3(1

.0)1.3

(0.9)

1.6(1

.5).04

Nu

mber

of st

ents,

mea

n (SD

)1.5

(1.2)

1.4(1

.0)1.9

(1.8)

.01

Sten

t leng

th(m

m), m

ean (

SD)

44.4

(27.5

)47

.9(2

7.5)

28.8

(22.2

)<.0

01

Sten

t diam

eter (

mm),

mean

(SD)

6.6(2

.3)6.9

(1.9)

5.3(3

.3).00

1 Pr

oced

ural

succ

ess,

n (%

)23

8(98

)19

0(98

)48

(100

).32

PHQ

scor

e, me

an (S

D)5.1

(6.0)

2.6(2

.8)15

.3(4

.2)


Baseline PAQ subscales and Summary score were compared by baseline depressive symptoms in Figure 1. Patients with depressive symptoms had lower scores on the PAQ Physical Limitation (12.7 vs. 20.6, P=.02), Symptoms (22.7 vs. 38.0, P<.0001), Treatment Satisfaction (77.0 vs. 82.9, P=.04) and Quality of Life (20.1 vs. 41.4, P<.0001) subscales, as well as the PAQ Summary scale (20.0 vs. 33.6, P<.0001) compared to those without depressive symptoms. The difference in Social Function-ing scores was not statistically significant for both groups (24.7 vs. 32.9, P=.07).

Figure 1 – Mean baseline PAQ subscales and Summary score compared by baseline depres-sive symptoms (PHQ ≥10). Error bars represent standard deviations; *P<.05; †P<.0001. Abbrevia-tions: PAQ, Peripheral Artery Questionnaire; PHQ, Patient Health Questionnaire.

0

20

40

60

80

100PHQ <10

PHQ ≥≥≥≥10

PhysicalLimitation

Symptoms TreatmentSatisfaction

Qualityof Life

SocialFunctioning

SummaryScore

*

*

† † †

Mean

PA

Q s

co

res


Higher PHQ depression scores at baseline were significantly associated with lower baseline PAD-specific health status scores (PAQ Summary score; β=-1.2 95%CI -1.6;-0.8, P<.0001). Adjusting for age, gender, coronary artery disease, chronic heart failure, diabetes and bilateral disease, baseline depressive symptoms remained independently associated with baseline PAD-specific health status (β=-1.0 95%CI -1.4;-0.7, P<.0001). A clinical relevant increase in depressive symptom scores (5 points), was associated with a 5 point decrease in the PAQ Summary score. These results were unchanged when the analysis was repeated in the subgroup with ankle-brachial index included as an extra covariate in the model.

At one year following PER, the changes in PAD-specific health status and depressive symptoms were compared among the 201 (83%) patients with no/improved depressive symptoms and the 41 (17%) with persistent or worsened depressive symptoms. Differences in baseline characteristics between these two groups were noted in gender; 39% of the male patients experienced persistent/worsened depressive symptoms vs. 61% of female patients, P=.001. Patients with persistent/worsened depres-sive symptoms had more lesions that were stented (1.7±1.3 vs. 1.3±1.0, P=.03) and more stents were used in this group (1.9±1.5 vs. 1.4±1.1, P=.04) as compared to no/improved depressive symp-toms. There were no differences in procedural success between depressive symptom groups (no/improved 98% vs. persistent/worsened 100%, P=.36).


Table 2 – Overview of depressive symptom scores and classification at baseline and one year follow-up stratified by one year follow-up health status response.

PAQ, Peripheral Artery Questionnaire; PHQ, Patient Health Questionnaire; SD, standard deviation.

Change in health status by 1 year

Responders (PAQ change ≥8) n=194/242 (80%)

Non-responders (PAQ change <8) n=48/242 (20%)

P value

PHQ baseline score, mean (SD) 4.9 (5.9) 6.0 (6.3) .24

Baseline depressive symptoms (PHQ ≥10)

.32

No depressive symptoms 158 (81) 36 (75)

Depressive symptoms 36 (19) 12 (25)

PHQ change score, mean (SD) -1.0 (6.7) 3.4 (8.3) .001

Change in depressive symptoms by 1yr

<.001

No/improved 172 (89) 29 (60)

Persistent/worsened 22 (11) 19 (40)


Table 2 provides an overview of PHQ depressive symptom scores and classification at baseline and one year follow-up stratified by one year follow-up health status response. Baseline depressive symptoms and baseline depression classification were not associated with health status response following PER at one year follow-up. In contrast, PHQ change scores (P=.001) and follow-up depres-sive symptoms were significantly associated with response in health status (P<.0001). In addition, Figure 2 provides an overview of one year depression status by baseline depression classification. Although the majority of patients without significant depressive symptoms at baseline (85%, 170/201) remained non-depressed at one year follow-up, 59% (24/41) of patients whose depressive symptoms worsened at one year follow-up, did not have significant depressive symptoms at baseline (P<.0001). In other words, these patients had a clinically important increase of ≥5 points in depression scores during follow-up.

Figure 2 – Overview of one year follow-up depressive symptoms: (A) no/improved depressive symptoms and (B) persistent/worsened depressive symptoms stratified by baseline depres-sive symptoms. Abbreviations: PHQ, Patient Health Questionnaire.


Changes in PAD-specific health status following PER are presented in Figure 3. The no/improved depression group improved on all subscales and Summary score (all P values <.0001), except for the Treatment Satisfaction scale which was very high at the time of the initial procedure and remained so in follow-up (82.6±16.5 vs. 82.9±21.0, P=.86). The persistent/worsened depressive symptoms group experienced statistically significant improvements on the Symptoms, Physical and Social Limitation and overall Summary score (P<.0001), but not the Treatment Satisfaction (P=.07) or Quality of Life (P=.09) subscales (Figure 3).


Figu

re 3

– M

ean

chan

ge s

core

s fo

r PAQ

sub

scale

s an

d Su

mm

ary

scor

e (b

aseli

ne v

s. on

e ye

ar fo

llow-

up) c

ompa

red

by n

o/im

prov

ed

depr

essiv

e sym

ptom

s ver

sus p

ersis

tent

/wor

sene

d de

pres

sive s

ympt

oms.

Abbr

eviat

ions:

PAQ,

Per

ipher

al Ar

tery Q

uesti

onna

ire.

-50

-40

-30

-20

-10

01

02

03

04

05

0

Ph

ys

ica

l L

imit

ati

on

Sy

mp

tom

s

Tre

atm

en

t S

ati

sfa

cti

on

Qu

ality

of

Lif

e

So

cia

l L

imit

ati

on

s

Su

mm

ary

Sc

ore

No

/im

pro

ved

dep

ressiv

e s

ym

pto

ms

Pers

iste

nt/

wo

rsen

ed

dep

ressiv

e s

ym

pto

ms

All

Pvalu

es s

ign

ific

an

t at

P<

.05

be

twe

en

:

PA

Q c

han

ge s

co

res


Importantly, the magnitude of PAD-specific health status benefits from PER differed significantly be-tween the groups on all subscales and Summary score (all P values <.05), with the persistent/worse depressive symptoms group showing less improvement in all PAD-specific health status domains as compared with those who never had significant depressive symptoms or whose depressive symp-toms improved.

Increases in depressive symptoms following PER were significantly associated with declines in PAD-specific health status at one year following PER (PAQ Summary scores; β=-1.3, 95%CI -1.7;-0.8, P<.0001). Adjusting for age, gender, coronary artery disease, chronic heart failure, diabetes, bilateral disease, and baseline health status, changes in depressive symptoms remained independently as-sociated with changes in PAD-specific health status at one year follow-up (β=-1.1, 95%CI -1.6;-0.8, P<.0001). A significant increase in depressive symptoms (5 points) was associated with a 6 point decrease in PAQ Summary scores at one year follow-up. These results were unchanged when the analysis was repeated in the subgroup with ankle-brachial index included as an extra covariate in the model.


DISCUSSION

One in five patients undergoing PER had clinically significant depressive symptoms at the time of their revascularization. Baseline depression class correlated significantly with most subscales of PAD-specific health status prior to PER: compared with patients without depressive symptoms, patients with significant depressive symptoms experienced more physical limitation, higher symptom burden, less treatment satisfaction, and lower quality of life. Moreover, a substantial proportion of all patients undergoing PER (17%) experienced persistent or worsened depressive symptoms at one year. Of note, the majority of these patients were patients who did not have significant depressive symp-toms at baseline and were thus patients whose depressive symptoms increased substantially during follow-up. Changes in depressive symptoms during follow-up, but not baseline depression symptoms, were associated with worse health status response following PER. Although patients with persistent or worsened depressive symptoms did display modest benefit for PER over one year, their quality of life and treatment satisfaction did not improve significantly. More importantly, the PAD-specific health status benefits of PER were significantly blunted in those with persistent or worsened depressive symptoms at one year. Collectively, these findings underscore the importance of depressive symp-toms on patients’ perceptions of their disease and the benefits that they attain from treatment.

Although prior studies have demonstrated an association between depressive symptoms, occlusive peripheral arterial disease, lower-leg symptoms, and functional decline,3-6 the interplay between de-pressive symptoms and PAD-specific health status has not yet been investigated from patients’ per-spectives. The findings of the current study that depressive symptoms – both cross-sectionally and at one year following revascularization - were associated with worse PAD-specific health status are consistent with findings from prior research in other cardiovascular disease populations.13-15, 29

Focusing on health status outcomes in cardiovascular disease is especially important in PAD patients as this chronic disease greatly impacts patients’ daily functioning.3 Although hemodynamic success and patency rates are important outcomes following PER, information obtained from health status outcomes can complement clinical indices because of their ability to evaluate the disease and treat-ment outcomes from a patient’s perspective. Previous research indicated that PAD patients are not always responsive in terms of health status after revascularization.12 In the current study, depressive symptoms were identified as a possible barrier that prevented patients from experiencing maximal improvement in PAD-specific health status after PER.


The understanding of the relationship between depressive symptoms and cardiovascular disease in general is not conclusive and the critical question that remains to be answered is whether de-pressive symptoms merely occurs as an epiphenomenon of cardiovascular disease or whether it reflects disease burden. Proposed pathophysiological and behavioral mechanisms for this – probably bidirectional relationship – include autonomic imbalance and activation of the hypothalamic-pituitary-adrenal axis, dysregulation of immunologic mechanisms, increased platelet activation, the associa-tion of depressive symptoms with a worse cardiovascular risk profile, life style factors, and failure to adhere to medical recommendations.30, 31 Possible mechanisms that specifically explain the link between depressive symptoms and health status are even less known; failure to be compliant with cardiovascular prevention strategies, e.g., difficulty with taking prescribed medications, may partly explain this association.32 The current study clearly cannot disentangle the direction of the relation-ship between depressive symptoms and impaired health status and thus future research aimed at alleviating depressive symptoms in those with persistent/worsened depressive symptoms after suc-cessful revascularization is needed and will allow for a direct test to certify that depressive symptoms impact patients’ health status.

Meanwhile, we believe that our findings illustrate that assessment and treatment of significant de-pressive symptoms is warranted in all PAD patients. First of all because depression in itself is one of the leading causes of disability worldwide33 and more specifically because depressive symptoms are associated with diminished benefits in PAD-specific health status after revascularization in PAD. Since baseline depressive symptoms were not associated with response in PAD-specific health sta-tus following PER, but changes in PHQ depressive symptoms during one year follow-up were, the results of our study indicate that depression screening needs to be an ongoing process; both when a patient first enters clinical practice and during follow-up. Vascular surgeons, interventionalists, and other clinicians involved in PAD management can facilitate depression recognition by incorporating systematic depression screening into daily care systems. The use of a simple screening tool, such as the PHQ-9, and close collaboration with other specialists involved in psychiatric screening and treat-ment are key factors that contribute to a greater awareness of depressive symptoms in PAD. As evi-dence of this, the American Heart Association and the American Psychiatric Association recommend routine depression screening in patients with coronary heart disease in various settings.21 While these recommendations do not necessarily apply on patients undergoing peripheral revascularization, there is no reason that assessment of depressive symptoms should not be extended to PAD patients. Furthermore, there is a need to establish a firm tradition of research on psychological risk factors in


PAD on its own by addressing their association with prognosis, patients’ health status, and underlying mechanisms and using this information in strategies to maximize health status outcomes.34, 35

Several limitations must be addressed in interpreting our findings: this is a prospective single-center registry of patients undergoing PER only. Compared with other studies, the study group had sig-nificant symptoms of PAD that necessitated referral for angiography and PER. Thus, these findings may not be applicable to patients with less severe PAD. Ankle-brachial index assessment was only available for a subset of patients in this study, and therefore multivariable analyses could not be adjusted for this index in the total study sample. Instead, we used bilateral disease as an indication for disease severity. In addition, sensitivity analyses including the ankle-brachial index as an extra covariate were performed and our results were not altered by including this disease severity index. Next, depression was not confirmed with a psychiatric diagnosis obtained from interview data, but we used a self-report instrument that has been shown to have good sensitivity and specificity to identify patients with a high probability of major depression.22, 23 On the other hand, both major depression and depressive symptoms are prognostic for outcomes and related to health status in cardiovascular disease.13, 36 Other potential treatments of depression were not evaluated. It is possible that depres-sion was diagnosed in the peri-procedural period or after discharge and therapy initiated, which could account for at least some of the improvements seen here. Although no data are available document-ing antidepressant treatment in PAD, reports from cardiac populations indicate that depression is often undertreated.37 Finally, due to the lack of protocol-driven angiographic follow-up; it is not pos-sible to correlate the 1-year outcomes with anatomic information. Therefore, future research needs to further explore whether depressive symptoms preceded worse 1-year outcomes, or whether those with worse outcomes became depressed at follow-up.

Despite these limitations, the ALEVE study indicates that depressive symptoms are associated with worse health status scores at baseline. Although patients with significant depressive symptoms im-proved on most health status subscales one year following revascularization, they made less prog-ress than patients without symptoms or patients whose depressive symptoms improved, apparently undermining the benefits of PER. Collectively, these results support the idea that there is an important opportunity to assess and treat depressive symptoms in PAD patients in order to maximize PAD-specific health status outcomes after peripheral revascularization.


REFERENCES

1. Criqui MH, Fronek A, Barrett-Connor E, Gabriel S, Goodman D. The prevalence of peripheral arterial disease in a defined population. Circulation 1985;71:510-15.

2. Criqui MH, Denenberg JO, Langer RD, Fronek A. The epidemiology of peripheral arterial disease: impor-tance of identifying the population at risk. Vasc Med 1997;2:221-26.

3. McDermott MM, Greenland P, Liu K, Guralnik JM, Criqui MH, Dolan NC, et al. Leg symptoms in peripheral arterial disease. Associated clinical characteristics and functional impairment. JAMA 2001;286:1599-606.




7. Beekman ATF, Copeland JRM, Prince MJ. Review of community prevalence of depression in later life. Br J Psychiatry 1999;174:307-11.



10. Anderson PL, Gelijns A, Moskowitz A, Arons R, Gupta L, Weinberg A, et al. Understanding trends in inpatient surgical volume: vascular interventions, 1980-2000. J Vasc Surg 2004;39:1200-8. American Psy-chiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition.

11. Bosch JL, van der Graaf Y, Hunink MG. Health-related quality of life after angioplasty and stent placement in patients with iliac artery occlusive disease: results of a randomized controlled clinical trial. The Dutch Iliac Stent Trial Study Group. Circulation 1999;99:3155-160. (DSM-IV). Washington, DC: American Psychi-atric Publishing; 1994.


13. Rumsfeld JS, Havranek E, Masoudi FA, Peterson ED, Jones P, Tooley JF, et al. Depressive symptoms are the strongest predictors of short-term declines in health status in patients with heart failure. J Am Coll Cardiol 2003;42:1811-17.


14. Pedersen SS, Denollet J, Spindler H, Ong AT, Serruys PW, Erdman RA, et al. Anxiety enhances the det-rimental effect of depressive symptoms on health status following percutaneous coronary intervention. J Psychosom Res 2006;61:783-9.

15. Mallik S, Krumholz HM, Lin ZQ, Mattera JA, Roumains SA, et al. Patients with depressive symptoms have lower health status benefits after coronary artery bypass surgery. Circulation 2005;111:271-7.

16. Katzen BT, Chang J, Knox WG. Percutaneous transluminal angioplasty with the Gruntzig balloon catheter. A review of 70 cases. Arch Surg 1979;114:1389-99.


18. Spitzer RL, Williams JB, Kroenke K, Linzer M, deGruy FV, 3rd, Hahn SR, et al. Utility of a new procedure for diagnosing mental disorders in primary care. The PRIME-MD 1000 study. JAMA 1994;272:1749-56.


20. Gilbody S, Richards D, Brealey S, Hewitt C. Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. J Gen Intern Med 2007;22:1596-602.

21. Lichtman JH, Bigger JT, Jr., Blumenthal JA, Frasure-Smith N, Kaufmann PG, Lespérance F, et al. Depres-sion and Coronary Heart Disease. Recommendations for Screening, Referral, and Treatment. A Science Advisory From the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council on Epidemiology and Prevention, and Interdisciplinary Council on Quality of Care and Outcomes Research. Circulation 2008;118:1768-75.

22. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA 1999;282:1737-44.

23. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606-13.

24. Lowe B, Schenkel I, Carney-Doebbeling C, Gobel C. Responsiveness of the PHQ-9 to Psychopharmaco-logical Depression Treatment. Psychosomatics 2006;47:62-7.

25. Lowe B, Unutzer J, Callahan CM, Perkins AJ, Kroenke K. Monitoring depression treatment outcomes with the Patient Health Questionnaire-9. Med Care 2004;42:1194-201.


27. Cohen J. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Academic Press; 1988.28. Sloan J. Symonds T, Vargas-Chanes D, Fridley B. Practical guidelines for assessing the clinical signifi-

cance of health-related quality of life changes within clinical trials. Drug Inf J 2003;37:23-31.


29. Ruo B, Rumsfeld JS, Hlatky MA, Liu H, Browner WS, Whooley MA. Depressive symptoms and health-related quality of life: the Heart and Soul Study. JAMA 2003;290:215-21.

30. Barth J, Schumacher M, Herrmann-Lingen C. Depression as a risk factor for mortality in patients with coronary heart disease: a meta-analysis. Psychosom Med 2004;66:802-13.

31. Lett HS, Blumenthal JA, Babyak MA, Sherwood A, Strauman T, Robins C, et al., Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment. Psychosom Med 2004;66:305-15.

32. Morgan AL, Masoudi FA, Havranek EP, Jones PG, Petersen PN, Krumholz HM, et al., Difficulty taking medications, depression, and health status in heart failure patients. J Card Fail 2006;12:54-60.

33. Mathers CD and Loncar D. Projections of global mortality and burden of disease from 2000 to 2030. PLoS Med 2006;3:e442.

34. Miller MD, Schulz R, Paradis C, Houck PR, Mazumdar S, Frank E, et al. Changes in perceived health status of depressed elderly patients treated until remission. Am J Psychiatry 1996;153:1350-2.

35. Swenson JR, O’Connor CM, Barton D, Van Zyl LT, Swedberg K, Forman LM, et al. Influence of depression and effect of treatment with sertraline on quality of life after hospitalization for acute coronary syndrome. Am J Cardiol 2003;92:1271-6.

36. Penninx BW, Beekman AT, Honig A, Deeg DJ, Schoevers RA, Van Eijk JT, et al. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry 2001;58:221-7.

37. Koenig H. Depression in hospitalized older patients with congestive heart failure. Gen Hosp Psychiatry

1998;20:29-43.

Chapter 8

Type D personality and reduced benefi t following exercise therapy in

peripheral arterial disease

8

176 Chapter 8 - Type D personality, exercise therapy, PAD

Smolderen KG, Kruidenier LM, Denollet J, Nicolaï SPA, Vriens PW, Teijink JAW. Type D personality and outcomes following exercise therapy in peripheral arterial disease. Submitted.

ABSTRACT

Background: Supervised exercise therapy in peripheral arterial disease (PAD) improves lower-leg functioning and functional capacity. To identify barriers compromising outcomes exercise therapy, we compared patients’ walking ability, benefit finding, and rates of invasive treatment following super-vised exercise therapy in PAD patients as a function of a Type D personality (tendency to experience psychological distress).

Design: Retrospective observational follow-up study.

Methods: All 218 patients completed the Type D scale and underwent a supervised exercise therapy protocol. Chart abstraction was completed at baseline and at 52 weeks follow-up. Walking ability was assessed at baseline, four, 12, 26, and 52 weeks follow-up.

Results: Despite the fact that all patients significantly improved their walking ability following exercise therapy (P’s <.0001), having a Type D personality was independently associated with worse walk-ing ability on all assessment points compared with non-Type D’s (P<.01 for functional claudication distance and a non-significant trend for absolute claudication distance, P=.07). The magnitude of improvement in walking distance did not differ for patients with and without a Type D personality (P values for interaction terms Type D*time >.05). Importantly, patients with a Type D personality per-ceived the exercise therapy as less beneficial (32% vs. 15%, P<.01) and eventually received more invasive treatment within follow-up (28% vs. 12%, P<.01) compared with non-Type D’s.

Conclusions: Despite the significant clinical improvement both in Type D and non-Type D patients following supervised exercise therapy, patients with a distressed personality type rated exercise therapy as less beneficial, and eventually received more aggressive treatment. Future studies need to evaluate whether PAD patients with a Type D personality may need extra support in order to fully benefit from conservative intervention programs.


BACKGROUND

In peripheral arterial disease (PAD), arterial perfusion is disturbed in the lower extremities due to ath-erosclerosis.1 PAD is a chronic, disabling disease2 and due to the co-presentation of cardiovascular risk factors, patients are at increased risk of suffering a cardiovascular event.3 Treatment in symp-tomatic lower extremity PAD is primarily aimed at relieving leg symptoms and dealing with comorbid conditions such as hypertension and hypercholesterolemia.

The preferred treatment to decrease leg symptoms PAD is exercise therapy.1 Although invasive treat-ment options are capable of offering quick relief of leg symptoms, the long-term results of those procedures are mixed.4 Exercise therapy is more time consuming and demanding for the patient to maintain, however, multiple benefits are gained by this strategy; improved walking ability, daily functioning, and likely prognosis regarding survival improves have been associated with a protocol of intense exercise therapy.5

Patients’ psychological make-up may be a possible barrier in the promotion of physical activity in PAD patients.6 A possible risk factor in this context may be the distressed personality type or “Type D” per-sonality.7 Patients with a Type D personality tend to experience a broad range of negative emotions and are unable to share these feelings with others.7 This personality type has been independently as-sociated with poor health status8 and adverse prognosis in cardiovascular patients.9, 10 Whether out-comes following supervised exercise therapy differ as a function of patients’ personality, has not been studied. We therefore compared PAD patients’ walking ability patients’ perceived benefit, and rates of invasive treatment following supervised exercise therapy as a function of Type D personality.


METHODS

Patients

All consecutive PAD patients referred for community-based supervised exercise therapy from January 2005 through September 2006 were included at the vascular outpatient clinic of the Atrium Medical Center, Heerlen, The Netherlands.11 All patients underwent vascular laboratory assessment to con-firm PAD diagnosis, which included ankle brachial index (ABI) measurement and duplex ultrasound scanning. Furthermore, an extensive history and measurement of clinical risk factors was performed by a nurse practitioner and documented in patients’ charts. All participating patients gave informed consent and the study was approved by the local ethics committee.

ABI measurementThe ABI was calculated by dividing the highest systolic ankle pressure of each leg by the highest systolic pressure of the left and right brachial arteries. PAD was considered to be present with an ABI below 0.90 in rest or decreasing more than 15% after exercise.

Exercise program and assessment of walking distancePatients received community-based supervised exercise therapy, according to national guidelines.11,

12 Generally, patients started with high frequency (2–3 sessions a week) during the first three months. After these three months, the frequency was reduced. The main mode of training was treadmill walk-ing up to submaximal pain. Furthermore, patients were encouraged to walk at a daily basis, in addi-tion to the training at the physiotherapy practice. Re-evaluation of functional performance took place at baseline, four, 12, 26 and 52 weeks by means of treadmill testing. Functional claudication distance (FCD–the distance at which a patient prefers to stop because of claudication pain) and absolute claudication distance (ACD–maximum walking distance) were determined in all patients.13 All patients were evaluated according to this protocol, unless comorbid conditions prevented them from perform-ing according to these guidelines. In such cases, an adjusted protocol was used both at the start of the therapy and throughout follow-up (e.g., slower pace, a lower gradient).


Type D personalityAll patients completed the DS14 7 after completing their exercise therapy; the DS14 consists of two 7-item subscales assessing negative affectivity and social inhibition. Questions are answered along a 5-point Likert scale. Sum scores ≥10 on both subscales indicate a Type D personality. The subscales have good reliability and previous research in cardiac patients indicated that Type D personality is a stable trait.14

Benefit and revascularizationAt the time personality assessment took place, patients were also asked whether they considered the supervised exercise therapy to be beneficial to them (yes/no) and patients’ medical records were searched to see which patients eventually received a revascularization (bypass surgery, endarterec-tomy, or percutaneous transluminal angioplasty) within 52 weeks of follow-up.


Baseline characteristics were examined for the total sample and stratified by Type D personality. Chi-square tests were used for categorical variables and Student t-tests for continuous variables. To analyze the longitudinal walking distance data (FCD and ACD), generalized estimating equa-tions (GEE) assuming exchangeable correlation structures were used. With GEE the relationships between variables of the model at different time-points are analyzed simultaneously; it combines a within-subject relationship with a between-subjects relationship, resulting in one single regression coefficient. Both univariable and multivariable GEE analyses stratifying by Type D personality us-ing FCD and ACD as outcome measures were performed. Whether Type D patients differed from their non-Type D counterparts regarding perceived benefit finding and revascularization procedures performed within follow-up, was examined using Chi-square tests and logistic regression analyses. Covariates in all multivariable analyses included age, sex, cardiac history, diabetes mellitus, ABI, and having an adjusted protocol. In patients undergoing a vascular intervention during the year of follow-up, the last result before the vascular intervention was carried forward. All analyses were performed using SPSS for Windows, version 16.0 (SPSS Inc., Chicago, Illinois) and P values <.05 were consid-ered statistically significant.


Results

A total of 324 patients participated in exercise therapy. By the time questionnaires were administered at follow-up, 13 patients were deceased, 12 patients were lost to follow-up (moved or had inacces-sible telephone connection), leaving 299 patients. Of those patients, 218 (73%) patients completed follow-up. Non-responders did not differ significantly from responders regarding demographics and clinical factors, although non-responders did have shorter baseline ACD (406m vs. 521m, P<.01).


Tabl

e 1 –

Base

line c

hara

cter

istics

of t

he to

tal s

ampl

e (n=

218)

and

stra

tified

by T

ype D

per

sona

lity.

Char

acte

ristic

To

tal s

ampl

e

(n=2

18, 1

00%

)

No T

ype D

pe

rson

ality

(n

=153

, 70%

)

Type

Dpe

rson

ality

(n

=65,

30%

)

P va

lue

Demo

grap

hics

Age,

mean

(SD)

, yea

rs 65

(10)

65 (1

1)

65 (1

0)

.74Ma

le se

x 13

7 (63

) 93

(61)

43

(66)

.45

Card

iovas

cular

histo

ry An

gina p

ector

is 35

(16)

22

(14)

13

(20)

.30

Myoc

ardia

l infar

ction

26

(12)

14

(9)

11 (1

7)

.10Tr

ansie

nt isc

hemi

c atta

ck

16 (7

) 11

(7)

4 (6)

.78

Stro

ke

14 (6

) 13

(9)

1 (2)

.06

Clini

cal fa

ctors

Diab

etes m

ellitu

s 80

(37)

49

(32)

30

(46)

.05

Hype

rchole

stero

lemia

171(

78)

122 (

80)

48 (7

4)

.34Hy

perte

nsion

170(

78)

120 (

78)

49 (7

5)

.62Ci

gare

tte sm

oking

10

5 (48

) 67

(44)

37

(57)

.08

Chro

nic ob

struc

tive p

ulmon

ary d

iseas

e31

(14)

19

(12)

12

(19)

.24

Osteo

arthr

itis13

(6)

11 (7

) 2 (

3)

.24An

kle-b

rach

ial in

dex,

mean

(SD)

0.7

5 (0.2

0)

0.74 (

0.18)

0.7

7 (0.2

4)

.50Ad

justed

exer

cise t

reatm

ent p

rotoc

ol28

(13)

17

(11)

11

(17)

.24

*Dat

a ar

e pr

esen

ted

as n

umbe

r (pe

rcen

tage

) of e

ach

grou

p, u

nless

oth

erwi

se in

dicat

ed. A

bbre

viatio

ns: S

D, st

anda

rd d

eviat

ion.


Baseline characteristics of the total sample and as a function of Type D classification are presented in Table 1. The mean age of the total sample was 65 years, and 63% was male. Whereas patients with a Type D personality were more likely to have diabetes mellitus, other demographic and clinical char-acteristics were not statistically different between Type D’s and non-Type D’s. An overview of patients’ mean functional and absolute claudication distances over time is presented in Table 2.


Tabl

e 2 –

Mean

(SD)

func

tiona

l and

abso

lute

clau

dica

tion

dist

ance

in m

eter

s ove

r tim

e.

Abbr

eviat

ions :

SD,

stan

dard

dev

iation

.

Func

tiona

l clau

dica

tion

dist

ance

, met

ers (

SD)

Base

line

4 wee

ks

12 w

eeks

26

wee

ks

52 w

eeks

Non-

Type

D

392.6

(362

.9)

594.2

(409

.5)

714.6

(459

.1)

896.0

(523

.9)

925.5

(534

.4)

Type

D

262.2

(201

.6)

469.5

(373

.2)

592.6

(512

.4)

738.0

(571

.0)

804.4

(567

.8)

Abso

lute

clau

dica

tion

dist

ance

, met

ers (

SD)

Base

line

4 wee

ks

12 w

eeks

26

wee

ks

52 w

eeks

Non-

Type

D

596.8

(407

.5)

789.4

(423

.1)

941.1

(470

.4)

1087

.2 (5

06.2)

11

03.7

(516

.8)

Type

D

465.4

(372

.8)

698.2

(444

.6)

795.1

(507

.8)

896.9

(560

.9)

944.4

(549

.8)


In univariable GEE analyses, there was an overall effect of time for FCD scores (P<.0001), improve-ment was significant for all assessment points (P’s <.0001). Type D was associated with shorter FCD (β=-123.8; 95% CI -206.7/-40.8; P<.01) as compared with non-Type D personality (Figure 1A). The time by Type D interaction terms were not significant (P values between .65 and .95), demonstrat-ing that the magnitude in walking distance improvement was not significantly different for patients with and without a Type D personality. The main effect for Type D personality remained significant after multivariable adjustment (β=-128.6; 95% CI -212.5/-44.7; P<.01). There was an overall effect of time for the course of ACD scores (P<.0001); all improvements in ACD over time were significant (P’s <.0001). Type D personality was correlated with shorter ACD as compared with non-Type D’s both in unadjusted (β=-93.9; 95%CI -214.8/27.1, P=.13) (Figure 1B) and adjusted (β=-106.2; 95%CI -221.4/9.0.1, P=.07) GEE analyses, although this effect failed to reach statistical significance. No interaction effects between Type D and time were observed (P values between .43 and .99).

Figure 1 – Course of (A) functional claudication distance (FCD) and (B) absolute claudica-tion distance (ACD) stratified by Type D personality. Estimated means and standard errors are presented.

Course of functional claudication distance (FCD)

0

200

400

600

800

1000

1200non-Type D

Type D

4 weeks 12 weeks 26 weeks 52 weeks

P<.01

Time (weeks)

Mean

FC

D (

m)

Course of absolute claudication distance (ACD)

0

200

400

600

800

1000

1200

non-Type D

Type D

4 weeks 12 weeks 26 weeks 52 weeks

P=.13

Time (weeks)

Mean

AC

D (

m)

A

B


Type D patients perceived their exercise therapy as less beneficial to them (no benefit in 32% for Type D’s vs. 15% for non-Type D’s, P<.01) as compared with non-Type D’s (Figure 2A). This result re-mained significant in multivariable logistic regression analysis (OR Type D for no benefit finding=2.4; 95% CI 1.1-5.0; P<.05). Type D patients eventually received more invasive treatment during follow-up (28% vs. 12%, P<.01) as compared with non-Type D’s (Figure 2B). These results persisted in multi-variable logistic regression analysis (OR Type D for invasive treatment=2.7; 95% CI 1.3-5.5; P<.01).


Figure 2 – (A) Proportion and percentages of patients that found exercise therapy to be non-beneficial as a function of Type D personality; (B) proportions and percentages that received invasive treatment during follow-up by Type D personality.

A Did not consider exercise therapy as beneficial

non-Type D Type D0

10

20

30

40

23/153

21/65

P<.01non-Type D

Type D

%

B Revascularization within follow-up period

non-Type D Type D0

10

20

30

19/153

18/65

P<.01 non-Type D

Type D

%


DISCUSSION

Both Type D and non-Type D patients significantly improved following supervised exercise therapy, and the degree to which they improved was not different for patients with or without a Type D per-sonality. However, having a Type D personality was consistently associated with shorter FCD’s both when entering exercise treatment and after completing therapy, compared with non-Type D patients. Importantly, Type D patients reported less perceived benefit following exercise therapy as compared with non-Type D’s. Finally, despite the fact that the first-choice of treatment was supervised exercise therapy, Type D patients eventually received more invasive treatment within the period of one year follow-up, as compared with non-Type D’s.

Prior studies on Type D personality in cardiac populations described the link between this personal-ity type and inadequate self-management behavior in heart failure patients,15 and the relationship between Type D personality and poorer performance on the 6-minute walking test following coronary artery bypass surgery.16 The new finding in our study is that although Type D patients significantly improved following supervised exercise therapy, they still considered exercise therapy to be less beneficial to them and they eventually were more likely to receive aggressive treatment for their PAD, compared with non-Type D’s.

Type D patients typically experience a broad range of negative feelings while not expressing these feelings in social interaction.7 Type D has been repeatedly identified as an independent predictor of poor health status and depressive symptoms.8, 17 One could argue that overall, patients with a Type D personality have a more pessimistic view of life, however, recent findings illustrate that this per-sonality construct is independently associated with an adverse prognosis both in cardiac and PAD populations.9, 10 In addition, preliminary findings illustrate that both behavioral mechanisms, such as poor-self management behavior,15 and pathophysiological pathways, such as increased inflammation and cortisol output, may partly explain the link between Type D personality and cardiovascular prog-nosis.18 Interventional studies directly aimed at improving outcomes in Type D patients are currently lacking. The purpose of treatment for Type D patients is not altering patients’ personality, because personality traits are rather robust19 and because the Type D personality configuration in itself is not psychopathological, but based on normal personality traits.20


This study provides indirect evidence that exercise treatment targeted at functional improvement of patients is not enough to allow Type D patients to fully benefit from conservative treatment. These results are consistent with previous findings in cardiac rehabilitation patients: Type D patients re-ported poorer health status compared with non-Type D patients pre- and post cardiac rehabilitation.21 Interventions probably need to address multiple tangible and changeable elements that may predis-pose Type D patients to adverse outcomes; relieving patients’ stress level and enhancing patients’ self-management skills may be key factors in this context. In order to design such interventions, prospective studies that further disentangle mechanisms involved in the relationship between Type D personality and adverse outcomes are needed.

It was also interesting to see that Type D patients received more invasive treatment within the period of follow-up, although supervised exercise therapy was the first-choice of treatment in all participants. Results of randomized controlled trials comparing exercise therapy versus revascularization indicate that from a societal perspective and when taking into account cost-effectiveness, a predominantly conservative approach is warranted in patients with symptomatic PAD.22 More importantly, revascu-larization procedures are primarily aimed at relieving lower-leg symptoms in PAD and do not prolong life expectancy whereas exercise treatment both focuses on improvement in functional status and indirectly on improving long-term prognosis as physical activity in intermittent claudication has been associated with increased survival, independent of age, ABI and body-mass-index.23

The results of the current study indicate that we need to understand that psychological mechanisms may play a pivotal role in preventing patients from obtaining maximal results in conservative treat-ment for patients with PAD. Additional support by means of cognitive-behavioral interventions may be needed to optimize treatment outcomes in patients with a vulnerable psychological profile.6 Tailor-made exercise programs that explore patients’ expectations, question patients’ illness perceptions, and that adopt a stepwise approach focussing on realistic goals have previously proven to be more beneficial as compared with standardized exercise therapy in older patients with chronic disease.24

Our results should be interpreted against the following limitations: first, we were only able to assess Type D personality following supervised exercise treatment. Although prior research indicated that Type D personality is a stable taxonomy,14 our results need to be replicated using Type D classifi-cation information that was obtained from baseline assessment. Second, since these results were based on observational data, no causality can be inferred and we need to consider the possibility


of residual confounding. Third, Type D was only statistically significantly associated with FCD, al-though a clear trend was observed for ACD. A larger sample size would probably have enabled us to demonstrate statistically significant results for both walking ability measures. Finally, angiographic information or ABI at follow-up were not available to correlate one year outcomes following exercise therapy with anatomic information.

In closing, the results of the current study suggest that personality may be an important factor to take into account when providing supervised exercise therapy in patients with PAD. The diminished benefit of patients with a Type D personality was clear in patients’ walking distance scores, their subjective evaluation, and the fact that they were more invasively treated as compared with non-Type D pa-tients. Clinicians can use this information to understand more clearly why certain patients are not fully benefiting from supervised exercise therapy. Greater awareness for psychological factors in clinicians treating PAD patients and close collaboration with professionals who can assist in addressing the cognitive-behavioral aspects in conservative treatment are needed to maximize successful outcomes following supervised exercise therapy.


REFERENCES


2. Regensteiner JG, Hiatt WR, Coll JR, Criqui MH, Treat-Jacobson D, McDermott MM, et al. The impact of peripheral arterial disease on health-related quality of life in the Peripheral Arterial Disease Awareness, Risk, and Treatment: New Resources for Survival (PARTNERS) Program. Vasc Med 2008;13:15-24.

3. Meru AV, Mittra S, Thyagarajan B, Chugh A. Intermittent claudication: an overview. Atherosclerosis 2006;187:221-37.


5. Stewart KJ, Hiatt WR, Regensteiner JG, Hirsch AT. Exercise training for claudication. N Engl J Med 2002;347:1941-51.

6. Rejeski WJ, Tian L, Liao Y, McDermott MM. Social cognitive constructs and the promotion of physical activ-ity in patients with peripheral artery disease. J Cardiopulm Rehabil Prev 2008;28:65-72.

7. Denollet J. DS14: Standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosom Med 2005:89-97.

8. Aquarius AE, Denollet J, Hamming JF, De Vries J. Role of Disease Status and Type D Personality in Out-comes in Patients with Peripheral Arterial Disease. Am J Cardiol 2005;96:996-1001.

9. Pedersen SS, Lemos PA, van Vooren PR, Liu TK, Daemen J, Erdman RA, et al. Type D personality predicts death or myocardial infarction after bare metal stent or sirolimus-eluting stent implantation: a Rapamycin-Eluting Stent Evaluated at Rotterdam Cardiology Hospital (RESEARCH) registry substudy. J Am Coll Cardiol 2004;44:997-1001.

10. Aquarius AE, Smolderen KG, De Vries J, Vriens PW, Denollet J. Type D personality predicts mortality in patients with peripheral arterial disease. Arch Surg 2009; 144:728-23.

11. Kruidenier LM, Nicolai SP, Hendriks EJ, Bollen EC, Prins MH, Teijink JA. Supervised exercise therapy for intermittent claudication in daily practice. J Vasc Surg 2009;49:363-70.

12. Jongert M, Hendriks H, van Hoek J, Klaasboer-Kogelman K, Robeer G, Simens B, et al. KNGF Richtlijn Claudicatio Intermittens. Nederlands Tijdschrift voor Fysiotherapie 2003 (Suppl):3-58.

13. Gardner AW, Skinner JS, Cantwell BW, Smith LK. Progressive vs. single-stage treadmill tests for evalua-tion of claudication. Med Sci Sports Exerc 1991;23:402-8.

14. Martens EJ, Kupper N, Pedersen SS, Aquarius AE, Denollet J. Type D personality is a stable taxonomy in post-MI patients over an 18-month period. J Psychosom Res 2007;63:545-50.


15. Schiffer AA, Denollet J, Widdershoven JW, Hendriks EH, Smith OR. Failure to consult for symptoms of heart failure in patients with a Type D personality. Heart 2007;93:814-8.

16. Simon A, Tringer I, Berenyi I, Veress G. Psychological factors considerably influence the results of 6-min walk test after coronary bypass surgery. Orv Hetil 2007;148:2087-94.

17. Pedersen SS, Ong AT, Sonnenschein K, Serruys PW, Erdman RA, van Domburg RT. Type D personality and diabetes predict the onset of depressive symptoms in patients after percutaneous coronary interven-tion. Am Heart J 2006;151:367 e1-367 e6.

18. Denollet J, Conraads VM, brutsaert DL, Clerck LSD, Stevens WJ, Vrints CJ. Cytokines and immune activa-tion in systolic heart failure: the role of Type D personality. Brain Behav Immun 2003;17:304-9.

19. Costa PT, Jr., McCrae RR. Stability and change in personality assessment: the revised NEO Personality Inventory in the year 2000. J Pers Assess 1997;68:86-94.

20. Denollet J. Type D personality. A potential risk factor refined. J Psychosom Res 2000;49:255-66.21. Pelle AJ, Erdman RA, van Domburg RT, Spiering M, Kazemier M, Pedersen SS. Type D patients report

poorer health status prior to and after cardiac rehabilitation compared to non-Type D patients. Ann Behav Med 2008;36:167-75.

22. de Vries SO, Visser K, de Vries JA, Wong JB, Donaldson MC, Hunink MG. Intermittent claudication: cost-effectiveness of revascularization versus exercise therapy. Radiology 2002;222:25-36.

23. Gardner AW, Montgomery PS, Parker DE. Physical activity is a predictor of all-cause mortality in patients with intermittent claudication. J Vasc Surg 2008;47:117-22.

24. Rejeski WJ, Brawley LR, Ambrosius WT, Brubaker PH, Focht BC, Foy CG, et al. Older adults with chronic disease: benefits of group-mediated counseling in the promotion of physically active lifestyles. Health

Psychol 2003;22:414-23.

Chapter 9

Type D personality predicts mortality in peripheral arterial disease:

a pilot study

9

196 Chapter 9 - Personality and mortality in PAD

Aquarius AE, Smolderen KG, Hamming JF, De Vries J, Vriens PW, Denollet J. Type D personality predicts mortality in periph-eral arterial disease: a pilot study. Arch Surg 2009;144:728-23.

ABSTRACT

Objectives: Type D personality refers to the tendency to experience negative emotions and to inhibit self-expression in social interaction, and has been shown to be an independent predictor of mortality in cardiac disease. Information about the influence of psychological factors on prognosis is lacking in peripheral arterial disease (PAD). Therefore, we examined whether Type D personality predicted all-cause mortality in PAD.

Design: Follow-up study.

Setting: Vascular surgery department of a teaching hospital in Tilburg, The Netherlands.

Patients: A total of 184 patients with symptomatic PAD (Mean=64.8±9.8 years) were followed up for 4 years (interquartile range, 3.5-4.5).

Measures: Patients completed the DS14 measure of Type D at baseline. Information about all-cause mortality was obtained from patients’ medical files.

Results: During 4 years follow-up, 16 patients (8.7%) died. Adjusting for age and sex, Type D person-ality was predictive of mortality (P=.03). Ankle-brachial index (P=.05), age (P=.01), diabetes mellitus (P=.02), pulmonary disease (P=.09), and renal disease (P=.03) were also predictive of mortality. Multivariable logistic regression revealed that age, diabetes, and renal disease were independent predictors (ORs ranging from 1.1 to 2.3) of all-cause mortality. After adjustment for these clinical predictors, Type D patients still had a more than 3-fold increased risk of death (OR=3.5; 95%CI 1.1-11.1, P=.04).

Conclusions: Type D personality predicts an increased risk of all-cause mortality in PAD, above and beyond traditional risk factors. Further research is needed to confirm these findings, but this pilot study suggests that the assessment of Type D personality may be useful for detecting high-risk patients with PAD.


INTRODUCTION

Peripheral arterial disease (PAD), a manifestation of generalized atherosclerosis, is a relatively under-diagnosed and undertreated disease.1, 2 However, patients with PAD are at a significantly increased risk of major secondary events, such as stroke, fatal myocardial infarction, and cardiovascular mortal-ity, compared with patients who have other forms of vascular disease.3 In addition to this increased cardiovascular risk,4-6 these patients often experience impaired quality of life (QOL).7-9

Preliminary evidence suggests that personality traits such as hostility may also be associated with the severity and progression of atherosclerosis in patients with PAD.10, 11 Another potential individual risk factor in this context is the distressed personality type (Type D). Type D refers to the joint tendency to experience negative emotions and to inhibit self-expression in social interaction.12 The distressed personality type is independently associated with morbidity, mortality, and poor QOL in cardiac pa-tients.13, 14 Previous findings in PAD patients and healthy controls indicate that Type D personality is associated with impaired QOL, in addition to the impairment already related to having PAD.8 However, prospective research on the relationship between Type D personality and mortality PAD patients with PAD is still lacking. Therefore, the aim of the present follow-up study is to evaluate the impact of dis-ease severity, comorbidity, and Type D personality on mortality in patients with PAD.


METHODS

Patients

One hundred eighty four patients with PAD (mean±SD=64.8±9.8 years) were followed up for 4 years (interquartile range, 3.5-4.5 years) to study the factors associated with subsequent all-cause mortal-ity. These patients were selected from a sample that originally consisted of 241 patients with sus-pected intermittent claudication enrolled at the vascular outpatient clinic of the St. Elisabeth Hospital in Tilburg, The Netherlands between September 1, 2001 and March 31, 2004. Patients were asked to complete the personality questionnaire before PAD diagnosis was established by a vascular surgeon based on the clinical examination and the ankle-brachial index (ABI). Exclusion criteria were cogni-tive impairment, the presence of severe psychopathological (e.g., psychosis and suicidal ideation) or invalidating somatic comorbidities (e.g., cancer), participation in another study, and insufficient knowl-edge of the Dutch language. Patients who did not have an abnormal resting (<0.90) or significant post-exercise ABI decrease were also excluded (n=15). Six (2.5%) patients were excluded owing to cognitive impairment (n=2), recent myocardial infarction (n=1), visual problems (n=1), influenza (n=1), and participation in another study (n=1). Hereafter, 188 out of 220 eligible patients (85.5%) agreed to participate. Of the remaining patients, 3 (1.6%) patients did not complete the baseline measurement of the Type D personality questionnaire and they were excluded from the analyses. Patients that died from an unnatural cause were excluded from the present study (n=1). This study was designed to conform to the Helsinki Declaration and was approved by the local ethics committee of the St. Elisa-beth Hospital, Tilburg, The Netherlands. All the patients gave informed consent.

Data collection

Assessment of Type D personalityThe DS 14 was used to assess the presence of a Type D personality prior to PAD diagnosis.12 This 14-item questionnaire consists of two 7-item subscales, Negative Affectivity and Social Inhibition. The Negative Affectivity subscale evaluates the tendency to experience negative emotions (e.g., “I often find myself worrying about something”) and the Social Inhibition subscale assesses the tendency to inhibit self-expression in social interaction (e.g., “I would rather keep people at a distance”). Items are


rated on a 5-point Likert scale from 0 (false) to 4 (true). A cut-off ≥10 on both subscales is indicative of a Type D personality. The DS14 is internally consistent with Cronbach’s α-values of 0.88 and 0.86, and has good factorial validity, with factor loadings ranging from 0.62 to 0.82.12

Cardiovascular risk factors and comorbidityIn the present study, diabetes mellitus, smoking, hypertension, hyperlipidemia, and cardiac, carotid, renal, and pulmonary status were measured at baseline in all patients according to the Society for Vascular Surgery/North American chapter of the International Society for Cardiovascular Surgery (SVS/ISCVS) recommended standards.15 Information was obtained from patients’ medical files.

ABI measurementA handheld Doppler device (Imexlab 9000; Imex Medical Systems Inc, Golden, Colorado) was used to obtain systolic pressures in the right and left brachial and posterior tibial and dorsalis pedis arteries. The ABI was calculated by dividing the highest of the posterior tibial and dorsalis pedis ankle pres-sures in each leg by the highest brachial pressure. The ABI at rest was measured while the patient was lying in the supine position. The lowest resting leg ABI was used in the analysis.

End pointThe end point in this study was death from all causes. Deaths and causes of death were determined by the ward physician. When deaths were ascribed to cancer, there were always histologic results available that confirmed malignancies. Causes of death were, therefore, extracted from patients’ medical records. For patients who died at home, cause of death was verified by consultation with their general practitioner. The mean follow-up period was 4.0 years (interquartile range, 3.5-4.5 years).


Baseline characteristics were studied for the total sample and stratified by Type D personality. Chi-square tests were used for dichotomous variables and Student’s t-tests were applied for continuous variables. The risk for the association between Type D and mortality was evaluated using sex- and age- adjusted Cox proportional Hazard Regression analysis. Multivariable logistic regression analysis (enter model) was used to determine the independent predictors of all-cause mortality. The criteria for entry and removal were P≤0.10 and P>0.10, respectively. All statistical tests were 2-tailed. SPSS for Windows version 14.0.1. (SPSS Inc, Chicago, Illinois) was used for all analyses.


RESULTS

No patients were lost at follow-up. All deaths were attributable to natural causes, except for one (ho-micide). This participant was excluded from the analysis. Baseline characteristics of the total sample, and stratified by the presence of Type D personality are presented in Table 1. There were no signifi-cant differences in risk factors as a function of Type D personality.

Table 1 – Characteristics of the total sample (n=184), and stratified by Type D personality.

Results are presented as % (n) unless otherwise specified. Abbreviations: SD, standard deviation; ABI, ankle-brachial index.

Total sample Type D n=64

Non-Type D n=120

P value

Mean age (SD) 64.8 (9.8) 65.7 (9.4) 63.0 (10.1) .08Male sex 63.6% (117) 67.2% (43) 61.7% (74) .46Mean ABI (SD) 0.61 (0.15) 0.60 (0.15) 0.62 (0.14) .28Diabetes mellitus

Mild 9.2% (17) 14.1% (9) 6.7% (8)Moderate 9.8% (18) 9.4% (6) 10.0% (12)Severe 0.5% (1) 0% (0) 0.8% (1)

.36

Tobacco use Mild 27.7% (51) 23.4% (15) 30% (36) .40Moderate 35.9% (66) 43.8% (28) 31.7% (38)Severe 17.4% (32) 17.2% (11) 17.5% (21)

HypertensionMild 16.3% (30) 21.9% (14) 13.3% (16) .52Moderate 20.7% (38) 18.8% (12) 21.7% (26)Severe 8.2% (15) 7.8% (5) 8.3% (10)

HyperlipidemiaMild 16.8% (31) 23.4% (15) 12.5% (15) .11Moderate 23.9% (44) 23.4% (15) 24.2% (29)Severe 9.8% (18) 4.7% (3) 17.5% (16)

Cardiac status Mild 16.3% (30) 10.9% (7) 13.3% (21) .30Moderate 10.9% (20) 17.2% (11) 9.2% (11)Severe 1.1% (2) 1.6% (1) 0.8% (1)

Carotid status Mild 4.3% (8) 6.3% (4) 3.3% (4) .29Moderate 4.9% (9) 7.8% (5) 3.3% (4)Severe 1.1% (2) 0% (0) 1.7% (2)

Renal status Mild 1.6% (3) 1.6% (1) 1.7% (2) .66Moderate 1.6% (3) 3.1% (2) 0.8% (1)Severe 1.1% (2) 1.6% (1) 0.8% (1)

Pulmonary status Mild 2.2% (4) 1.6% (1) 2.5% (3) .84Moderate 5.4% (10) 6.3% (4) 5.0% (6)Severe 0.5% (1) 0% (0) 0.8% (1)


During 4 years follow-up, 16 patients (8.7%) died. Most deaths (7/16=44%) were due to cancer, and (6/16=38%) were due to cardiovascular death. The other three causes of death were pneumonia, acute pancreatitis, and terminal emphysema complicated by corticosteroid-induced diabetes.

Adjusting for age and sex, Type D personality was predictive of all-cause mortality (P=.03). Age- and sex-adjusted estimates are commonly presented in mortality analyses, and in observational studies, where groups could be biased by a differential in the sex ratio or average age.16 Survival percentages for Type D and non-Type D personality across time are presented in Figure 1. To test for differences between the resulting curves, age- and sex-adjusted Cox Proportional Hazard Regression analysis was used (Hazard Ratio [HR] Type D for all-cause mortality=3.2, 95% Confidence Interval [CI95%] 1.2-8.6, P=.02). Lower resting ABI (P=.05), older age (P=0.01), and the presence of diabetes mel-litus (P=.02), renal disease (P=.03), and pulmonary disease (P=.09) were also predictive of mortality (Table 2). Risk estimates of dichotomous variables and their 95% confidence intervals are presented in Figure 2.

Table 2 – Characteristics of participants according to survival status.

*Adjusting for age and sex. Abbreviations: SD, standard deviation; ABI, ankle-brachial index.

Survivors(n=168)

Non-survivors (n=16)

P value

Mean age (SD) 64.2 (9.8) 71.1 (7.7) <.01Male sex 63.1% (106) 68.8% (4) .65Mean ABI (SD) 0.61 (0.15) 0.54 (0.14) .05Diabetes mellitus

Mild 9.5% (16) 6.3% (1)Moderate 7.7% (13) 31.3% (5)Severe 0.6% (1) 0% (0)

.03

Tobacco use Mild 26.8% (45) 37.5% (6)Moderate 35.1% (59) 43.8% (7)Severe 18.5% (31) 6.3% (1)

.47

HypertensionMild 15.5% (26) 25.0% (4)Moderate 20.2% (34) 25.0% (4)Severe 8.3% (14) 6.3% (1)

.70

HyperlipidemiaMild 16.5% (28) 12.5% (2)Moderate 23.5% (40) 25.0% (4)Severe 10.7% (18) 6.3% (1)

.89

Cardiac status Mild 14.9% (25) 18.8% (3)Moderate 10.7% (18) 25.0% (4)Severe 1.2% (2) 0% (0)

.33

Carotid status Mild 4.8% (8) 0% (0)Moderate 4.8% (8) 6.3% (1)Severe 1.2% (2) 0% (0)

.79

Renal status Mild 1.2% (2) 6.3% (1)Moderate 1.2% (2) 6.3% (1)Severe 0.6% (1) 6.3% (1)

.03

Pulmonary status Mild 2.4% (4) 0% (0)Moderate 4.2% (7) 18.8% (3)Severe 0.6% (1) 0% (0)

.09

Type D personality 32.7% (55) 56.3% (9) .03*


Multivariable logistic regression revealed that age, diabetes, and renal disease were independent clinical predictors (Odds Ratios ranging from 1.1 to 2.3) of all-cause mortality. After adjustment for these clinical predictors, Type D patients still had a more than 3-fold risk of death (P=.04) (Table 3).

Table 3 – Independent predictors of all-cause mortality in patients with PAD.

Abbreviations: ABI, ankle-brachial index; CI, confidence interval; OR, odds ratio.

Predictor OR [95% CI] P value

Type D personality 3.5 [1.1-11.1] 0.04

Age 1.1 [1.0-1.2] 0.02

Male sex 2.3 [0.6-8.6] 0.20

ABI 1.0 [0.9-1.0] 0.34

Diabetes 2.3 [1.2-4.6] 0.02

Renal disease 2.3 [1.0-5.3] 0.04

Pulmonary disease 1.4 [0.7-3.2] 0.37

Figure 1 – Cumulative survival (%) over time stratified by Type D personality.

Years543210

Surv

ival

(%)

100

98

96

94

92

90

88

Page 1

Figure 2 – Univariate odds ratios (OR) and 95% confidence intervals (CI) of dichotomous predictors of all-cause mortality. Type D adjusted for age and sex.

0.1 1 10

Pulmonary Disease

Male Sex

Renal Disease

Diabetes Mellitus

Type D

Alive Death

3.3 [1.1-10.0]

2.0 [1.1-3.6]

2.5 [1.2-5.4]

1.9 [0.9-3.7]

1.3 [0.4-3.9]

OR [95% CI]

Alive Death

Type D

Diabetes mellitus

Renal disease

Male sex

Pulmonary disease

Non-Type D

Type D


DISCUSSION

In this pilot study, we found that patients with a Type D personality had a more than 3-fold risk of dying during follow-up. To our knowledge, no other psychological trait was ever studied in relation to the risk of mortality in PAD. Scarce evidence exists that personality traits such as hostility and anger are associated with PAD and atherosclerotic progression as measured by the ABI.10, 11, 17 Traditional risk factors such as age, diabetes mellitus, and renal disease were also independently associated with all-cause mortality; these findings are in line with recent literature.18 The ABI was not an independent predictor of mortality, but the ABI at baseline was relatively high in this sample, and previous research shows that higher ABIs have less specificity for the prediction of survival.19

Although few deaths can be directly attributed to PAD, patients with PAD have generalized athero-sclerosis and multiple risk factors that predispose them to an increased risk of fatal cardiovascu-lar events.20 Moreover, PAD is also a powerful predictor of all-cause mortality;19, 21, 22 cancer-related deaths, such as lung cancer, are especially more prevalent in PAD.23 In the present study, most death causes were cancer-related; pancreas and lung carcinoma were especially common. Cardiovascular deaths accounted for 38% of the non-survivors. Life-style factors that are involved in the incidence of cardiovascular disease and cancer, such as smoking and obesity, may explain to a large extent the strong link between PAD and all-cause mortality.24

New in the present study is the finding that a psychological trait was an independent predictor of all-cause mortality in patients diagnosed as having intermittent claudication. Psychological factors, such as chronic psychological distress, depression, and social avoidance, are extensively studied in other atherosclerotic diseases such as coronary artery disease25-28 and cerebrovascular disease.29 Chronic emotional stress and the inhibition of emotional and behavioral expression can be largely attributed to broad personality traits that refer to stable individual differences in emotions and behavior.30 More-over, the distressed personality type or Type D personality is a strong predictor of impaired QOL and adverse prognosis in cardiac patients.8, 13, 31

There are a variety of physiological and behavioral pathways that may mediate the relationship be-tween Type D personality and adverse health outcomes in cardiovascular patients. Type D personal-ity has been associated with increased immune activation in patients with chronic heart failure, as indicated by higher circulating plasma levels of the pro-inflammatory cytokine tumor necrosis factor-α


(TNF-α) and its soluble receptors sTNFR1s and TNFR2.32, 33 Type D personality has also been as-sociated with disruption of the hypothalamic-pituitary-adrenocortical axis and increased cortisol reac-tivity in experimental34 and clinical research.35 Inadequate self-management of chronic disease is a potential behavioral mechanism that may explain the relation between Type D and poor prognosis in cardiovascular disease.36

Overall, attention for psychological factors, and personality in particular, will become increasingly important given the continuing epidemics of chronic cardiovascular disease, obesity, and diabetes mellitus.37, 38 In addition to their adverse effect on cardiovascular prognosis, personality and chronic stress act as barriers to improvement of life style factors in cardiovascular patients39 and need to be addressed in clinical practice.40 Although patients with PAD typically have multiple cardiovascular risk factors that put them at high risk for fatal cardiovascular events,1 research shows patients with PAD receive suboptimal secondary prevention.41 In addition to improving awareness of the traditional medical risk factors in PAD, attention should be given to psychological factors that may have an ad-verse effect on the clinical course of PAD.

These findings, however, need to be interpreted with caution because there were only a limited num-ber of events in this pilot study. Nonetheless, the Type D effect was discerned in the small sample. After controlling for important clinical risk factors, such as ABI, diabetes, and renal disease, the pres-ence of the Type D effect suggests that personality may be associated with adverse prognosis in PAD. By analogy, initial observations on Type D personality and mortality in a small sample of coronary patients,42 were confirmed afterward in a larger patient sample.43 Therefore, confirmatory research on the distressed personality and mortality in patients with PAD is warranted in multiple centers that are involved in PAD management. Although age tended to be higher in Type D patients (not statisti-cally significant), controlling for age in multivariable analysis did not explain the association between personality and mortality. On the contrary, it suppressed the irrelevant variance in Type D personality, and there are no indications that Type D is associated with older age.13, 14, 31, 41 Finally, the standard assessment of personality before diagnosis of PAD and the prospective design are major strengths of this study.

Hence, in light of the challenge of optimizing risk management in PAD, a personality-based approach may be useful. Previous research has already shown that Type D personality predicts prognosis in cardiac patients13, 14, 31, 41 as well as impaired QOL.8, 25 This study suggests that attention for personality variables may also improve the detection of high-risk patients with PAD.


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22. Lange S, Trampisch HJ, Haberl R, Darius H, Pittrow D, Schuster A, et al. Excess 1-year cardiovascular risk in elderly primary care patients with a low ankle-brachial index (ABI) and high homocysteine level. Atherosclerosis 2005;178:351-7.

23. Fiotti N, Altamura N, Cappelli C, Schillan M, Guarnieri G, Giansante C. Long term prognosis in patients with peripheral arterial disease treated with antiplatelet agents. Eur J Vasc Endovasc Surg 2003;26:374-80.

24. Eyre H, Kahn R, Robertson RM, Clark NG, Doyle C, Hong Y, et al. Preventing cancer, cardiovascular disease, and diabetes: a common agenda for the American Cancer Society, the American Diabetes As-sociation, and the American Heart Association. Circulation 2004;109:3244-55.

25. Pedersen SS, Denollet J. Type D personality, cardiac events, and impaired quality of life: a review. Eur J Cardiovasc Prev Rehabil 2003;10:241-8.

26. Berry JD, Lloyd-Jones DM, Garside DB, Wang R, Greenland P. Social avoidance and long-term risk for cardiovascular disease death in healthy men: the Western Electric Study. Ann Epidemiol 2007;17:591-96.

27. Welin C, Lappas, G, Wilhelmsen L. Independent importance of psychosocial factors for prognosis after myocardial infarction. J Intern Med 2000;247:629-39.

28. Milani RV, Lavie CJ. Impact of cardiac rehabilitation on depression and its associated mortality. Am J Med 2007;120:799-806.

29. Carney RM, Freedland KE. Psychological distress as a risk factor for stroke-related mortality. Stroke 2002;33:5-6.


30. Denollet J. Personality and coronary heart disease: the Type D scale-16 (DS16). Ann Behav Med 1998;20:209-15.

31. Denollet J, Vaes J, Brutsaert DL. Inadequate response to treatment in coronary heart disease: ad-verse effects of Type D personality and younger age on 5-year prognosis and quality of life. Circulation 2000;102:630-5.

32. Denollet J, Conraads VM, Brutsaert DL, De Clerck LS, Stevens WJ, vrints CJ. Cytokines and immune activation in systolic heart failure: the role of Type D personality. Brain Behav Immun 2003;17:304-9.

33. Conraads VM, Denollet J, De Clerck LS, Stevens WJ, Bridts C, Vrints. Type D personality is associated with increased levels of tumour necrosis factor (TNF)-alpha and TNF-alpha receptors in chronic heart failure. Int J Cardiol 2006;113:34-8.

34. Habra ME, Linden W, Anderson JC, Weinberg J. Type D personality is related to cardiovascular and neu-roendocrine reactivity to acute stress. J Psychosom Res 2003;55:235-45.

35. Whitehead DL, Perkins-Porras L, Strike PC, Magid K, Steptoe A. Cortisol awakening response is elevated in acute coronary syndrome patients with Type D personality. J Psychosom Res 2007;62:419-25.

36. Schiffer AA, Denollet J, Widdershoven JW, Hendriks EH, Smith OR. Failure to Consult for Symptoms of Heart Failure in Patients with a Type D Personality. Heart 2007;93:814-8.

37. McDermott MM. The international pandemic of chronic cardiovascular disease. JAMA 2007;297:1253-5.38. Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks JS, Koplan JP. The continuing epidemics of obesity

and diabetes in the United States. JAMA 2001;286:1195-200.39. De Backer G, Ambrosioni E, Borch-Johnsen K, Brotons C, Cifkova R, Dallongeville J, et al. European

guidelines on cardiovascular disease prevention in clinical practice: third joint task force of European and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of eight societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2003;10:S1-S10.

40. Albus C, Jordan J, Herrmann-Lingen C. Screening for psychosocial risk factors in patients with coronary heart disease-recommendations for clinical practice. Eur J Cardiovasc Prev Rehabil 2004;11:75-9.

41. Wilson AM, Bachoo P, Mackay IA, Cassar K, Brittenden J. Completing the Audit Cycle: Comparison of Cardiac Risk Factor Management in Patients with Intermittent Claudication in Two Time Periods. Eur J Vasc Endovasc Surg 2007;33:715-16.

42. Denollet J, Sys SU, Brutsaert DL. Personality and mortality after myocardial infarction. Psychosom Med 1995;57:582-91.

43. Denollet J, Sys SU, Stroobant N, Rombouts H, Gillebert TC, Brutsaert DL. Personality as independent

predictor of long-term mortality in patients with coronary heart disease. Lancet 1996;347:417-21.

Holding up a mirror: refl ections of patient-centered research in cardiac disease

Part III

Chapter 10

Impact of peripheral arterial disease on health status: a comparison

with chronic heart failure

10

216 Chapter 10 – Health status PAD and CHF

Smolderen KG, Pelle AJ, Kupper N, Mols F, Denollet J. Impact of peripheral arterial disease on health status: a comparison with chronic heart failure. J Vasc Surg. In Press.

ABSTRACT

Objective: To further document the experienced burden in patients with peripheral arterial disease (PAD), we compared the health status of patients with PAD and chronic heart failure (CHF). As a secondary aim, we studied clinical and socio-demographic correlates of health status in both condi-tions.

Design: A cross-sectional observational study.

Setting: Four outpatient clinics in the Southern part of The Netherlands.

Subjects: Ambulatory patients, consisting of 346 PAD and 188 CHF patients.

Main outcome measures: All patients completed the Short-Form 12 to assess their physical and mental health status.

Methods: Information about socio-demographic, clinical risk factors, and disease severity indices was obtained from patients’ medical records. Propensity methodology was applied to enhance com-parability between both medical conditions.

Results: Type of medical condition explained differences in health status (F=33.1, P<.0001, Effect Size=0.27). Impaired physical health status was more often reported in PAD patients (48.4%) com-pared with CHF patients (17.4%, OR=4.4, 95%CI 2.3-8.8, P<.0001); impaired mental health sta-tus was more noted in CHF patients (43.5% vs. 22.0%, OR=1.7, 95%CI 1.2-2.6, P=.002). In PAD, younger age (P=.002), low education (P=.02), cardiac history (P=.02), diabetes mellitus (P=.03), and a lower ankle brachial index (P=.003) were associated with worse physical health status; younger age (P=.01) and living without partner (P=.01) were associated with lower mental health status scores. In CHF, patients with comorbid diabetes mellitus (P<.001) and females (P=.001) reported worse physi-cal health, whereas no clinical or socio-demographics were associated with mental health status.


Conclusions: By contrasting PAD patients’ health status with another chronic disabling condition, the impact of PAD on patients’ physical health status became evident; whereas mental health status was more affected in CHF, patients with PAD reported a greater physical burden as compared with CHF patients. Especially PAD patients who were younger, lower-educated, without a partner or had a cardiac history, reported a higher disease burden. Clinicians need to be aware of these differences in order to develop tailor-made disease management programs for different groups of cardiovascular patients.


INTRODUCTION

The main challenges in peripheral arterial disease (PAD) refer to the prevention of cardiovascular events and the decrease of patients’ disease burden.1 PAD is often a precursor of more advanced cardiovascular disease such as coronary and cerebrovascular disease.1 Recent findings indicate that PAD patients have worse long-term outcomes compared with coronary artery disease patients.2, 3 De-spite these findings, deficiencies in awareness regarding PAD risk management and undertreatment of atherosclerotic risk factors still exist and may contribute to high rates of cardiovascular morbidity and mortality.2, 4

In addition to their increased cardiovascular risk, PAD patients are known to experience impaired health status due to lower-limb symptoms, sometimes even after receiving a technically success-ful endovascular revascularization.5, 6 In an era where patient-centered outcomes are becoming an important standard in evaluating treatment options,7, 8 information about subjective health status and its determinants in PAD is relatively under documented as compared with the body of research on health status that is available in other cardiovascular disease groups. This information will be nec-essary when designing tailor-made disease management programs for PAD patients, as programs developed in cardiac patients are not readily implementable in PAD patients.9

To estimate the burden associated with PAD, the first goal of this multi-center study was to compare the health status of patients with PAD and chronic heart failure (CHF).10 CHF has deleterious effects on prognosis and health status,11 and improving health status in CHF has been emphasized as an important treatment goal on its own.8 The second goal was to identify clinical risk factors associated with impaired health status in both patient groups.


METHODS

Patients

Patients with newly diagnosed symptomatic PAD were consecutively included at the vascular outpa-tient clinics of the St. Elisabeth Hospital and TweeSteden Hospital in Tilburg, The Netherlands (March 1, 2006-May 31, 2008). CHF patients visiting the cardiology outpatient clinic of the St. Elisabeth Hospital, Tilburg, the Amphia Hospital, Breda, or the Zorgsaam Hospital, Terneuzen, The Netherlands (June 1, 2006-May 31, 2008) were consecutively included for this study. All hospitals were public teaching hospitals in the Southern part of The Netherlands.

PAD inclusion criteria were defined as having symptomatic PAD and an abnormal resting Ankle–Brachial Index (ABI) (≤0.90) or an abnormal post-exercise ABI (ABI decrease of 15 % after exercise).1 Stable CHF patients were included if they met the following criteria: systolic heart failure; Left Ven-tricle Ejection Fraction (LVEF) <40%; stable on oral medication during the past month; no medical ad-missions during the past month; New York Heart Association-functional class (NYHA) I-III. Exclusion criteria were cognitive impairment; chronic severe psychiatric condition (e.g., psychosis) or invalidat-ing or life-threatening conditions that prevented participation (e.g., cancer); insufficient knowledge of the Dutch language or illiteracy. In addition, CHF patients aged >80 years were excluded (in order to avoid too much response burden in this older age group), as well as non-stable CHF patients that experienced an acute myocardial infarction one month prior to inclusion (in order to avoid unwanted confounding effects of the acute event). PAD patients were excluded if they had ischemic rest pain, tissue loss, ulcers or gangrene. Patients with normal ABIs or patients with non-compressible ankle pressures were also ineligible for inclusion. Other reasons for exclusion included emigration or par-ticipation in another study.

PAD patients were asked to participate in the study by their treating vascular surgeon during their visit at the outpatient clinic, following a diagnostic work-up that confirmed the presence of PAD. CHF patients were approached for participation by their treating cardiologist or heart failure nurse during their outpatient visit to the cardiology department. All patients received a set of self-administered questionnaires which they could complete at home and return by mail.


The studies were approved by the local ethics committees of the participating hospitals and con-ducted conform to the Helsinki Declaration. All participants provided written informed consent.

Measures

Health status The Dutch Short Form12 (SF-12) was administered to assess health status.12, 13 This generic in-strument measures overall physical and mental health status indicated by the Physical Component Summary and the Mental Component Summary scores.14 According to standard scoring procedures, all scales were standardized to the general Dutch population norms (range between 0-100, mean score=50, SD=10), with higher scores indicating better functioning.15 The SF-12 has been demon-strated to be a valid and reliable instrument.12

Disease severityIn PAD patients, a handheld Doppler ultrasonic instrument with an 8-MHz vascular probe (Imexlab 9000; Imex Medical Systems Inc, Golden Colorado) was used by trained technicians to obtain systolic blood pressure readings in the right and left brachial arteries, right and left dorsalis pedis arteries, and right and left posterior tibial arteries. The ABI at rest and after walking on a treadmill was registered according to the latest TASC guidelines.1 Of the ABI values obtained in each leg, the lower resting ABI was used in all analyses. Duplex ultrasound scanning was employed to determine the localization of the lesions in the PAD patients. In CHF patients, information on NYHA class was obtained from the medical file; LVEF was collected by means of echocardiography and was used as an index of disease severity.

Socio-demographics and clinical variables Information on socio-demographics was self-reported by the participants and included sex, age, edu-cational level (low education indicated patients who did not complete high school), and partner status. Clinical variables for both PAD and CHF patients were obtained from the patients’ medical records and included cardiac history prior to the referral event (previous myocardial infarction, coronary artery bypass surgery, percutaneous coronary intervention), history of stroke or transient ischemic attack, current smoking, comorbidities (i.e., diabetes mellitus, hypercholesterolemia, hypertension, renal failure, and chronic obstructive pulmonary disease, history of PAD and CHF) and prescribed cardio-


protective medications (i.e., aspirin, angiotensin-converting enzyme inhibitors, β-Blockers, calcium channel blockers, diuretics, nitrates, statins, and anticoagulants).


There were two main objectives in this study. We first compared the health status of patients with PAD and patients with CHF. For this purpose, patients were matched according to their clinical risk profile, in order to enhance comparability of PAD and CHF patients. Next, we evaluated a series of clinical and socio-demographic correlates of health status in both medical conditions. To optimize power, we used the whole cohort for the second purpose.

Matching PAD and CHF patients by clinical risk profileBaseline variables were examined for the total cohort and stratified by medical condition. Discrete variables were compared using Chi-square tests and continuous variables with the Student t-test for independent variables as appropriate. To enhance comparability between both medical conditions, propensity score methodology was applied using multivariable logistic regression analysis containing all baseline variables.16 A propensity score was then calculated for each patient, providing an estimate of the propensity toward belonging to either the PAD or the CHF group. Subsequently, PAD patients were matched with CHF patients based on their closest propensity score using a precision of three decimal points. After matching, baseline variables were examined again stratified by medical condi-tion, to ensure that both groups had comparable clinical risk profiles.

Distribution of health status scores and clinical and prevalence of impaired health status To examine differences in levels of health status in PAD and CHF patients, multiple analyses of variance (MANOVA and ANOVA) were performed in the matched cohort (between-subjects design). Partial Eta Squared was calculated as an index of Effect Size.17 To facilitate clinical interpretability, the physical and mental health scores were dichotomized, including the lowest scoring 33%18 in the impaired health status group. Chi square tests were used to compare prevalence of impaired physical and mental health in PAD vs. CHF.


Clinical and socio-demographic correlates of health statusFor each patient subgroup separately, multivariable linear regression analyses were conducted to determine the correlates of health status. When determining the association between important cor-relates and health status, the following covariates were included: age, sex, current smoking, hyper-cholesterolemia, hypertension, and diabetes mellitus as these correlates are identified as major risk factors in cardiovascular disease.19, 20 In addition, all multivariable analyses were adjusted for cardiac history, disease severity (i.e., in PAD we controlled for ABI, and in CHF for LVEF), history of PAD or CHF, and socio-demographic variables (having no partner, low education). Analyses were replicated excluding those patients with overlapping diagnoses (n=9 with a history of PAD and n=4 with a his-tory of CHF) as sensitivity analyses. Results of both sets of analyses were similar, and therefore, the former described analyses - including the extra patients - will be reported here.

All statistical tests were two-tailed, and P values <.05 indicated statistical significance. Analyses were performed using SPSS 17.0 for Windows (SPSS inc., Chicago, Illinois).


RESULTS

Matching PAD and CHF patients by clinical risk profile

The total sample consisted of 534 patients, of which 346 had PAD diagnosis and 188 patients had CHF diagnosis (Figure 1). The mean age of the total sample was 66 years and 29% was female. Table 1 provides information about baseline characteristics before and after matching. Because the clinical risk profile differed for many aspects in both medical conditions (Table 1, left), patients were matched based on their closest propensity score. We were able to match 104 PAD patients with 104 CHF patients, leaving 208 patients for further statistical analysis. These 208 patients were used in the health status comparison analyses. We used the full cohort when evaluating clinical and socio-demographic correlates of health status in each medical condition (n=346 for PAD and n=188 for CHF), in order to optimize power.


Figure 1 – Overview of patients included in this study.


After matching, there were no differences on baseline variables between PAD and CHF patients (Ta-ble 1, right). CHF patients that could not be matched were more likely to on a beta blocker (81.0% vs. 58.7%) and to be older (70.2 vs. 67.1 years) as compared with matched CHF patients. Non-matched PAD patients were lower educated (63.6% vs. 32.7%), were less likely to have a history of myocardial infarction, to take ACE inhibitors (31.0% vs. 52.9%), diuretics (23.9% vs. 48.1%), but were more on aspirin (71.8% vs. 49.0%) and were more likely to be a smoker (62.0% vs. 34.6%) as compared with matched PAD patients.


Tabl

e 1 –

Base

line c

hara

cter

istics

for t

he to

tal s

ampl

e and

stra

tified

by m

edica

l con

ditio

n.*

Befo

re m

atch

ing

Afte

r mat

chin

g†

Char

acte

ristic

To

tal

Sam

ple

(n=5

34)

PAD

(n=3

46)

CHF

(n=1

88)

P va

lue

Tota

l sa

mpl

e(n

=208

)

PAD

(n=1

04)

CHF

(n=1

04)

P va

lue

Socio

-dem

ogra

phics

Me

an ag

e (SD

), ye

ars

65.7

(9.4)

65

.1 (9

.7)

66.9

(8.9)

.04

67.2

(9.2)

67

.3 (9

.5)

67.1

(8.9)

.79

Fe

male

Sex

29.2

(156

) 33

.2 (1

15)

21.8

(41)

.01

23.6

(49)

26

.0 (2

2)

21.2

(27)

.41

No

partn

er

23.4

(125

) 24

.3 (8

4)

21.8

(41)

.52

25

.0 (5

2)

25.0

(26)

25

.0 (2

6)

1.00

Low

educ

ation

30

.6 (1

62)

28.4

(98)

34

.8 (6

4)

.13

32.7

(68)

32

.7 (3

0)

32.7

(30)

1.0

0 Me

dical

histor

y

Pr

eviou

s myo

card

ial in

farcti

on

33.1

(176

) 17

.3 (6

0)

62.4

(116

) <.0

001

43.8

(91)

42

.3 (4

4)

45.2

(47)

.68

Pr

eviou

s cor

onar

y arte

ry by

pass

surg

ery

16.9

(90)

11

.0 (3

8)

28.0

(52)

<.0

001

18.8

(39)

17

.3 (1

8)

20.2

(21)

.59

Prev

ious P

CI

13.7

(73)

8.2

(28)

24

.2 (4

5)

<.000

117

.8 (3

7)

16.3

(17)

19

.2 (2

0)

.59

Histo

ry of

strok

e or t

rans

ient

ische

mic a

ttack

15

.1 (8

0)

15.4

(53)

14

.5 (2

7)

.79

13.9

(29)

14

.4 (1

5)

13.5

(14)

.84

Diab

etes m

ellitu

s 24

.8 (1

32)

22.5

(78)

29

.0 (5

4)

.10

30.3

(63)

32

.7 (3

4)

27.9

(29)

.45

Hy

perch

oleste

rolem

ia 67

.0 (3

55)

68.6

(236

) 64

.0 (1

19)

.28

65.4

(136

) 63

.5 (6

6)

67.3

(70)

.56

Hy

perte

nsion

54

.0 (2

68)

59.9

(206

) 43

.0 (8

0)

<.000

155

.8 (1

16)

57.7

(60)

53

.8 (5

6)

.58

Curre

nt sm

oking

42

.0 (2

24)

52.3

(181

) 23

.0 (4

3)

<.000

130

.8 (6

4)

34.6

(36)

26

.9 (2

8)

.23

Rena

l failu

re

7.3 (3

9)

9.6 (3

3)

3.2 (6

) .01

5.8 (1

2)

7.7 (8

) 3.8

(4)

.23

Chro

nic ob

struc

tive p

ulmon

ary

disea

se

15.8

(84)

13

.3 (4

6)

20.4

(38)

.03

22.1

(46)

21

.2 (2

2)

23.1

(24)

.74

Mean

BMI

(SD)

27

.1 (4

.6)

26.6

(4.7)

27

.9 (4

.4)

.0127

.9 (5

.1)

27.9

(5.8)

27

.9 (4

.3)

.14

Medic

ation

As

pirin

59.8(

319)

74

.6 (2

58)

32.6

(61.0

) <.0

001

47.6

(99)

49

.0 (5

1)

46.2

(48)

.68

Angio

tensin

-conv

ertin

g en

zyme

inhib

itors

47.5

(253

) 40

.8 (1

41)

59.9

(112

) <.0

001

54.8

(114

) 52

.9 (5

5)

56.7

(59)

.58

β-Bl

ocke

rs 49

.2 (2

62)

39.6

(137

) 66

.8 (1

25)

<.000

158

.2 (1

21)

57.7

(60)

58

.7 (6

1)

.89

Calci

um ch

anne

l bloc

kers

20.3

(108

) 22

.5 (7

8)

16.0

(30)

.08

22

.1 (4

6)

23.1

(24)

21

.2 (2

2)

.74

Diur

etics

38

.9 (2

06)

24.8

(85)

64

.7 (1

21)

<.000

154

.8 (1

14)

48.1

(50)

61

.5 (6

4)

.06

Nitra

tes

17.9

(95)

7.6

(26)

36

.9 (6

9)

<.000

124

.0 (5

0)

21.2

(22)

26

.9 (2

8)

.33

Stati

ns

75.8

(404

) 79

.8(27

6)

68.4

(128

) .01

65.9

(137

) 64

.4 (6

7)

67.3

(70)

.66

An

ticoa

gulan

ts 34

.9 (1

86)

19.9

(69)

62

.6 (1

17)

<.000

178

(37.5

) 32

.7 (3

4)

42.3

(44)

.15


*Res

ults

are

pres

ente

d as

% (n

), un

less

othe

rwise

sta

ted.

Abb

revia

tions

: PAD

, per

ipher

al ar

teria

l dise

ase;

CHF

, chr

onic

hear

t fail

ure;

PCI

, per

cuta

neou

s co

rona

ry

inter

vent

ion; B

MI,

body

mas

s ind

ex. †

Mat

ched

on

age,

gen

der,

prev

ious M

I, pr

eviou

s CAB

G, p

revio

us P

CI, h

yper

tens

ion, c

urre

nt sm

oking

, ren

al fa

ilure

, COP

D, u

se

of a

spirin

, ACE

-inhib

itors

, β-B

locke

rs, d

iuret

ics, n

itrat

es, s

tatin

s and

ant

icoag

ulant

s. Si

gnific

ant r

esult

s are

pre

sent

ed in

bold

face

.

Befo

re m

atch

ing

Afte

r mat

chin

g†

Char

acte

ristic

To

tal

Sam

ple

(n=5

34)

PAD

(n=3

46)

CHF

(n=1

88)

P va

lue

Tota

l sa

mpl

e(n

=208

)

PAD

(n=1

04)

CHF

(n=1

04)

P va

lue

Socio

-dem

ogra

phics

Me

an ag

e (SD

), ye

ars

65.7

(9.4)

65

.1 (9

.7)

66.9

(8.9)

.04

67.2

(9.2)

67

.3 (9

.5)

67.1

(8.9)

.79

Fe

male

Sex

29.2

(156

) 33

.2 (1

15)

21.8

(41)

.01

23.6

(49)

26

.0 (2

2)

21.2

(27)

.41

No

partn

er

23.4

(125

) 24

.3 (8

4)

21.8

(41)

.52

25

.0 (5

2)

25.0

(26)

25

.0 (2

6)

1.00

Low

educ

ation

30

.6 (1

62)

28.4

(98)

34

.8 (6

4)

.13

32.7

(68)

32

.7 (3

0)

32.7

(30)

1.0

0 Me

dical

histor

y

Pr

eviou

s myo

card

ial in

farcti

on

33.1

(176

) 17

.3 (6

0)

62.4

(116

) <.0

001

43.8

(91)

42

.3 (4

4)

45.2

(47)

.68

Pr

eviou

s cor

onar

y arte

ry by

pass

surg

ery

16.9

(90)

11

.0 (3

8)

28.0

(52)

<.0

001

18.8

(39)

17

.3 (1

8)

20.2

(21)

.59

Prev

ious P

CI

13.7

(73)

8.2

(28)

24

.2 (4

5)

<.000

117

.8 (3

7)

16.3

(17)

19

.2 (2

0)

.59

Histo

ry of

strok

e or t

rans

ient

ische

mic a

ttack

15

.1 (8

0)

15.4

(53)

14

.5 (2

7)

.79

13.9

(29)

14

.4 (1

5)

13.5

(14)

.84

Diab

etes m

ellitu

s 24

.8 (1

32)

22.5

(78)

29

.0 (5

4)

.10

30.3

(63)

32

.7 (3

4)

27.9

(29)

.45

Hy

perch

oleste

rolem

ia 67

.0 (3

55)

68.6

(236

) 64

.0 (1

19)

.28

65.4

(136

) 63

.5 (6

6)

67.3

(70)

.56

Hy

perte

nsion

54

.0 (2

68)

59.9

(206

) 43

.0 (8

0)

<.000

155

.8 (1

16)

57.7

(60)

53

.8 (5

6)

.58

Curre

nt sm

oking

42

.0 (2

24)

52.3

(181

) 23

.0 (4

3)

<.000

130

.8 (6

4)

34.6

(36)

26

.9 (2

8)

.23

Rena

l failu

re

7.3 (3

9)

9.6 (3

3)

3.2 (6

) .01

5.8 (1

2)

7.7 (8

) 3.8

(4)

.23

Chro

nic ob

struc

tive p

ulmon

ary

disea

se

15.8

(84)

13

.3 (4

6)

20.4

(38)

.03

22.1

(46)

21

.2 (2

2)

23.1

(24)

.74

Mean

BMI

(SD)

27

.1 (4

.6)

26.6

(4.7)

27

.9 (4

.4)

.0127

.9 (5

.1)

27.9

(5.8)

27

.9 (4

.3)

.14

Medic

ation

As

pirin

59.8(

319)

74

.6 (2

58)

32.6

(61.0

) <.0

001

47.6

(99)

49

.0 (5

1)

46.2

(48)

.68

Angio

tensin

-conv

ertin

g en

zyme

inhib

itors

47.5

(253

) 40

.8 (1

41)

59.9

(112

) <.0

001

54.8

(114

) 52

.9 (5

5)

56.7

(59)

.58

β-Bl

ocke

rs 49

.2 (2

62)

39.6

(137

) 66

.8 (1

25)

<.000

158

.2 (1

21)

57.7

(60)

58

.7 (6

1)

.89

Calci

um ch

anne

l bloc

kers

20.3

(108

) 22

.5 (7

8)

16.0

(30)

.08

22

.1 (4

6)

23.1

(24)

21

.2 (2

2)

.74

Diur

etics

38

.9 (2

06)

24.8

(85)

64

.7 (1

21)

<.000

154

.8 (1

14)

48.1

(50)

61

.5 (6

4)

.06

Nitra

tes

17.9

(95)

7.6

(26)

36

.9 (6

9)

<.000

124

.0 (5

0)

21.2

(22)

26

.9 (2

8)

.33

Stati

ns

75.8

(404

) 79

.8(27

6)

68.4

(128

) .01

65.9

(137

) 64

.4 (6

7)

67.3

(70)

.66

An

ticoa

gulan

ts 34

.9 (1

86)

19.9

(69)

62

.6 (1

17)

<.000

178

(37.5

) 32

.7 (3

4)

42.3

(44)

.15


In the matched cohort, the mean ABI for PAD patients was 0.65 (SD 0.21), and 4 (3.8%) patients had a history of CHF. A total of 55.8% (58) presented with iliac disease, 71.2% (74) with femoral disease, 69.2% (72) with popliteal disease, 43.3% (45) presented with other below knee lesions, and 33.7% (35) patients presented with bilateral disease. A history of previous peripheral revascularization was present in 17.3% (18) of PAD patients. Mean LVEF for CHF patients was 33.7% (SD=7.3), history of PAD was present in 9 (8.7%) CHF patients. The majority of CHF patients had early stage disease; a total of 49 (47.1%) had NYHA class I, 44 (42.3%) was classified as NYHA class II, and 3 (10.6%) had NYHA class III.

Distribution of health status scores and clinical and prevalence of impaired health status

The distribution of physical and mental health scores (Mean, Median, 25th to 75th percentiles and range), stratified by medical condition are presented in Figure 2. PAD patients had lower physical health scores as compared with CHF patients and patients with CHF had lower mental health scores as compared with PAD patients. Statistical significance of differences in health status scores were analyzed using univariable analyses of variance (MANOVA and ANOVA). Type of medical condi-tion explained differences in health status (physical and mental health) (F=33.1, P<.0001, Effect Size=0.27). On sub domain level, type of medical condition was also significantly associated with differences in mean health status scores (38.4±10.2 for PAD vs. 43.9±7.1 for CHF, Fphysical health=17.7, P<.0001, Effect Size=0.09 and 47.0±11.1 for PAD vs. 42.2±6.8 for CHF, Fmental health=12.4, P=.001, Effect Size=0.06). According to generally accepted criteria,17 these Effect Sizes can be interpreted as small to moderate Effect Sizes.


Figure 2 – Distribution of health status scores in PAD and CHF. Mean (closed circle), median (horizontal line), 25th to 75th percentile (box), and range (whiskers) of summary component scale scores by medical condition. Abbreviations: PAD, peripheral arterial disease; CHF, chronic heart fail-ure.

P<.0001

PAD CHF0

20

40

60

80

100

Ph

ysic

al h

ealt

h

P=.001

PAD CHF0

20

40

60

80

100

Men

tal h

ealt

h

Figure 3 – Prevalence (%) of Impaired Health Status (Lowest Tertile) Stratified

by Medical Condition. Abbreviations: PAD, peripheral arterial disease; CHF, chronic

heart failure. *PAD coded as 1, and CHF coded as 0. † CHF coded as 1, and PAD

coded as 0.


Figure 3 presents the prevalence of impaired physical and mental health status by medical condition. PAD patients had an increased risk of impaired physical health status as compared with CHF patients (48.4% vs. 17.4%; OR=4.4, P<.0001); conversely, impaired mental health status was more prevalent in CHF patients (43.5% vs. 22.0%; OR=1.7, P=.002). Importantly, results were replicated in the total cohort of matched and unmatched patients (results available from the authors).

Figure 3 – Prevalence (%) of impaired health status (lowest tertile) stratified by medical condi-tion. Abbreviations: PAD, peripheral arterial disease; CHF, chronic heart failure. *PAD coded as 1, and CHF coded as 0. †CHF coded as 1, and PAD coded as 0.

0

20

40

60

Physical Health Mental Health

PAD

CHF

P<.0001*

OR=4.4 [2.3-8.8]

Imp

air

ed

he

alt

h s

tatu

s (

%)

P=.002†

OR=1.7 [1.2-2.6]

Physical health Mental health


Clinical and socio-demographic correlates of health status

Multivariable linear regression analyses were performed to identify relevant clinical and socio-demo-graphic correlates of physical (Table 2) and mental health status (Table 3) in each medical condition. When including only one medical condition at a time, results indicated that PAD patients who did not complete high school education (P=.02), PAD patients with a history of cardiac disease (P=.02) or with comorbid diabetes mellitus (P=.03) reported lower physical health status scores, whereas older age (P=.002) and higher ABI values (P=.003) were associated with higher physical health status scores. In CHF, female sex (P=.001) and comorbid diabetes mellitus (P<.001) were significantly as-sociated with reporting worse physical health status (Table 2). Older age (P=.01) was associated with higher mental health status scores in PAD patients, whereas PAD patients without a partner (P=.01) indicated to have worse mental health status scores as compared with those living with a partner. No clinical or sociodemographic correlates could be identified for mental health status in CHF patients (Table 3).


Tabl

e 2 –

Inde

pend

ent c

orre

lates

of p

hysic

al he

alth

stat

us.

Abbr

eviat

ions:

ABI,

ankle

-bra

chial

inde

x; CH

F, ch

ronic

hea

rt fa

ilure

; LVE

F, lef

t ven

tricu

lar e

jectio

n fra

ction

; PAD

, per

ipher

al ar

teria

l dise

ase;

Si

gnific

ant r

esult

s are

pre

sent

ed in

bold

face

.

PA

D

CH

F

Corre

lates

β [9

5% C

I] P

valu

e

β [9

5% C

I] P

valu

e

Age

0.22

[0.08

;0.35

].00

2 -0

.09[-0

.25;0.

06]

.24Fe

male

sex

-0.08

[-0.19

;-0.04

].20

-0.28

[-0.44

;-0.12

].00

1

No pa

rtner

-0.11

[-0.23

;0.01

].07

0.14

[-0.03

;0.31

].10

Low

educ

ation

-0

.14[-0

.26;-0

.02]

.02

-0.07

[-0.23

;0.09

].41

Card

iac hi

story

-0.15

[-0.27

;-0.03

].02

-0

.04[-0

.20;0.

13]

.67

ABI

0.17

[0.06

;0.29

].00

3 -

--

LVEF

--

--0

.04[-0

.19;0.

11]

.61

Como

rbid

PAD

-

--

0.01

[-0.17

;0.16

].96

Como

rbid

CHF

-0.07

[-0.18

;0.04

].21

--

-

Diab

etes m

ellitu

s -0

.13[-0

.24;0.

01]

.03

-0.31

[-0.46

;-0.15

]<.0

01

Hype

rchole

stero

lemia

-0.05

[-0.16

;0.07

].40

0.09

[-0.08

;0.25

].31

Hype

rtens

ion-0

.01[-0

.11;0.

13]

.870.0

8[-0

.07;0.

25]

.28

Curre

nt sm

oking

-0.05

[-0.07

;0.18

].41

-0.08

[-0.24

;0.07

].30


Tabl

e 3 –

Inde

pend

ent c

orre

lates

of m

enta

l hea

lth st

atus

.

Abbr

eviat

ions:

ABI,

ankle

-bra

chial

inde

x; CH

F, ch

ronic

hea

rt fa

ilure

; LVE

F, lef

t ven

tricu

lar e

jectio

n fra

ction

; PAD

, per

ipher

al ar

teria

l dise

ase;

Si

gnific

ant r

esult

s are

pre

sent

ed in

bold

face

.

PA

D

CHF

Corre

lates

β [9

5% C

I] P

valu

e

β [9

5% C

I] P

valu

e

Age

0.24

[0.07

;0.35

].01

-0

.09[-0

.30;0.

07]

.27Fe

male

sex

-0.06

[-0.22

;0.16

].75

-0.06

[-0.53

;0.12

].51

No pa

rtner

-0.20

[-0.52

;-0.06

].01

0.0

6[-0

.03;0.

24]

.55

Low

educ

ation

-0

.05[-0

.12;0.

10]

.85-0

.13[-0

.27;0.

04]

.13

Card

iac hi

story

0.10

[-0.11

;0.13

].88

0.05

[-0.23

;0.22

].60

ABI

-0.04

[-0.08

;0.15

].52

--

-

LVEF

--

-0.0

3[-0

.23;0.

19]

.72

Como

rbid

PAD

-

--

0.06

[-0.20

;0.23

].48

Como

rbid

CHF

-0.06

[-0.18

;0.05

].32

--

-

Diab

etes m

ellitu

s -0

.09[-0

.21;0.

03]

.15-0

.17[-0

.55;0.

01]

.06

Hype

rchole

stero

lemia

-0.09

[-0.21

;0.03

].12

0.06

[-0.09

;0.24

].49

Hype

rtens

ion0.0

3[-0

.09;0.

15]

.650.0

1[-0

.09;0.

17]

.99

Curre

nt sm

oking

0.02

[-0.11

;0.15

].73

-0.01

[-0.28

;0.15

].89


DISCUSSION

By comparing PAD patients’ health status with another chronic disabling condition, the impact of PAD on patients’ physical health status became evident; patients with PAD reported a greater physical burden as compared with CHF patients, whereas mental health status was more affected in CHF patients. These results were both found using the continuous and dichotomous health status scores. Different clinical and socio-demographic correlates of disease burden were identified in patients with PAD and CHF.

The most important finding of this study was the discrepancy in health status scores between both medical conditions. Intuitively, one would expect that patients with a more advanced manifestation of cardiovascular disease, i.e. CHF patients, experience equal, if not greater symptom burden, and that this is accordingly reflected in their physical health status scores.21, 22 Our results underscore the importance of the issue of impaired physical health status in PAD patients and urge clinicians to focus on the invalidating character of PAD from the patient’s point of view.

Mental health status was found to be worse in CHF patients as compared with PAD patients. Howev-er, this does not imply that mental health status is not affected by PAD. In fact, recent findings indicate that depressive mood is a substantial problem in PAD.23, 24 The reason why there was a discrepancy in mental health status levels between both groups may be that CHF patients have to deal with end of life issues due to the advanced character of their disease.25 The observed disparity that was found regarding physical health status in both medical conditions may be explained by the occurrence of response shift in patients with more advanced cardiovascular disease.26 CHF patients may have acquiesced in the fact that their condition and its associated burden are irreversible, while patients with PAD may perceive their illness as more transient and expect to improve physical functioning. In contrast with CHF, there are diverse treatment options available for PAD patients that are aimed to relieve symptom burden.1

Important clinical and socio-demographic correlates of worse health status scores in PAD included younger age, lower educational level, cardiac history, diabetes mellitus, lower ABI scores, and living without a partner. Clinical factors that were associated with lower health status scores in CHF patients were female sex and comorbid diabetes mellitus. All these characteristics are easy to detect in daily clinical practice and should increase clinicians’ awareness, as these clinical and socio-demographic


correlates have been previously shown to explain disparities in cardiovascular outcomes.27, 28

Our results illustrate that it may be worthwhile studying risk factors in terms of poor health status out-comes per individual cardiovascular condition; especially in PAD, a firm research tradition on docu-menting patient-centered outcomes is still lacking and needs further development. Input from these studies will be needed to develop disease-specific management programs. In cardiac disease, health professionals are familiar with a tradition of multidisciplinary disease management programs, offering patient education, smoking cessation, diet and exercise counseling, which have proven to be effec-tive in improving clinical outcomes and health status.29,30 Such specific multidisciplinary treatment programs are not widespread in patients with PAD, although PAD patients have a poor cardiovascular prognosis and share the same risk factors with coronary heart disease patients.3, 31 The results of this study indicate that there is a need to develop specific management programs for PAD patients as different aspects of health status may be impacted by their condition and will require a tailor-made approach to optimize health status outcomes.

This study has some limitations: first, the current study did not evaluate the role of behavioral or intrapsychic factors, such as personality and distress, factors that may be equally important or even more important when documenting patients’ health status.32, 33 Future research studying PAD patients’ health status needs to incorporate traditional disease indicators and clinical information, as well as socio-demographic, behavioral, and psychological variables. Second, due to the cross-sectional na-ture of this study, no causality can be inferred from our findings. Third, since we analyzed the results of an observational study, we need to take into account the possibility of residual confounding. Finally, due to the lack of protocol-driven echo screening in PAD patients and ABI screening in CHF patients, we only could rely on their primary clinical diagnosis to define our clinical populations.

In conclusion, this study showed that physical health status was worse in PAD patients, as compared with CHF, whereas mental health status was more affected in CHF. Previous research already in-dicated that the secondary prevention of PAD patients is suboptimal when comparing with to other cardiac patient groups.2 By contrasting the health status of PAD patients with the health status of CHF patients, this study identified a new need that requires action. We believe that our findings may initiate further research documenting risk populations of patients with PAD in terms of their health status. Health status measures are becoming increasingly important in the sense that they provide an answer to the need of having more sensitive outcome measures to evaluate treatment outcomes


in PAD, as opposed to traditional clinical outcomes, such as death and patency rates. Focusing on patient-centered outcomes is also relevant because they provide important input for the development of disease management programs, and because of the potential prognostic information contained in these measures.34

AcknowledgementsWe would like to thank all participating patients and Drs. Vriens, Van Berge Henegouwen, Burger, Heyligers, Kranendonk, de Feyter, Gerritsen, Brenninkmeijer, Szabó, Alings, Janssens, Mrs. Nooren, Mr. Van Hees, Mrs. Vingerhoets, and Mrs. de Wit for their help with the data collection.


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3. Welten GM, Schouten O, Hoeks SE, Chonchol M, Vidakovic R, van Domburg RT, et al. Long-term progno-sis of patients with peripheral arterial disease: a comparison in patients with coronary artery disease. J Am Coll Cardiol 2008;51:1588-96.

4. Hirsch AT, Gloviczki P, Drooz A, Lovell M, Creager MA. Mandate for creation of a national peripheral arterial disease public awareness program: an opportunity to improve cardiovascular health. J Vasc Surg 2004;39:474-81.

5. Dumville JC, Lee AJ, Smith FB, Fowkes FG. The health-related quality of life of people with peripheral arterial disease in the community: the Edinburgh Artery Study. Br J Gen Pract 2004;54:826-31.


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8. Stanek EJ, Oates MB, McGhan WF, Denofrio D, Loh E. Preferences for treatment outcomes in patients with heart failure: symptoms versus survival. J Card Fail 2000;6:225-32.

9. Clark AM, Hartling L, Vandermeer B, McAlister FA. Meta-analysis: secondary prevention programs for patients with coronary artery disease. Ann Intern Med 2005;143:659-72.

10. Hobbs FD, Kenkre JE, Roalfe AK, Davis RC, Hare R, Davies MK. Impact of heart failure and left ventricu-lar systolic dysfunction on quality of life: a cross-sectional study comparing common chronic cardiac and medical disorders and a representative adult population. Eur Heart J 2002;23:1867-76.

11. Swedberg K, Cleland J, Dargie H, Drexler H, Follath F, Komajda M, et al. Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur Heart J 2005;26:1115-40.

12. Ware J, Jr., Kosinski M, Keller SD. A 12-Item Short-Form Health Survey: construction of scales and pre-liminary tests of reliability and validity. Med Care 1996;34:220-33.


13. Gandek B, Ware JE, Aaronson NK, Apolone G, Bjorner JB, Brazier JE, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project. Inter-national Quality of Life Assessment. J Clin Epidemiol 1998;51:1171-8.

14. Ware JE, Jr., Kosinski M, Bayliss MS, McHorney CA, Rogers WH, Raczek A. Comparison of methods for the scoring and statistical analysis of SF-36 health profile and summary measures: summary of results from the Medical Outcomes Study. Med Care 1995;33:AS264-79.

15. Mols F, Pelle AJ, Kupper N. Normative data of the SF-12 health survey with validation using postmyocar-dial infarction patients in the Dutch population. Qual Life Res 2009;18:403-414.

16. D’Agostino RB, Jr. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med 1998;17:2265-81.

17. Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum; 1988.18. Rumsfeld JS, Magid DJ, Plomondon ME, Sales AE, Grunwald GK, Every NR, et al. History of depression,

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fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24:987-1003.21. Walke LM, Gallo WT, Tinetti ME, Fried TR. The burden of symptoms among community-dwelling older

persons with advanced chronic disease. Arch Intern Med 2004;164:2321-4.22. Regensteiner JG, Hiatt WR, Coll JR, Criqui MH, Treat-Jacobson D, McDermott MM, et al. The impact of

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23. Smolderen KG, Aquarius AE, de Vries J, Smith OR, Hamming JF, Denollet J. Depressive symptoms in peripheral arterial disease: A follow-up study on prevalence, stability, and risk factors. J Affect Disord 2008;110:27-35.


25. Stromberg A, Jaarsma T. Thoughts about death and perceived health status in elderly patients with heart failure. Eur J Heart Fail 2008;10:608-13.

26. Levenson JW, McCarthy EP, Lynn J, Davis RB, Phillips RS. The last six months of life for patients with congestive heart failure. J Am Geriatr Soc 2000;48:S101-9.

27. Bernheim SM, Spertus JA, Reid KJ, Bradley EH, Desai RA, Peterson ED, et al. Socioeconomic disparities in outcomes after acute myocardial infarction. Am Heart J 2007;153:313-9.


28. Ting HH, Bradley EH, Wang Y, Lichtman JH, Nallamothu BK, Sullivan MD, et al. Factors associated with longer time from symptom onset to hospital presentation for patients with ST-elevation myocardial infarc-tion. Arch Intern Med 2008;168:959-68.

29. Kasper EK, Gerstenblith G, Hefter G, Van Anden E, Brinker JA, Thiemann DR, et al. A randomized trial of the efficacy of multidisciplinary care in heart failure outpatients at high risk of hospital readmission. J Am Coll Cardiol 2002;39:471-80.

30. Whellan DJ, Gaulden L, Gattis WA, Granger B, Russell SD, Blazing MA, et al. The benefit of implementing a heart failure disease management program. Arch Intern Med 2001;161:2223-8.

31. Graham I, Atar D, Borch-Johnsen K, Boysen G, Burell G, Cifkova R, et al. European guidelines on cardio-vascular disease prevention in clinical practice: executive summary. Eur Heart J 2007;28:2375-414.


33. Aquarius AE, Denollet J, de Vries J, Hamming JF. Poor health-related quality of life in patients with pe-ripheral arterial disease: Type D personality and severity of peripheral arterial disease as independent predictors. J Vasc Surg 2007;46:507-12.

34. Heidenreich PA, Spertus JA, Jones PG, Weintraub WS, Rumsfeld JS, Rathore SS, et al. Health status

identifies heart failure outpatients at risk for hospitalization or death. J Am Coll Cardiol 2006;47:752-6.

Chapter 11

Th e association of cognitive and somatic depressive symptoms with depression

recognition and outcomes aft er myocardial infarction

11

242 Chapter 11 - Depressive symptom dimensions in Myocardial infarction

Smolderen KG, Spertus JA, Reid KJ, Buchanan DM, Krumholz HM, Denollet J, Vaccarino V, Chan PS. The association of cognitive and somatic depressive symptoms with depression recognition and outcomes after myocardial infarction. Circ Car-diovasc Qual Outcomes 2009;2:328-37.

ABSTRACT

Background: Among patients with acute myocardial infarction (AMI), depression is both common and under-recognized. The association of different manifestations of depression, somatic and cogni-tive, with depression recognition and long-term prognosis is poorly understood.

Methods and Results: Depression was confirmed in 481 AMI patients enrolled from 21 sites dur-ing their index hospitalization with a Patient Health Questionnaire (PHQ-9) score ≥10. Within the PHQ-9, separate somatic and cognitive symptom scores were derived and the independent asso-ciation between these domains and the clinical recognition of depression, as documented in the medical records, was evaluated. In a separate multisite AMI registry of 2,347 patients, the associa-tion between somatic and cognitive depressive symptoms and 4-year all-cause mortality and 1-year all-cause rehospitalization was evaluated. Depression was clinically recognized in 29% (n=140) of patients. Cognitive depressive symptoms (Relative Risk [RR] per Standard Deviation [SD] in-crease=1.14; 95% confidence interval [CI] 1.03-1.26; P=0.01) were independently associated with depression recognition, while the association for somatic symptoms and recognition (RR=1.04; 95% CI 0.87-1.26; P=0.66) was not significant. However, unadjusted Cox regression analyses found that only somatic depressive symptoms were associated with 4-year mortality (Hazard Ratio [HR] per SD increase=1.22; 95% confidence interval [CI] 1.08-1.39) or 1-year rehospitalization (HR=1.22; 95%CI 1.11-1.33) while cognitive manifestations were not (HR for mortality=1.01; 95%CI 0.89-1.14; HR for rehospitalization=1.01; 95%CI 0.93-1.11). After multivariable adjustment, the association between somatic symptoms and rehospitalization persisted (HR=1.16; 95% CI:1.06-1.27; P=.01) but was at-tenuated for mortality (HR=1.07; 95% CI:0.94-1.21; P=.30).

Conclusions: Depression after AMI was recognized in fewer than 1 in 3 patients. Although cognitive symptoms were associated with recognition of depression, somatic symptoms were associated with long-term outcomes. Comprehensive screening and treatment of both somatic and cognitive symp-toms may be necessary to optimize depression recognition and treatment in AMI patients.


BACKGROUND

Depression after acute myocardial infarction (AMI) is prevalent and associated with both worse qual-ity of life1 and higher rates of mortality and rehospitalization.2-5 Despite efforts to promote systematic depression screening and facilitate its treatment in AMI patients,6-8 depression often goes unrec-ognized9-11 and its treatment after AMI with pharmacologic and behavioral interventions have not resulted in lower rates of mortality or rehospitalization.12 While depression is a common comorbidity that warrants treatment in its own right and can be useful in identifying high-risk patients for more aggressive treatment of coronary artery disease, a better understanding of which symptoms of de-pression are prognostic of long-term clinical outcomes would inform therapeutic strategies for future efficacy trials.

Depression is a complex disease characterized by both somatic and cognitive manifestations.13-15 So-matic depressive symptoms (e.g., fatigue, loss of energy, and sleep disturbances) are often masked by the physical symptoms of cardiovascular disease.16-18 Consequently, clinicians may be more likely to recognize and focus treatment of depression among those patients who manifest significant cog-nitive symptoms, such as sadness, pessimism, and anhedonia. While clinical trials of depression after AMI have largely relied on therapies that primarily target cognitive depressive symptoms,12, 19 preliminary studies suggest that somatic depressive symptoms have equal, if not greater, importance for prognosis in cardiac disease than do cognitive symptoms.20-23

An improved understanding of the cognitive and somatic depressive symptom dimensions would be a critical step in improving detection of and targeting interventions for depression in AMI patients. This is particularly important if there is discordance between the symptom dimensions that are associated with recognition and prognosis. Accordingly, we evaluated whether cognitive or somatic depressive symptoms facilitate recognition of depression in patients hospitalized with AMI and the extent to which each symptom domain was associated with long-term mortality and rehospitalization.


METHODS

Participants and study design

Data from two similar AMI registries—the Translational Research Investigating Underlying disparities in acute Myocardial infarction Patients’ Health Status (TRIUMPH) study and the Prospective Registry Evaluating outcomes after Myocardial Infarctions: Events and Recovery (PREMIER) study—were used to conduct this study. Both studies are large, prospective, geographically diverse, multi-site registries of academic and non-academic institutions within the US Patients for the TRIUMPH study were enrolled from 21 hospitals between April 11, 2005 and December 31, 2008, while patients within PREMIER were enrolled from 19 hospitals between January 1, 2003, and June 28, 2004. The TRI-UMPH study prospectively collected data on depression recognition and completed enrollment in December 2008. In contrast, the PREMIER study provided data on 1-year hospitalization rates and 4-year mortality but did not prospectively assess depression recognition. Therefore, we assessed depression recognition within TRIUMPH but evaluated long-term outcomes within PREMIER. The overview of both study designs is provided in Figure 1.

Both TRIUMPH and PREMIER had similar inclusion criteria and common enrollment sites, and the study design of PREMIER has been previously described.24 In both registries, patients 18 years of age or older with biomarker evidence of myocardial injury (a positive troponin or elevated creatinine kinase-MB fraction within 24 hours of hospital admission) and supporting evidence of an AMI (isch-emic signs or symptoms for >20 minutes or electrocardiographic ST changes) were enrolled. Patients were excluded if they were incarcerated or had biomarker elevations after elective coronary revascu-larization. Additionally, because we were interested in evaluating the association between depressive symptoms with recognition and prognosis, we excluded patients (n=142 [5.5%] in TRIUMPH and n=127 [5.4%] in PREMIER) without a baseline assessment of depressive symptoms with the Patient Health Questionnaire (PHQ-9). All participants provided written informed consent and the study pro-tocols were approved by the institutional review board at each participating site.


Data collection

Detailed data in both TRIUMPH and PREMIER were collected through chart abstraction (on clinical comorbidities, admission medications, presenting electrocardiogram, and treatments during the first 24 hours) and standardized in-depth interviews by trained hospital research staff between 24 and 72 hours after AMI admission (depressive symptoms, tobacco use, demographics, socioeconomic factors). Finally, at the time of discharge, angiographic data, in-hospital treatment of AMI, discharge recommendations, discharge medications, and discharge diagnoses were also documented by chart abstraction. Patient data included demographics (age, sex, and race), social and economic factors (marital status, education, access to health insurance, and employment status), and clinical variables (hypercholesterolemia, hypertension, peripheral arterial disease, diabetes mellitus, prior AMI, prior angina, prior coronary artery bypass surgery [CABG] or percutaneous coronary intervention [PCI], prior stroke, chronic renal failure, chronic lung disease, chronic heart failure, non-skin cancer, smok-ing, body mass index, family history of coronary artery disease, and history of depression or current treatment for depression). In addition, data were obtained on AMI severity (ST elevation vs. non-ST elevation AMI, left ventricular ejection fraction <40%, Killip class, number of coronary arteries with ≥75% stenosis, and systolic blood pressure and heart rate at AMI presentation). Finally, treatment information (coronary angiography, PCI, and CABG), patient instructions at discharge (cardiac reha-bilitation, diet counseling, exercise counseling, follow-up lipid assessment, and smoking cessation), and data on the percent and number of the Joint Commission on Accreditation of Healthcare Organi-zations’ quality of care indicators received at hospital discharge (e.g., appropriate use of aspirin, beta-blockers, thienopyridines, and other medications, median time to primary PCI, and lipid assessment during index hospitalization) were collected.25

Assessment of depressive symptomsThe PHQ-9, a validated tool for depression screening, was used to assess symptoms of depression.26 The PHQ-9 quantifies the frequency, over the past two weeks, of each of nine Diagnostic and Statisti-cal Manual of Mental Disorders, Fourth Edition27 criteria on a 4-point Likert scale ranging from “0” (not at all) to “3” (nearly every day). Responses are summed to create a score between 0 and 27 points. A PHQ score of ≥10 has been recommended to screen for the diagnosis of major depression and has been shown to have a sensitivity and specificity of 88%.28-30


In this study, we were interested in examining the somatic and cognitive dimensions of depression. Based on prior work,20 four PHQ-9 items related to problems with sleep, fatigability, appetite, and psy-chomotor agitation/retardation were classified as somatic depressive symptoms, whereas five items, related to lack of interest, depressed mood, negative feelings about self, concentration problems and suicidal ideation, were classified as cognitive depressive symptoms. These depression dimension classifications have been previously validated, with high Cronbach’s alpha statistics for both somatic depressive symptoms (0.77) and cognitive depressive symptoms (0.84).20 We accordingly calculated sum scores of the two dimensions for our analyses.20 Correlations between both dimensions among patients with a PHQ-9 ≥10 ranged from r=0.04 in TRIUMPH to r=0.23 in PREMIER.

Depression recognitionThe primary endpoint for the first objective of this study was the recognition of depression at the time of AMI hospitalization in the TRIUMPH study. Patients were classified as depressed if they had a PHQ-9 score of ≥10. Clinicians, blinded to the results of the PHQ-9, had to make a diagnosis of de-pression in the hospital chart, assign a diagnosis of depression at hospital discharge, prescribe active depression treatment (antidepressant medication, counseling, or psychiatric consultation), or refer patients for depression management at discharge in order for patients to be classified as ‘clinically recognized’. To ensure that we did not misclassify the use of antidepressive medications as indicat-ing depression recognition, the clinical indications for such medications were reviewed. Patients with a PHQ-9 ≥10 and taking antidepressant medications solely for the purposes of smoking cessation (n=6 for bupropion) or neuropathic pain (n=5 for tricyclic antidepressants or serotonin-norepinephrine reuptake inhibitors) were not classified as having recognized depression.

Mortality and rehospitalizationThe endpoints for the second objective of this study were 4-year all-cause mortality and 1-year all-cause rehospitalization among patients enrolled in the PREMIER study. Mortality was determined using the Social Security Death Master File, and hospitalization data were determined from phone interviews at one month, six months, and one year.



There were two main objectives in this study. We first evaluated whether somatic or cognitive depres-sive symptoms were associated with clinical recognition of depression in TRIUMPH. Next, we evalu-ated whether somatic or cognitive depressive symptoms were associated with long-term outcomes in PREMIER.


Figure 1 – Overview of study design and objectives. Abbreviations: AMI, acute myocardial infarction; PHQ, patient health questionnaire; PRE-MIER, prospective registry evaluating outcomes after myocardial infarctions: events and recovery; TRIUMPH, translational research investigating underlying disparities in acute myocardial infarction patients’ health Status.

PH

Q depression dim

ensionsD

emographics

Socioeconom

ic factorsM

edical comorbidities

Clinical characteristics

PH

Q depression

dimensions

Objective 1

Depression recognition in

TRIU

MPH

Objective 2

Long-term prognosis in

PREM

IER

Index hospitalization

Follow-up

Depression recognition in

Depressed (PH

Q > 10) patients

Covariates

Dem

ographicsS

ocioeconomic factors

Medical com

orbiditiesC

linical characteristicsC

atheterization dataR

evascularization dataC

linical site information

1-Year rehospitalization

4-Year m

ortality


Depression recognition in TRIUMPHTo assess predictors of depression recognition, baseline characteristics of patients with recognized and unrecognized depression were compared using Student’s t-tests and the Wilcoxon tests for con-tinuous variables and Chi-square or Fisher’s Exact tests for categorical variables, as appropriate. Hi-erarchical modified Poisson regression models, which adjust for clustering at the hospital level, were then constructed to assess the unadjusted and adjusted relationship between somatic and cognitive depression scores and clinical recognition of depression (binary dependent variable) by entering both dimensions simultaneously in the model as independent variables. Non-linear relationships between the depression dimensions and recognition were assessed with restricted cubic spline terms with 3 knots for curvature in the multivariable models.31 Because of the high event rate; a modified Poisson regression model (i.e., Poisson regression with a robust error variance) was used to derive relative risks, as odds ratios would overestimate the strengths of associations.32

The multivariable model adjusted for all variables with a significant association in bivariate analysis as described in Table 1, along with the following clinically important variables regardless of statistical significance: age, gender, marital status, insurance status, left ventricular ejection fraction <40%, his-tory of chronic heart failure, and ST elevation AMI. Somatic and cognitive depression symptom scores were evaluated as continuous variables and were interpreted using a standard deviation increase for each measure (3 points for both). As a sensitivity analysis, we repeated the analyses when the cohort was restricted to patients without a history of depression.

Mortality and rehospitalization in PREMIERFor descriptive purposes only, we categorized patients in the upper quartile of somatic and cognitive depressive symptom scores as having significant somatic or cognitive depressive symptoms. Base-line comparisons between those with and without significant somatic depressive symptoms were compared using Student’s t-tests and the Wilcoxon test for continuous variables and the Chi-square or Fisher’s Exact test for categorical variables, as appropriate. Similarly, baseline characteristics were compared between those with and without significant cognitive depressive symptoms.

The association of a PHQ-9 score ≥10 with higher mortality and rehospitalization risk, as demonstrat-ed in prior studies,5, 33 was first validated in our study cohort with unadjusted Kaplan-Meier plots and multivariable Cox proportional hazards regression analyses stratified by site of care. Next, unadjusted and multivariable Cox proportional hazard regression models stratified by site were constructed to


jointly evaluate the association of both somatic and cognitive depressive symptom scores (as con-tinuous variables in the model) with mortality and rehospitalization in separate models. Multivariable models adjusted for demographic (age, sex, race), clinical (diabetes mellitus, prior coronary artery disease (prior MI, prior PCI or prior CABG), stroke, chronic renal failure, chronic lung disease, chronic heart failure, non-skin cancer, current smoking, body mass index) socioeconomic (marital status, education, insurance status and working status), AMI severity (ST elevation AMI, left ventricular ejec-tion fraction <40%, heart rate), and treatment (angiography, revascularization, percent and number of quality of care indicators received) variables. Somatic and cognitive depression symptom scores were interpreted using a standard deviation increase in each measure (3 point increase). Non-linear relationships of depression dimensions and outcomes were assessed using restricted cubic spline terms with 3 knots for curvature in the multivariable models.31

Missing data

Model covariates in TRIUMPH were missing for at least 1 study covariate in 7 patients (1.5% of cohort), with no study covariate having >1% missing data. Data in PREMIER were missing for at least 1 study covariate in 326 patients (13.9% of cohort), with no study covariate having >6% missing data. In both datasets, missing data were assumed to be missing at random and imputed as a single imputation dataset using IVEWARE software.34 Additionally, data on mortality was 100% complete in PREMIER, but follow-up interviews on rehospitalization were missing in 9% (n=197) of surviving patients. Based on prior work,35 bias attributable to those without follow-up interviews was assessed by creating a non-parsimonious model for the propensity to miss the 1-year follow-up interview. The reciprocal of this probability was then used to weight the associations among responders in the mul-tivariable Cox regression model for rehospitalization to adjust for potential observable bias from lost follow-up.35 For both sets of analyses, results with and without weighting were comparable, so only the weighted are presented.

All tests for significance were two-tailed with an alpha level of 0.05 and were conducted with SAS Version 9.1.3 (SAS Institute, Cary, NC) and R version 2.6.0.36 The authors independently designed the study, collected and analyzed the data, and drafted and revised the manuscript. Drs. Smolderen and Chan had full access to all of the data and take full responsibility for the integrity of the data and the accuracy of the data analysis.


RESULTS

Depression recognition in the TRIUMPH registry

Of 2,573 patients screened with the PHQ-9 in TRIUMPH, depression was present in 481 (19%) patients. Of these, depression was unrecognized in 341 (71%) and recognized in 140 (29%) pa-tients. Among those with recognized depression, antidepressants were prescribed at discharge in 118 (84.3%) patients and depression counseling or a recommendation for further follow-up was pre-scribed in 72 (51.4%) patients. Depression was less likely to be recognized in patients who were black, had attained a lower educational level, and who were employed (Table 1). Depression was more likely to be recognized among patients with a prior history of hypercholesterolemia, CABG, PCI, and depression. Patients with recognized depression, compared to those with unrecognized depression, had higher scores on the PHQ-9 for cognitive symptoms (7.5±3.3 vs. 6.3±2.9; P<.001) but similar scores for somatic symptoms (7.7±2.0 vs. 7.6±2.0; P=.59).


Tabl

e 1 –

Char

acte

ristic

s of p

atien

ts w

ith re

cogn

ized

and

unre

cogn

ized

depr

essio

n wi

thin

TRI

UMPH

.

Depr

essio

nRe

cogn

ized

n=14

0Un

reco

gnize

d n=

341

P va

lue

Demo

grap

hics,

No. (

%)

Mean

age(

SD),

year

s55

.6 (1

1.7)

56.5

(12.1

) .44

Fema

le se

x 68

(48.6

) 15

1 (44

.3)

.39Ra

ce Whit

e/Cau

casia

n Bl

ack/A

frican

Ame

rican

Ot

her

103 (

73.6)

24

(17.1

) 13

(9.3)

219 (

64.2)

95

(27.9

) 27

(7.9)

.05

Socio

econ

omic

factor

s, No

. (%

) Ma

rried

54 (3

8.6)

144 (

42.4)

.44

Grea

ter th

an hi

gh sc

hool

educ

ation

77

(55.0

) 14

5 (42

.6)

.01No

med

ical in

sura

nce

28 (2

0.0)

90 (2

6.4)

.20W

orkin

g full

- or p

art-t

ime

42 (3

0.0)

142 (

41.7)

.05

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

79 (5

6.4)

158 (

46.3)

.04

Hype

rtens

ion10

9 (77

.9)

240 (

70.4)

.10

Perip

hera

l arte

rial d

iseas

e 9 (

6.4)

21 (6

.2)

.91Di

abete

s mell

itus

63 (4

5.0)

126 (

37.0)

.10

Prior

AMI

31

(22.1

) 71

(20.8

) .75

Prior

angin

a24

(17.1

) 41

(12.0

) .14

Prior

CAB

G 27

(19.3

) 34

(10.0

) .01

Prior

PCI

42

(30.0

) 73

(21.4

) .05

Prior

stro

ke

10 (7

.1)

15 (4

.4)

.22Ch

ronic

rena

l failu

re

13 (9

.3)

23 (6

.7)

.34Ch

ronic

lung

dise

ase

17 (1

2.1)

38 (1

1.1)

.75Ch

ronic

hear

t failu

re

19 (1

3.6)

34 (1

0.0)

.25Ca

ncer

(othe

r tha

n skin

)9 (

6.4)

26 (7

.6)

.65Sm

oked

with

in las

t 30 d

ays

70 (5

0.0)

170 (

50.3)

.95

Mean

body

mas

s ind

ex

30.9

(7.1)

30

.5 (7

.0)

.60Fa

mily

histor

y of C

AD

107 (

77.0)

26

2 (77

.5)

.90Hi

story

of de

pres

sion

57 (4

0.7)

18 (5

.3)

<.001

Clini

cal c

hara

cteris

tics i

ndex

MI a

dmiss

ion, N

o. (%

)ST

-elev

ation

MI

51 (3

6.4)

132 (

38.7)

.64

Ejec

tion f

racti

on <

40%

28

(20.0

) 71

(20.9

) .83

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

113 (

81.9)

22

(15.9

) 2 (

1.4)

1 (0.7

)

281 (

84.1)

45

(13.5

) 5 (

1.5)

3 (0.9

)

.91

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm H

g13

7.0(3

2.1)

143.2

(30.0

).05

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 87

.0(24

.8)83

.8(21

.9).16


Abbr

eviat

ions:

AMI,

acut

e m

yoca

rdial

infa

rctio

n; B

MI,

body

mas

s ind

ex (k

ilogr

ams/m

eter

s2 ); CA

BG, c

oron

ary

arte

ry b

ypas

s gr

aftin

g; C

AD, c

oron

ary

arte

ry d

iseas

e;

PCI,

perc

utan

eous

coro

nary

inte

rven

tions

.

Depr

essio

nRe

cogn

ized

n=14

0Un

reco

gnize

d n=

341

P va

lue

Demo

grap

hics,

No. (

%)

Mean

age(

SD),

year

s55

.6 (1

1.7)

56.5

(12.1

) .44

Fema

le se

x 68

(48.6

) 15

1 (44

.3)

.39Ra

ce Whit

e/Cau

casia

n Bl

ack/A

frican

Ame

rican

Ot

her

103 (

73.6)

24

(17.1

) 13

(9.3)

219 (

64.2)

95

(27.9

) 27

(7.9)

.05

Socio

econ

omic

factor

s, No

. (%

) Ma

rried

54 (3

8.6)

144 (

42.4)

.44

Grea

ter th

an hi

gh sc

hool

educ

ation

77

(55.0

) 14

5 (42

.6)

.01No

med

ical in

sura

nce

28 (2

0.0)

90 (2

6.4)

.20W

orkin

g full

- or p

art-t

ime

42 (3

0.0)

142 (

41.7)

.05

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

79 (5

6.4)

158 (

46.3)

.04

Hype

rtens

ion10

9 (77

.9)

240 (

70.4)

.10

Perip

hera

l arte

rial d

iseas

e 9 (

6.4)

21 (6

.2)

.91Di

abete

s mell

itus

63 (4

5.0)

126 (

37.0)

.10

Prior

AMI

31

(22.1

) 71

(20.8

) .75

Prior

angin

a24

(17.1

) 41

(12.0

) .14

Prior

CAB

G 27

(19.3

) 34

(10.0

) .01

Prior

PCI

42

(30.0

) 73

(21.4

) .05

Prior

stro

ke

10 (7

.1)

15 (4

.4)

.22Ch

ronic

rena

l failu

re

13 (9

.3)

23 (6

.7)

.34Ch

ronic

lung

dise

ase

17 (1

2.1)

38 (1

1.1)

.75Ch

ronic

hear

t failu

re

19 (1

3.6)

34 (1

0.0)

.25Ca

ncer

(othe

r tha

n skin

)9 (

6.4)

26 (7

.6)

.65Sm

oked

with

in las

t 30 d

ays

70 (5

0.0)

170 (

50.3)

.95

Mean

body

mas

s ind

ex

30.9

(7.1)

30

.5 (7

.0)

.60Fa

mily

histor

y of C

AD

107 (

77.0)

26

2 (77

.5)

.90Hi

story

of de

pres

sion

57 (4

0.7)

18 (5

.3)

<.001

Clini

cal c

hara

cteris

tics i

ndex

MI a

dmiss

ion, N

o. (%

)ST

-elev

ation

MI

51 (3

6.4)

132 (

38.7)

.64

Ejec

tion f

racti

on <

40%

28

(20.0

) 71

(20.9

) .83

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

113 (

81.9)

22

(15.9

) 2 (

1.4)

1 (0.7

)

281 (

84.1)

45

(13.5

) 5 (

1.5)

3 (0.9

)

.91

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm H

g13

7.0(3

2.1)

143.2

(30.0

).05

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 87

.0(24

.8)83

.8(21

.9).16


Adjusting for demographic, and clinical factors, cognitive depressive symptoms were associated with depression recognition (adjusted Risk Ratio [RR] per Standard Deviation [SD] increase=1.14; 95% CI, 1.03-1.26; P=.01), but no significant association was observed for somatic depressive symp-toms (adjusted RR per SD increase=1.04; 95% CI, 0.87-1.26; P=.66) (Figure 2). There was no evi-dence of non-linearity (P value >.25). Results were not different when we restricted the cohort to only those patients without a history of depression. Other predictors of depression recognition included a history of depression (adjusted RR=3.90; 95% CI, 2.73-5.58; P<.001) and chronic heart failure (adjusted RR=1.45; 95% CI, 1.02-2.08; P=.04). Race, education, and employment status were not independently associated with depression recognition. The final model showed good discrimination (C-statistic=0.78).


Figure 2 – Independent predictors of depression recognition during index AMI hospitalization. Model estimates are presented as relative risks with 95% confidence intervals. Abbreviations: AMI, acute myocardial infarction; CHF, chronic heart failure; EF, ejection fraction; PHQ, patient health questionnaire; SD, Standard Deviation; STEMI, ST-elevation myocardial infarction.

0.25 0.50 1.00 2.00 4.00

PHQ Somatic score (5 point increase)

PHQ Cognitive score (5 point increase)

STEMI

History of CHF

EF <40%

History of depression

Insurance

Education > high school

Non-Caucasian

Married

Male vs. female

Age (10 year increase)0.96 (0.88, 1.04)

0.94 (0.76, 1.17)

0.93 (0.74, 1.16)

0.86 (0.60, 1.22)

1.16 (0.90, 1.49)

0.99 (0.65, 1.51)

3.90 (2.73, 5.58)

1.05 (0.75, 1.47)

1.45 (1.02, 2.08)

1.05 (0.78, 1.40)

1.14 (1.03, 1.26)

1.04 (0.87, 1.26)


Mortality and rehospitalization in the PREMIER registry

Of 2,347 patients within PREMIER, 624 (26.6%) were classified as having significant somatic depres-sive symptoms (upper quartile of somatic depressive symptom score ≥6) and 590 (25.1%) were cat-egorized as having significant cognitive depressive symptoms (upper quartile of cognitive depressive symptom dimension score ≥4).

Baseline comparisons between those with and without significant somatic depressive symptoms and those with and without significant cognitive depressive symptoms are presented in Table 2. In both comparisons, patients with significant depressive symptoms were younger; were more likely to be female and African American, and were less likely to be married. Depressed patients were also less likely to have completed post-secondary education and to be employed. Moreover, patients with ei-ther significant somatic or cognitive symptoms of depression, compared to those without, had higher frequencies of comorbidities (history of hypertension, diabetes mellitus, AMI, angina, PCI, chronic lung disease, and chronic heart failure) and worse disease severity at the time of their AMI (higher Kil-lip class and heart rate). However, they were less likely to undergo coronary angiography, to undergo revascularization with either PCI or CABG, or to receive referrals for cardiac rehabilitation or exercise counseling at discharge. While patients in all groups were eligible for the same number of quality-of-care indicators (including medications) at discharge, patients with significant somatic depressive symptoms received fewer of these treatments at discharge.


Tabl

e 2 –

Patie

nt ch

arac

teris

tics o

f the

dep

ress

ion

grou

ps w

ithin

PRE

MIER

.*

Sign

ifica

nt P

HQ so

mat

ic sy

mpt

oms

Sign

ifica

nt P

HQ co

gniti

ve sy

mpt

oms

Ye

s n=

624

No

n=17

23P

valu

e Ye

s n=

590

No

n=17

57P

valu

e

Demo

grap

hics,

No. (

%)

Mean

age (

SD),

year

s 59

.1 (1

2.6)

61.4

(13.0

) <.0

0158

.0 (1

1.7)

61.7

(13.1

) <.0

01Fe

male

sex

256 (

41.0)

49

7 (28

.8)

<.001

233 (

39.5)

52

0 (29

.6)

<.001

Race

W

hite/C

auca

sian

Blac

k/Afric

an A

meric

an

Othe

r

42

7 (68

.6)

162 (

26.0)

33

(5.3)

13

07 (7

6.3)

330 (

19.3)

75

(4.4)

<.001

39

5 (67

.3)

161 (

27.4)

31

(5.3)

13

39 (7

6.6)

331 (

18.9)

77

(4.4)

<.001

Socio

econ

omic

factor

s, No

. (%

)

Ma

rried

33

5 (54

.3)

1066

(62.7

) <.0

0130

7 (53

.1)

1094

(62.9

) .00

1Gr

eater

than

high

scho

ol ed

ucati

on

259 (

42.2)

86

4 (50

.8)

<.001

244 (

42.1)

87

9 (50

.6)

<.001

Havin

g no i

nsur

ance

81

(13.8

) 19

4 (11

.8)

.22

91 (1

6.2)

184 (

11.0)

.00

1W

orkin

g full

- or p

art-t

ime

231 (

37.2)

79

3 (46

.4)

<.001

211 (

36.0)

81

3 (46

.6)

<.001

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

323 (

51.8)

82

2 (47

.7)

.08

303 (

51.4)

84

2 (47

.9)

.15

Hype

rtens

ion

426 (

68.3)

10

61 (6

1.6)

.0141

0 (69

.5)

1077

(61.3

) <.0

01Pe

ri phe

ral a

rteria

l dise

ase

58 (9

.3)

128 (

7.4)

.14

46 (7

.8)

140 (

8.0)

.89

Diab

etes m

ellitu

s 21

9 (35

.1)

453 (

26.3)

<.0

0120

1 (34

.1)

471 (

26.8)

<.0

01Pr

ior A

MI

164 (

26.3)

33

5 (19

.4)

<.001

163 (

27.6)

33

6 (19

.1)

<.001

Prior

angin

a 13

2 (21

.2)

271 (

15.7)

.01

128 (

21.7)

27

5 (15

.7)

<.001

Prior

CAB

G 90

(14.4

) 20

6 (12

.0)

.11

85 (1

4.4)

211 (

12.0)

.13

Pr

ior P

CI

129 (

20.7)

27

9 (16

.2)

.0112

0 (20

.3)

288 (

16.4)

.03

Prior

stro

ke

45 (7

.2)

109 (

6.3)

.44

49 (8

.3)

105 (

6.0)

.05Ch

ronic

rena

l failu

re

76 (1

2.2)

155 (

9.0)

.0262

(10.5

) 16

9 (9.6

) .53

Ch

ronic

lung

dise

ase

122 (

19.6)

18

4 (10

.7)

<.001

100 (

16.9)

20

6 (11

.7)

.001

Chro

nic he

art fa

ilure

10

8 (17

.3)

175 (

10.2)

<.0

0198

(16.6

) 18

5 (10

.5)

<.001

Canc

er (o

ther t

han s

kin)

46 (7

.4)

150 (

8.7)

.30

42 (7

.1)

154 (

8.8)

.21

Smok

ed w

ithin

last 3

0 day

s 23

3 (37

.6)

567 (

33.0)

.04

244 (

41.7)

55

6 (31

.7)

<.001

Mean

bod y

mas

s ind

ex (S

D)

29.7

(6.6)

29

.0 (6

.3)

.0329

.6 (6

.4)

29.1

(6.4)

.10

Fa

mily

histor

y of C

AD

228 (

36.5)

57

4 (33

.3)

.15

218 (

36.9)

58

4 (33

.2)

.10

Curre

ntly r

eceiv

ing tr

eatm

ent fo

r 15

0 (24

.2)

147 (

8.6)

<.001

167 (

28.5)

13

0 (7.4

) <.0

01Cl

inica

l cha

racte

ristic

s ind

ex M

I adm

ission

,

ST

-elev

ation

MI

249 (

39.9)

76

8 (44

.6)

.0423

5 (39

.8)

782 (

44.5)

.05

E jec

tion f

racti

on <

40%

18

1 (29

.0)

427 (

24.9)

.04

159 (

26.9)

44

9 (25

.6)

.53

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

40

0 (76

.0)

87 (1

6.5)

28 (5

.3)

11 (2

.1)

12

52 (8

5.1)

169 (

11.5)

24

(1.6)

26

(1.8)

<.001

39

1 (77

.0)

83 (1

6.3)

23 (4

.5)

11 (2

.2)

12

61 (8

4.7)

173 (

11.6)

29

(1.9)

26

(1.7)

<.001

Dise

ased

vess

els (>

75%

sten

osis)

0

1

2

3

61

(11.7

) 26

8 (51

.2)

101(

19.3)

93

(17.8

)

13

1 (8.6

) 76

3 (50

.3)

340 (

22.4)

28

4 (18

.7)

.12

58

(11.8

) 22

7 (46

.3)

113 (

23.1)

92

(18.8

)

13

4 (8.6

) 80

4 (51

.8)

328 (

21.1)

28

5 (18

.4)

.07

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm

140.2

(32.8

) 13

8.9(3

0.8)

.39

140.0

(32.5

) 13

9.0(3

1.0)

.53

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 83

.4(20

.0)

80.5(

22.1)

.01

83.8(

21.1)

80

.4(21

.7)

<.001

Cathe

teriza

tion a

nd re

vasc

ulariz

ation

data ,

Prim

ary o

r othe

r PCI

35

6 (57

.1)

1069

(62.0

) .03

324 (

54.9)

11

01 (6

2.7)

<.001

Coro

nar y

angio

grap

hy

523 (

83.8)

15

18 (8

8.1)

.0149

0 (83

.1)

1551

(88.3

) .00

1Re

vasc

ulariz

ation

42

1 (67

.5)

1268

(73.6

) .01

387 (

65.6)

13

02 (7

4.1)

<.001

Patie

nt ins

tructi

ons a

t disc

har g

e, No

. (%

)

Card

iac re

habil

itatio

n 26

3 (42

.1)

870 (

50.5)

<.0

0124

0 (40

.7)

893 (

50.8)

<.0

01Di

et co

unse

ling

485 (

77.7)

13

32 (7

7.3)

.83

457 (

77.5)

13

60 (7

7.4)

.98

Exer

cise c

ouns

eling

26

7 (42

.8)

868 (

50.4)

.00

125

2 (42

.7)

883 (

50.3)

.01

Li pid

asse

ssme

nt 67

(10.7

) 26

9 (15

.6)

.0174

(12.5

) 26

2 (14

.9)

.16

Smok

ing ce

ssati

on

199 (

31.9)

48

0 (27

.9)

.06

204 (

34.6)

47

5 (27

.0)

<.001

Clini

cal s

ite in

forma

tion

Mean

QOC

: Num

ber o

f elig

ible i

ndica

tors

5.1 (1

.4)

5.2 (1

.3)

.45

5.1 (1

.3)

5.2 (1

.3)

.20

Mean

QOC

: % of

eligi

ble

indica

tors r

eceiv

ed (S

D)

85.3

(19.0

) 88

.2 (1

7.0)

<.001

86.6

(18.1

) 87

.7 (1

7.4)

.18

Depr

essiv

e sym

ptoms

, No.

(%)

De

pres

sion p

rese

nt ba

selin

e (PH

Q ≥1

0)

444 (

71.2)

80

(4.6)

<.0

0145

5 (77

.1)

69 (3

.9)

<.001


Sign

ifica

nt P

HQ so

mat

ic sy

mpt

oms

Sign

ifica

nt P

HQ co

gniti

ve sy

mpt

oms

Ye

s n=

624

No

n=17

23P

valu

e Ye

s n=

590

No

n=17

57P

valu

e

Demo

grap

hics,

No. (

%)

Mean

age (

SD),

year

s 59

.1 (1

2.6)

61.4

(13.0

) <.0

0158

.0 (1

1.7)

61.7

(13.1

) <.0

01Fe

male

sex

256 (

41.0)

49

7 (28

.8)

<.001

233 (

39.5)

52

0 (29

.6)

<.001

Race

W

hite/C

auca

sian

Blac

k/Afric

an A

meric

an

Othe

r

42

7 (68

.6)

162 (

26.0)

33

(5.3)

13

07 (7

6.3)

330 (

19.3)

75

(4.4)

<.001

39

5 (67

.3)

161 (

27.4)

31

(5.3)

13

39 (7

6.6)

331 (

18.9)

77

(4.4)

<.001

Socio

econ

omic

factor

s, No

. (%

)

Ma

rried

33

5 (54

.3)

1066

(62.7

) <.0

0130

7 (53

.1)

1094

(62.9

) .00

1Gr

eater

than

high

scho

ol ed

ucati

on

259 (

42.2)

86

4 (50

.8)

<.001

244 (

42.1)

87

9 (50

.6)

<.001

Havin

g no i

nsur

ance

81

(13.8

) 19

4 (11

.8)

.22

91 (1

6.2)

184 (

11.0)

.00

1W

orkin

g full

- or p

art-t

ime

231 (

37.2)

79

3 (46

.4)

<.001

211 (

36.0)

81

3 (46

.6)

<.001

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

323 (

51.8)

82

2 (47

.7)

.08

303 (

51.4)

84

2 (47

.9)

.15

Hype

rtens

ion

426 (

68.3)

10

61 (6

1.6)

.0141

0 (69

.5)

1077

(61.3

) <.0

01Pe

ri phe

ral a

rteria

l dise

ase

58 (9

.3)

128 (

7.4)

.14

46 (7

.8)

140 (

8.0)

.89

Diab

etes m

ellitu

s 21

9 (35

.1)

453 (

26.3)

<.0

0120

1 (34

.1)

471 (

26.8)

<.0

01Pr

ior A

MI

164 (

26.3)

33

5 (19

.4)

<.001

163 (

27.6)

33

6 (19

.1)

<.001

Prior

angin

a 13

2 (21

.2)

271 (

15.7)

.01

128 (

21.7)

27

5 (15

.7)

<.001

Prior

CAB

G 90

(14.4

) 20

6 (12

.0)

.11

85 (1

4.4)

211 (

12.0)

.13

Pr

ior P

CI

129 (

20.7)

27

9 (16

.2)

.0112

0 (20

.3)

288 (

16.4)

.03

Prior

stro

ke

45 (7

.2)

109 (

6.3)

.44

49 (8

.3)

105 (

6.0)

.05Ch

ronic

rena

l failu

re

76 (1

2.2)

155 (

9.0)

.0262

(10.5

) 16

9 (9.6

) .53

Ch

ronic

lung

dise

ase

122 (

19.6)

18

4 (10

.7)

<.001

100 (

16.9)

20

6 (11

.7)

.001

Chro

nic he

art fa

ilure

10

8 (17

.3)

175 (

10.2)

<.0

0198

(16.6

) 18

5 (10

.5)

<.001

Canc

er (o

ther t

han s

kin)

46 (7

.4)

150 (

8.7)

.30

42 (7

.1)

154 (

8.8)

.21

Smok

ed w

ithin

last 3

0 day

s 23

3 (37

.6)

567 (

33.0)

.04

244 (

41.7)

55

6 (31

.7)

<.001

Mean

bod y

mas

s ind

ex (S

D)

29.7

(6.6)

29

.0 (6

.3)

.0329

.6 (6

.4)

29.1

(6.4)

.10

Fa

mily

histor

y of C

AD

228 (

36.5)

57

4 (33

.3)

.15

218 (

36.9)

58

4 (33

.2)

.10

Curre

ntly r

eceiv

ing tr

eatm

ent fo

r 15

0 (24

.2)

147 (

8.6)

<.001

167 (

28.5)

13

0 (7.4

) <.0

01Cl

inica

l cha

racte

ristic

s ind

ex M

I adm

ission

,

ST

-elev

ation

MI

249 (

39.9)

76

8 (44

.6)

.0423

5 (39

.8)

782 (

44.5)

.05

E jec

tion f

racti

on <

40%

18

1 (29

.0)

427 (

24.9)

.04

159 (

26.9)

44

9 (25

.6)

.53

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

40

0 (76

.0)

87 (1

6.5)

28 (5

.3)

11 (2

.1)

12

52 (8

5.1)

169 (

11.5)

24

(1.6)

26

(1.8)

<.001

39

1 (77

.0)

83 (1

6.3)

23 (4

.5)

11 (2

.2)

12

61 (8

4.7)

173 (

11.6)

29

(1.9)

26

(1.7)

<.001

Dise

ased

vess

els (>

75%

sten

osis)

0

1

2

3

61

(11.7

) 26

8 (51

.2)

101(

19.3)

93

(17.8

)

13

1 (8.6

) 76

3 (50

.3)

340 (

22.4)

28

4 (18

.7)

.12

58

(11.8

) 22

7 (46

.3)

113 (

23.1)

92

(18.8

)

13

4 (8.6

) 80

4 (51

.8)

328 (

21.1)

28

5 (18

.4)

.07

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm

140.2

(32.8

) 13

8.9(3

0.8)

.39

140.0

(32.5

) 13

9.0(3

1.0)

.53

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 83

.4(20

.0)

80.5(

22.1)

.01

83.8(

21.1)

80

.4(21

.7)

<.001

Cathe

teriza

tion a

nd re

vasc

ulariz

ation

data ,

Prim

ary o

r othe

r PCI

35

6 (57

.1)

1069

(62.0

) .03

324 (

54.9)

11

01 (6

2.7)

<.001

Coro

nar y

angio

grap

hy

523 (

83.8)

15

18 (8

8.1)

.0149

0 (83

.1)

1551

(88.3

) .00

1Re

vasc

ulariz

ation

42

1 (67

.5)

1268

(73.6

) .01

387 (

65.6)

13

02 (7

4.1)

<.001

Patie

nt ins

tructi

ons a

t disc

har g

e, No

. (%

)

Card

iac re

habil

itatio

n 26

3 (42

.1)

870 (

50.5)

<.0

0124

0 (40

.7)

893 (

50.8)

<.0

01Di

et co

unse

ling

485 (

77.7)

13

32 (7

7.3)

.83

457 (

77.5)

13

60 (7

7.4)

.98

Exer

cise c

ouns

eling

26

7 (42

.8)

868 (

50.4)

.00

125

2 (42

.7)

883 (

50.3)

.01

Li pid

asse

ssme

nt 67

(10.7

) 26

9 (15

.6)

.0174

(12.5

) 26

2 (14

.9)

.16

Smok

ing ce

ssati

on

199 (

31.9)

48

0 (27

.9)

.06

204 (

34.6)

47

5 (27

.0)

<.001

Clini

cal s

ite in

forma

tion

Mean

QOC

: Num

ber o

f elig

ible i

ndica

tors

5.1 (1

.4)

5.2 (1

.3)

.45

5.1 (1

.3)

5.2 (1

.3)

.20

Mean

QOC

: % of

eligi

ble

indica

tors r

eceiv

ed (S

D)

85.3

(19.0

) 88

.2 (1

7.0)

<.001

86.6

(18.1

) 87

.7 (1

7.4)

.18

Depr

essiv

e sym

ptoms

, No.

(%)

De

pres

sion p

rese

nt ba

selin

e (PH

Q ≥1

0)

444 (

71.2)

80

(4.6)

<.0

0145

5 (77

.1)

69 (3

.9)

<.001

Sign

ifica

nt P

HQ so

mat

ic sy

mpt

oms

Sign

ifica

nt P

HQ co

gniti

ve sy

mpt

oms

Ye

s n=

624

No

n=17

23P

valu

e Ye

s n=

590

No

n=17

57P

valu

e

Demo

grap

hics,

No. (

%)

Mean

age (

SD),

year

s 59

.1 (1

2.6)

61.4

(13.0

) <.0

0158

.0 (1

1.7)

61.7

(13.1

) <.0

01Fe

male

sex

256 (

41.0)

49

7 (28

.8)

<.001

233 (

39.5)

52

0 (29

.6)

<.001

Race

W

hite/C

auca

sian

Blac

k/Afric

an A

meric

an

Othe

r

42

7 (68

.6)

162 (

26.0)

33

(5.3)

13

07 (7

6.3)

330 (

19.3)

75

(4.4)

<.001

39

5 (67

.3)

161 (

27.4)

31

(5.3)

13

39 (7

6.6)

331 (

18.9)

77

(4.4)

<.001

Socio

econ

omic

factor

s, No

. (%

)

Ma

rried

33

5 (54

.3)

1066

(62.7

) <.0

0130

7 (53

.1)

1094

(62.9

) .00

1Gr

eater

than

high

scho

ol ed

ucati

on

259 (

42.2)

86

4 (50

.8)

<.001

244 (

42.1)

87

9 (50

.6)

<.001

Havin

g no i

nsur

ance

81

(13.8

) 19

4 (11

.8)

.22

91 (1

6.2)

184 (

11.0)

.00

1W

orkin

g full

- or p

art-t

ime

231 (

37.2)

79

3 (46

.4)

<.001

211 (

36.0)

81

3 (46

.6)

<.001

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

323 (

51.8)

82

2 (47

.7)

.08

303 (

51.4)

84

2 (47

.9)

.15

Hype

rtens

ion

426 (

68.3)

10

61 (6

1.6)

.0141

0 (69

.5)

1077

(61.3

) <.0

01Pe

ri phe

ral a

rteria

l dise

ase

58 (9

.3)

128 (

7.4)

.14

46 (7

.8)

140 (

8.0)

.89

Diab

etes m

ellitu

s 21

9 (35

.1)

453 (

26.3)

<.0

0120

1 (34

.1)

471 (

26.8)

<.0

01Pr

ior A

MI

164 (

26.3)

33

5 (19

.4)

<.001

163 (

27.6)

33

6 (19

.1)

<.001

Prior

angin

a 13

2 (21

.2)

271 (

15.7)

.01

128 (

21.7)

27

5 (15

.7)

<.001

Prior

CAB

G 90

(14.4

) 20

6 (12

.0)

.11

85 (1

4.4)

211 (

12.0)

.13

Pr

ior P

CI

129 (

20.7)

27

9 (16

.2)

.0112

0 (20

.3)

288 (

16.4)

.03

Prior

stro

ke

45 (7

.2)

109 (

6.3)

.44

49 (8

.3)

105 (

6.0)

.05Ch

ronic

rena

l failu

re

76 (1

2.2)

155 (

9.0)

.0262

(10.5

) 16

9 (9.6

) .53

Ch

ronic

lung

dise

ase

122 (

19.6)

18

4 (10

.7)

<.001

100 (

16.9)

20

6 (11

.7)

.001

Chro

nic he

art fa

ilure

10

8 (17

.3)

175 (

10.2)

<.0

0198

(16.6

) 18

5 (10

.5)

<.001

Canc

er (o

ther t

han s

kin)

46 (7

.4)

150 (

8.7)

.30

42 (7

.1)

154 (

8.8)

.21

Smok

ed w

ithin

last 3

0 day

s 23

3 (37

.6)

567 (

33.0)

.04

244 (

41.7)

55

6 (31

.7)

<.001

Mean

bod y

mas

s ind

ex (S

D)

29.7

(6.6)

29

.0 (6

.3)

.0329

.6 (6

.4)

29.1

(6.4)

.10

Fa

mily

histor

y of C

AD

228 (

36.5)

57

4 (33

.3)

.15

218 (

36.9)

58

4 (33

.2)

.10

Curre

ntly r

eceiv

ing tr

eatm

ent fo

r 15

0 (24

.2)

147 (

8.6)

<.001

167 (

28.5)

13

0 (7.4

) <.0

01Cl

inica

l cha

racte

ristic

s ind

ex M

I adm

ission

,

ST

-elev

ation

MI

249 (

39.9)

76

8 (44

.6)

.0423

5 (39

.8)

782 (

44.5)

.05

E jec

tion f

racti

on <

40%

18

1 (29

.0)

427 (

24.9)

.04

159 (

26.9)

44

9 (25

.6)

.53

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

40

0 (76

.0)

87 (1

6.5)

28 (5

.3)

11 (2

.1)

12

52 (8

5.1)

169 (

11.5)

24

(1.6)

26

(1.8)

<.001

39

1 (77

.0)

83 (1

6.3)

23 (4

.5)

11 (2

.2)

12

61 (8

4.7)

173 (

11.6)

29

(1.9)

26

(1.7)

<.001

Dise

ased

vess

els (>

75%

sten

osis)

0

1

2

3

61

(11.7

) 26

8 (51

.2)

101(

19.3)

93

(17.8

)

13

1 (8.6

) 76

3 (50

.3)

340 (

22.4)

28

4 (18

.7)

.12

58

(11.8

) 22

7 (46

.3)

113 (

23.1)

92

(18.8

)

13

4 (8.6

) 80

4 (51

.8)

328 (

21.1)

28

5 (18

.4)

.07

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm

140.2

(32.8

) 13

8.9(3

0.8)

.39

140.0

(32.5

) 13

9.0(3

1.0)

.53

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 83

.4(20

.0)

80.5(

22.1)

.01

83.8(

21.1)

80

.4(21

.7)

<.001

Cathe

teriza

tion a

nd re

vasc

ulariz

ation

data ,

Prim

ary o

r othe

r PCI

35

6 (57

.1)

1069

(62.0

) .03

324 (

54.9)

11

01 (6

2.7)

<.001

Coro

nar y

angio

grap

hy

523 (

83.8)

15

18 (8

8.1)

.0149

0 (83

.1)

1551

(88.3

) .00

1Re

vasc

ulariz

ation

42

1 (67

.5)

1268

(73.6

) .01

387 (

65.6)

13

02 (7

4.1)

<.001

Patie

nt ins

tructi

ons a

t disc

har g

e, No

. (%

)

Card

iac re

habil

itatio

n 26

3 (42

.1)

870 (

50.5)

<.0

0124

0 (40

.7)

893 (

50.8)

<.0

01Di

et co

unse

ling

485 (

77.7)

13

32 (7

7.3)

.83

457 (

77.5)

13

60 (7

7.4)

.98

Exer

cise c

ouns

eling

26

7 (42

.8)

868 (

50.4)

.00

125

2 (42

.7)

883 (

50.3)

.01

Li pid

asse

ssme

nt 67

(10.7

) 26

9 (15

.6)

.0174

(12.5

) 26

2 (14

.9)

.16

Smok

ing ce

ssati

on

199 (

31.9)

48

0 (27

.9)

.06

204 (

34.6)

47

5 (27

.0)

<.001

Clini

cal s

ite in

forma

tion

Mean

QOC

: Num

ber o

f elig

ible i

ndica

tors

5.1 (1

.4)

5.2 (1

.3)

.45

5.1 (1

.3)

5.2 (1

.3)

.20

Mean

QOC

: % of

eligi

ble

indica

tors r

eceiv

ed (S

D)

85.3

(19.0

) 88

.2 (1

7.0)

<.001

86.6

(18.1

) 87

.7 (1

7.4)

.18

Depr

essiv

e sym

ptoms

, No.

(%)

De

pres

sion p

rese

nt ba

selin

e (PH

Q ≥1

0)

444 (

71.2)

80

(4.6)

<.0

0145

5 (77

.1)

69 (3

.9)

<.001

Tabl

e 2 (c

ontin

ued)

– Pa

tient

char

acte

ristic

s of t

he d

epre

ssio

n gr

oups

with

in P

REMI

ER.*


*Dep

ress

ion d

imen

sions

wer

e de

fined

by t

he h

ighes

t sco

re q

uarti

le fo

r som

atic

and

for c

ognit

ive d

epre

ssive

sym

ptom

s. Ab

brev

iation

s: AM

I, ac

ute

myo

card

ial in

farc

-tio

n; B

MI,

body

mas

s ind

ex (k

ilogr

ams/m

eter

s2 ); CA

BG, c

oron

ary

arte

ry b

ypas

s gr

aftin

g; C

AD, c

oron

ary

arte

ry d

iseas

e; P

CI, p

ercu

tane

ous

coro

nary

inte

rven

tions

; PH

Q, p

atien

t hea

lth q

uesti

onna

ire; Q

OC, q

uality

of c

are;

STE

MI,

ST-s

egm

ent e

levat

ion.

Sign

ifica

nt P

HQ so

mat

ic sy

mpt

oms

Sign

ifica

nt P

HQ co

gniti

ve sy

mpt

oms

Ye

s n=

624

No

n=17

23P

valu

e Ye

s n=

590

No

n=17

57P

valu

e

Demo

grap

hics,

No. (

%)

Mean

age (

SD),

year

s 59

.1 (1

2.6)

61.4

(13.0

) <.0

0158

.0 (1

1.7)

61.7

(13.1

) <.0

01Fe

male

sex

256 (

41.0)

49

7 (28

.8)

<.001

233 (

39.5)

52

0 (29

.6)

<.001

Race

W

hite/C

auca

sian

Blac

k/Afric

an A

meric

an

Othe

r

42

7 (68

.6)

162 (

26.0)

33

(5.3)

13

07 (7

6.3)

330 (

19.3)

75

(4.4)

<.001

39

5 (67

.3)

161 (

27.4)

31

(5.3)

13

39 (7

6.6)

331 (

18.9)

77

(4.4)

<.001

Socio

econ

omic

factor

s, No

. (%

)

Ma

rried

33

5 (54

.3)

1066

(62.7

) <.0

0130

7 (53

.1)

1094

(62.9

) .00

1Gr

eater

than

high

scho

ol ed

ucati

on

259 (

42.2)

86

4 (50

.8)

<.001

244 (

42.1)

87

9 (50

.6)

<.001

Havin

g no i

nsur

ance

81

(13.8

) 19

4 (11

.8)

.22

91 (1

6.2)

184 (

11.0)

.00

1W

orkin

g full

- or p

art-t

ime

231 (

37.2)

79

3 (46

.4)

<.001

211 (

36.0)

81

3 (46

.6)

<.001

Medic

al his

tory,

No. (

%)

Hype

rchole

stero

lemia

323 (

51.8)

82

2 (47

.7)

.08

303 (

51.4)

84

2 (47

.9)

.15

Hype

rtens

ion

426 (

68.3)

10

61 (6

1.6)

.0141

0 (69

.5)

1077

(61.3

) <.0

01Pe

ri phe

ral a

rteria

l dise

ase

58 (9

.3)

128 (

7.4)

.14

46 (7

.8)

140 (

8.0)

.89

Diab

etes m

ellitu

s 21

9 (35

.1)

453 (

26.3)

<.0

0120

1 (34

.1)

471 (

26.8)

<.0

01Pr

ior A

MI

164 (

26.3)

33

5 (19

.4)

<.001

163 (

27.6)

33

6 (19

.1)

<.001

Prior

angin

a 13

2 (21

.2)

271 (

15.7)

.01

128 (

21.7)

27

5 (15

.7)

<.001

Prior

CAB

G 90

(14.4

) 20

6 (12

.0)

.11

85 (1

4.4)

211 (

12.0)

.13

Pr

ior P

CI

129 (

20.7)

27

9 (16

.2)

.0112

0 (20

.3)

288 (

16.4)

.03

Prior

stro

ke

45 (7

.2)

109 (

6.3)

.44

49 (8

.3)

105 (

6.0)

.05Ch

ronic

rena

l failu

re

76 (1

2.2)

155 (

9.0)

.0262

(10.5

) 16

9 (9.6

) .53

Ch

ronic

lung

dise

ase

122 (

19.6)

18

4 (10

.7)

<.001

100 (

16.9)

20

6 (11

.7)

.001

Chro

nic he

art fa

ilure

10

8 (17

.3)

175 (

10.2)

<.0

0198

(16.6

) 18

5 (10

.5)

<.001

Canc

er (o

ther t

han s

kin)

46 (7

.4)

150 (

8.7)

.30

42 (7

.1)

154 (

8.8)

.21

Smok

ed w

ithin

last 3

0 day

s 23

3 (37

.6)

567 (

33.0)

.04

244 (

41.7)

55

6 (31

.7)

<.001

Mean

bod y

mas

s ind

ex (S

D)

29.7

(6.6)

29

.0 (6

.3)

.0329

.6 (6

.4)

29.1

(6.4)

.10

Fa

mily

histor

y of C

AD

228 (

36.5)

57

4 (33

.3)

.15

218 (

36.9)

58

4 (33

.2)

.10

Curre

ntly r

eceiv

ing tr

eatm

ent fo

r 15

0 (24

.2)

147 (

8.6)

<.001

167 (

28.5)

13

0 (7.4

) <.0

01Cl

inica

l cha

racte

ristic

s ind

ex M

I adm

ission

,

ST

-elev

ation

MI

249 (

39.9)

76

8 (44

.6)

.0423

5 (39

.8)

782 (

44.5)

.05

E jec

tion f

racti

on <

40%

18

1 (29

.0)

427 (

24.9)

.04

159 (

26.9)

44

9 (25

.6)

.53

Killip

clas

s I (

No he

art fa

ilure

) II (

Hear

t failu

re)

III (P

ulmon

ary e

dema

) IV

(Car

dioge

nic sh

ock)

40

0 (76

.0)

87 (1

6.5)

28 (5

.3)

11 (2

.1)

12

52 (8

5.1)

169 (

11.5)

24

(1.6)

26

(1.8)

<.001

39

1 (77

.0)

83 (1

6.3)

23 (4

.5)

11 (2

.2)

12

61 (8

4.7)

173 (

11.6)

29

(1.9)

26

(1.7)

<.001

Dise

ased

vess

els (>

75%

sten

osis)

0

1

2

3

61

(11.7

) 26

8 (51

.2)

101(

19.3)

93

(17.8

)

13

1 (8.6

) 76

3 (50

.3)

340 (

22.4)

28

4 (18

.7)

.12

58

(11.8

) 22

7 (46

.3)

113 (

23.1)

92

(18.8

)

13

4 (8.6

) 80

4 (51

.8)

328 (

21.1)

28

5 (18

.4)

.07

Mean

systo

lic bl

ood p

ress

ure (

SD),

mm

140.2

(32.8

) 13

8.9(3

0.8)

.39

140.0

(32.5

) 13

9.0(3

1.0)

.53

Mean

hear

t rate

(SD)

, bea

ts pe

r minu

te 83

.4(20

.0)

80.5(

22.1)

.01

83.8(

21.1)

80

.4(21

.7)

<.001

Cathe

teriza

tion a

nd re

vasc

ulariz

ation

data ,

Prim

ary o

r othe

r PCI

35

6 (57

.1)

1069

(62.0

) .03

324 (

54.9)

11

01 (6

2.7)

<.001

Coro

nar y

angio

grap

hy

523 (

83.8)

15

18 (8

8.1)

.0149

0 (83

.1)

1551

(88.3

) .00

1Re

vasc

ulariz

ation

42

1 (67

.5)

1268

(73.6

) .01

387 (

65.6)

13

02 (7

4.1)

<.001

Patie

nt ins

tructi

ons a

t disc

har g

e, No

. (%

)

Card

iac re

habil

itatio

n 26

3 (42

.1)

870 (

50.5)

<.0

0124

0 (40

.7)

893 (

50.8)

<.0

01Di

et co

unse

ling

485 (

77.7)

13

32 (7

7.3)

.83

457 (

77.5)

13

60 (7

7.4)

.98

Exer

cise c

ouns

eling

26

7 (42

.8)

868 (

50.4)

.00

125

2 (42

.7)

883 (

50.3)

.01

Li pid

asse

ssme

nt 67

(10.7

) 26

9 (15

.6)

.0174

(12.5

) 26

2 (14

.9)

.16

Smok

ing ce

ssati

on

199 (

31.9)

48

0 (27

.9)

.06

204 (

34.6)

47

5 (27

.0)

<.001

Clini

cal s

ite in

forma

tion

Mean

QOC

: Num

ber o

f elig

ible i

ndica

tors

5.1 (1

.4)

5.2 (1

.3)

.45

5.1 (1

.3)

5.2 (1

.3)

.20

Mean

QOC

: % of

eligi

ble

indica

tors r

eceiv

ed (S

D)

85.3

(19.0

) 88

.2 (1

7.0)

<.001

86.6

(18.1

) 87

.7 (1

7.4)

.18

Depr

essiv

e sym

ptoms

, No.

(%)

De

pres

sion p

rese

nt ba

selin

e (PH

Q ≥1

0)

444 (

71.2)

80

(4.6)

<.0

0145

5 (77

.1)

69 (3

.9)

<.001


Mortality We first validated the association between formal depression and mortality in the cohort and found that the rates of all cause mortality were higher among the 524 (22.3%) patients with a PHQ-9 score ≥10 (24.2% vs. 16.3%; adjusted Hazard Ratio (HR), 1.41; 95% CI: 1.12-1.76; P=.01) (Supplemental material). Next, we assessed the association between significant somatic and cognitive depressive symptoms and mortality. Event rates for patients with no depressive symptoms, patients with significant somatic but no cognitive symptoms, patients with significant cognitive but no somatic symptoms, and patients in the highest quartiles for both somatic and cognitive symptoms are presented in Table 3. The unad-justed mortality risk for patients with and without significant cognitive depressive symptoms was simi-lar (unadjusted HR per SD increase=1.01; 95%CI, 0.89-1.14) (Table 3 and Figure 3). In contrast, com-pared to patients without significant somatic depressive symptoms, patients with significant somatic depressive symptoms had a higher unadjusted mortality risk (unadjusted HR per SD increase=1.22; 95%CI, 1.08-1.39). After multivariable adjustment, the association between somatic symptoms and mortality was attenuated (adjusted HR per SD increase=1.07; 95% CI, 0.94-1.21; P=.30) (Figure 3). There was no evidence of non-linearity (P value >.25).


Tabl

e 3 –

Even

t rat

es b

y dep

ress

ive sy

mpt

om g

roup

for 4

-yea

r mor

talit

y and

1-ye

ar re

hosp

italiz

atio

n.*

*Dep

ress

ive sy

mpt

om d

imen

sions

wer

e de

fined

by t

he h

ighes

t sco

re q

uarti

le fo

r som

atic

and

for c

ognit

ive d

epre

ssive

sym

ptom

s.

Prog

nosis

4-Ye

ar m

orta

lity

1-Ye

ar re

hosp

italiz

atio

n

Depr

essiv

e sym

ptom

s n

%P

valu

e n

%P

valu

e

No de

pres

sive s

ympto

ms

244/1

508

16.2

<.001

478/1

426

33.5

<.001

Cogn

itive s

ympto

ms

36/21

516

.769

/193

35.8

Soma

tic sy

mptom

s 52

/249

20.9

100/2

3542

.6

Soma

tic an

d cog

nitive

symp

toms

92/37

524

.515

1/337

44.8


RehospitalizationWe also validated that formal depression (PHQ-9 ≥10) in this cohort was associated with a higher risk for rehospitalization (42.7% vs. 34.7%; adjusted HR, 1.23; 95% CI: 1.04-1.46; P=.02) (Supplemen-tal material). When examined by depressive symptom domain, patients with and without significant cognitive depressive symptoms had similar rates of rehospitalization during follow-up (unadjusted HR per SD increase=1.01, 95%CI, 0.93-1.11) (Table 3 and Figure 3). In contrast, compared to pa-tients without significant somatic depressive symptoms, patients with significant somatic depressive symptoms had higher unadjusted rates of rehospitalization during follow-up (unadjusted HR per SD increase=1.22; 95%CI 1.11-1.33), an association which persisted after multivariable adjustment for numerous potential confounders (adjusted HR per SD increase=1.16; 95%CI, 1.06-1.27, P=.01) (Fig-ure 3). There was no evidence of non-linearity (P value >.25).


Figu

re 3

– Mod

el es

timat

es o

f risk

for 4

-yea

r mor

talit

y and

1-ye

ar re

hosp

italiz

atio

n fo

r som

atic

and

cogn

itive

dep

ress

ive sy

mpt

oms.

Abbr

eviat

ions:

CI, c

on-

fiden

ce in

terva

l; HR,

haza

rd ra

tio; P

HQ, p

atien

t hea

lth qu

estio

nnair

e. Mu

ltivar

iable

mode

ls ad

justed

for d

emog

raph

ic (a

ge, s

ex, r

ace)

, clin

ical (d

iabete

s mell

itus,

prior

co

rona

ry ar

tery d

iseas

e, str

oke,

chro

nic re

nal fa

ilure

, chr

onic

lung d

iseas

e, ch

ronic

hear

t failu

re, n

on-sk

in ca

ncer,

curre

nt sm

oking

, bod

y mas

s ind

ex) s

ocioe

cono

mic

(mar

ital s

tatus

, edu

catio

n, ins

uran

ce st

atus a

nd w

orkin

g sta

tus),

AMI s

ever

ity (S

T ele

vatio

n AMI

, left

ventr

icular

ejec

tion

fracti

on <

40%

, hea

rt ra

te), a

nd tr

eatm

ent

(ang

iogra

phy,

reva

scula

rizati

on, p

erce

nt an

d num

ber o

f qua

lity of

care

indic

ators

rece

ived)

varia

bles.

0.5

1.0

2.0

PH

Q S

omat

ic s

ympt

oms

PH

Q C

ogni

tive

sym

ptom

s

Reh

ospi

taliz

atio

n

PH

Q S

omat

ic s

ympt

oms

PH

Q C

ogni

tive

sym

ptom

s

Mor

talit

y

1.01

(0.8

9, 1

.14)

1.22

(1.0

8, 1

.39)

1.01

(0.9

3, 1

.11)

1.22

(1.1

1, 1

.33)

Una

djus

ted

mod

elH

R (9

5% C

I)

0.5

1.0

2.0

1.10

(0.9

7, 1

.25)

1.07

(0.9

4, 1

.21)

1.00

(0.9

1, 1

.09)

1.16

(1.0

6, 1

.27)

Adj

uste

d m

odel

HR

(95%

CI)


DISCUSSION

In this study, we found that 7 out of 10 patients with significant depressive symptoms were not recog-nized during the care and management of their AMI; despite accumulating evidence that depression is associated with higher morbidity and mortality. Among those patients with clinically recognized depression, prominent cognitive depressive symptoms (such as sadness, pessimism, and loss of in-terest) were more likely to facilitate the recognition of depression, while predominantly somatic symp-toms (such as fatigue, loss of energy, and sleep difficulties) were not independently associated with depression recognition. While cognitive symptoms were associated with recognition of depression, they were not independently associated with a higher risk for rehospitalization or death. In contrast, somatic depressive symptoms were associated with a higher risk for mortality and for rehospitaliza-tion, although the association with mortality was attenuated after adjustment for clinical variables. These findings highlight an important dissonance in the current paradigm of care. While recognition of depression is associated with manifestations of cognitive symptoms, prognosis after AMI is associ-ated with somatic depressive symptoms. To our knowledge, this is the first study to jointly examine the relationship between somatic and cognitive depressive symptoms with depression recognition and prognosis among hospitalized AMI patients. These findings extend the findings of prior studies. Several studies in primary care patients have previously reported that the diagnosis of depression in patients with primarily somatic symptoms is particularly challenging because they resemble and are often attributed to the patient’s underlying illness.17, 18, 37 While primary care investigators have long recognized that presentation with somatic symptoms creates barriers to depression recognition and treatment, this issue has not been as-sessed in depressed AMI patients. In contrast to the recognition of depression, preliminary studies have suggested that somatic, and not cognitive, depressive symptoms are associated with worse prognosis.20-23 These few studies, however, have largely evaluated intermediate outcomes such as the metabolic syndrome21 and heart rate variability.20 Moreover, the extent to which these prognostic studies have been able to comprehensively control for potential confounders of somatic and cognitive depressive symptoms, such as socioeconomic factors (marital status, educational level, and insur-ance security), severity of the index AMI (ST-elevation AMI, left ventricular ejection fraction), and AMI treatment (diagnostic cardiac catheterization, PCI or CABG, and quality of care indicators), has been limited.20-22 In this study, we were able to control for these potential confounders of somatic and cogni-tive depressive symptoms and were able to identify a discordance as to which symptom dimension


was associated with recognition and prognosis. There is evidence to suggest that the cognitive symptoms of depression may be mediated by al-terations in serotonin metabolism, whereas the somatic symptoms of depression are affected by de-creased basal ganglia dopamine activity.38 Biochemical studies also suggest that selective serotonin-reuptake inhibitors (SSRIs), which increase serotonin levels, primarily improve cognitive depressive symptoms.38 Thus our study findings may help explain why prior pharmacologic and behavioral in-terventions of depression have not resulted in lower rates of mortality or rehospitalization.12, 19 These trials examined interventions (e.g., SSRI medications, cognitive-behavioral therapy or interpersonal therapy) which primarily target the cognitive features of depression, and their inability to demon-strate reductions in cardiovascular morbidity and mortality may, in part, be due to undertreatment of somatic depressive symptoms. While treating the cognitive symptoms of depressed AMI patients is of unquestioned importance, it may not be sufficient to improve cardiovascular prognosis. Given the effect of exercise training on somatic depressive symptoms39, 40 and the established effects of cardiac rehabilitation in decreasing morbidity and mortality in patients with coronary artery disease,41-43 future clinical trials of depression after AMI may wish to consider a more comprehensive treatment approach that targets both somatic and cognitive depressive symptoms.

Despite accumulating and consistent evidence that depression after AMI is associated with a worse prognosis, and despite efforts to increase its awareness and screening in cardiac patients,6, 7 our results, in this geographically diverse, multi-site, contemporary, ‘real-world’ registry, suggest that de-pression remains unrecognized in most patients hospitalized for an AMI. While therapeutic strategies to modify morbidity and mortality risk for patients with depression after AMI continue to be an active area of investigation, the PHQ-9 instrument remains an important tool in identifying high-risk patients who may benefit from closer monitoring or more aggressive medical therapy. In addition, close col-laboration with specialists involved in treating depression will be essential in formulating individual-ized treatment plans aimed at both reducing patients’ depressive symptom burden and facilitating their recovery following AMI.

Our findings should be considered in light of several potential limitations. First, we assessed depres-sive symptoms with a self-report questionnaire during patients’ hospitalization and did not use a formal psychiatric interview. However, the PHQ-9 has been shown to have high concordance with psychiatric interviews and its ease of use allows for broader dissemination than a Structured Diagnos-


tic Interview.28 Second, depression recognition was determined from data abstraction from patients’ hospital charts. As such, we cannot rule out the possibility that clinicians recognized but did not document their diagnosis of depression in the medical record, which would have underestimated the rates of recognized depression in this study. It is also important to note that thresholds for clinically rel-evant somatic and cognitive depressive symptoms have not been validated and require further study. Finally, a concern common to all observational studies, is the possibility of residual confounding, despite our efforts to adjust for a broad and detailed spectrum of socioeconomic, medical comorbidity, disease severity, and treatment characteristics. More specifically, the presence of somatic symptoms may be overlapping with unmeasured cardiac symptoms or factors related to cardiovascular fitness for which we could not adjust for in the current study.

In conclusion, by discriminating between somatic and cognitive depressive symptoms, we were able to identify a discrepancy between the relative association of these symptoms for depression recogni-tion and AMI outcomes. Although cognitive depressive symptoms were associated with recognition of depression, somatic depressive symptoms were associated with long-term outcomes. Opportunities for active screening and comprehensive treatment programs that address both the somatic and cog-nitive manifestations of depression need to be explored as they may be needed to more effectively treat depression after AMI.


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3. Barth J, Schumacher M, Herrmann-Lingen C. Depression as a risk factor for mortality in patients with coronary heart disease: a meta-analysis. Psychosom Med. 2004;66:802-13.

4. Carney RM, Blumenthal JA, Catellier D, Freedland KE, Berkman LF, Watkins LL, et al. Depression as a risk factor for mortality after acute myocardial infarction. Am J Cardiol. 2003;92:1277-81.

5. Parashar S, Rumsfeld JS, Spertus JA, Reid KJ, Wenger NK, Krumholz HM, et al. Time course of depres-sion and outcome of myocardial infarction. Arch Intern Med. 2006;166:2035-43.

6. Lichtman JH, Bigger JT, Jr., Blumenthal JA, Frasure-Smith N, Kaufman PG, Lesperance F, et al. Depres-sion and Coronary Heart Disease. Recommendations for Screening, Referral, and Treatment. A Science Advisory From the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council on Epidemiology and Prevention, and Interdisciplinary Council on Quality of Care and Outcomes Research. Circulation. 2008;118:1768-75.

7. Davidson KW, Kupfer DJ, Bigger JT, Califf RM, Carney RM, Coyne JC, et al. Assessment and treatment of depression in patients with cardiovascular disease: National Heart, Lung, and Blood Institute Working Group Report. Psychosom Med. 2006;68:645-50.

8. Rumsfeld JS, Ho PM. Depression and cardiovascular disease: a call for recognition. Circulation. 2005;111:250-3.

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10. Amin AA, Jones AM, Nugent K, Rumsfeld JS, Spertus JA. The prevalence of unrecognized depression in patients with acute coronary syndrome. Am Heart J. 2006;152:928-34.

11. Huffman JC, Smith FA, Blais MA, Beiser ME, Januzzi JL, Fricchione GL. Recognition and treatment of depression and anxiety in patients with acute myocardial infarction. Am J Cardiol. 2006;98:319-24.

12. Joynt KE, O’Connor CM. Lessons from SADHART, ENRICHD, and other trials. Psychosom Med. 2005;67 Suppl 1:S63-6.

13. Belmaker RH, Agam G. Major depressive disorder. N Engl J Med. 2008;358:55-68.14. van Praag HM. Kraepelin, biological psychiatry, and beyond. Eur Arch Psychiatry Clin Neurosci. 2008;258

Suppl 2:29-32.


15. Lecrubier Y. Physical components of depression and psychomotor retardation. J Clin Psychiatry. 2006;67 Suppl 6:23-6.

16. Tylee A, Gandhi P. The importance of somatic symptoms in depression in primary care. Prim Care Com-panion J Clin Psychiatry. 2005;7:167-76.

17. Menchetti M, Murri B, Bertakis K, Bortolotti B, Berardi D. Recognition and treatment of depression in primary care: effect of patients’ presentation and frequency of consultation. J Psychosom Res. 2009; 335-41.

18. Barkow K, Heun R, Ustun TB, Berger M, Bermejo I, Gaebel W, et al. Identification of somatic and anxi-ety symptoms which contribute to the detection of depression in primary health care. Eur Psychiatry. 2004;19:250-7.

19. Lesperance F, Frasure-Smith N, Koszycki D, Laliberte MA, van Zyl LT, Baker B, et al. Effects of citalopram and interpersonal psychotherapy on depression in patients with coronary artery disease: the Canadian Cardiac Randomized Evaluation of Antidepressant and Psychotherapy Efficacy (CREATE) trial. JAMA. 2007;297:367-79.

20. de Jonge P, Mangano D, Whooley MA. Differential association of cognitive and somatic depressive symp-toms with heart rate variability in patients with stable coronary heart disease: findings from the Heart and Soul Study. Psychosom Med. 2007;69:735-39.

21. Capuron L, Su S, Miller AH, Bremner JD, Goldberg J, Vogt GJ, et al. Depressive symptoms and metabolic syndrome: is inflammation the underlying link? Biol Psychiatry. 2008;64:896-900.

22. de Jonge P, Ormel J, van den Brink RH, van Melle JP, Spijkerman TA, Kuijper A, et al. Symptom dimen-sions of depression following myocardial infarction and their relationship with somatic health status and cardiovascular prognosis. Am J Psychiatry. 2006;163:138-44.

23. Schiffer A, Pelle A, Smith O, Widdershoven JW, Hendriks EH, Pedersen SS. Somatic versus cognitive symptoms of depression as predictors of all-cause mortality and health status in chronic heart failure. J Clin Psychiatry. In Press.

24. Spertus JA, Peterson E, Rumsfeld JS, Jones PG, Decker C, Krumholz H. The Prospective Registry Evalu-ating Myocardial Infarction: Events and Recovery (PREMIER)--evaluating the impact of myocardial infarc-tion on patient outcomes. Am Heart J. 2006;151:589-97.

25. Specifications Manual for National Hospital Quality Measures, version 2.0. Joint Commission on Accredi-tation of Healthcare Organizations. Accessed March 26, 2009. http://www.jointcommission.org/Perfor-manceMeasurement/PerformanceMeasurement/Historical+NHQM+manuals.htm

26. Spitzer RL, Williams JB, Kroenke K, Linzer M, deGruy FV3rd, Hahn SR, et al. Utility of a new procedure for diagnosing mental disorders in primary care. The PRIME-MD 1000 study. JAMA. 1994;272:1749-56.

27. Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric As-sociation; 1994.


28. Gilbody S, Richards D, Brealey S, Hewitt C. Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. J Gen Intern Med. 2007;22:1596-602.

29. Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA. 1999;282:1737-44.

30. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16:606-13.

31. Harrell FE. Regression Modeling Strategies With Applications to Linear Models, Logistic Regression and Survival Analysis. New York: Springer-Verlag; 2001.

32. Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702-6.

33. Whooley MA, de Jonge P, Vittinghoff E, Otte C, Moos R, Carney RM, et al. Depressive symptoms, health behaviors, and risk of cardiovascular events in patients with coronary heart disease. JAMA. 2008;300:2379-88.

34. Raghunathan TE, Solenberger PW, Van Hoeyk J. IVEware: Imputation and Variance Estimation Software - User Guide. Michigan: Survey Research Center, Institute for Social Research University of Michigan; 2002.

35. Lunceford JK, Davidian M. Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study. Stat Med. 2004;23:2937-60.

36. R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2006.

37. Kirmayer LJ, Robbins JM, Dworkind M, Yaffe MJ. Somatization and the recognition of depression and anxiety in primary care. Am J Psychiatry. 1993;150:734-41.

38. Capuron L, Miller AH. Cytokines and psychopathology: lessons from interferon-alpha. Biol Psychiatry. 2004;56:819-24.

39. Blumenthal JA, Babyak MA, Moore KA, Craighead WE, Herman S, Khatri P, et al. Effects of exercise train-ing on older patients with major depression. Arch Intern Med. 1999;159:2349-56.

40. Blumenthal JA, Babyak MA, Doraiswamy PM, Watkins L, Hoffman BM, Barbour KA, et al. Exercise and pharmacotherapy in the treatment of major depressive disorder. Psychosom Med. 2007;69:587-96.

41. Walther C, Mobius-Winkler S, Linke A, Bruegel M, Thiery J, et al. Regular exercise training compared with percutaneous intervention leads to a reduction of inflammatory markers and cardiovascular events in patients with coronary artery disease. Eur J Cardiovasc Prev Rehabil. 2008;15:107-12.

42. Milani RV, Lavie CJ. Impact of cardiac rehabilitation on depression and its associated mortality. Am J Med. 2007;120:799-806.

43. Witt BJ, Jacobsen SJ, Weston SA, Killian JM, Meverden RA, Allison TG, Reeder GS, Roger VL. Cardiac

rehabilitation after myocardial infarction in the community. J Am Coll Cardiol. 2004;44:988-96.


SUPPLEMENTAL MATERIAL The association between the overall PHQ and 4-year mortality and 1-year rehospitalization.

Table 1 – Model estimates of risk for 4-year mortality and 1-year rehospitalization for depres-sive symptoms (PHQ ≥10).

Abbreviations: CI, confidence interval; HR, hazard ratio; PHQ, patient health questionnaire.

PHQ depressive symptoms

Unadjusted analyses Adjusted analyses

Prognosis HR 95% CI P value HR 95% CI P value

4-Year mortality 1.48 1.20-1.84 <.001 1.41 1.12-1.76 .01

1-Year

rehospitalization 1.37 1.16-1.61 <.001 1.23 1.04-1.46 .02

Figure 1 A, B – Kaplan-Meier plots for 4-year mortality (Figure 1A) and 1-year rehospitalization (Figure 1B) for depressed (PHQ-9 ≥10) and non-depressed groups (PHQ-9 <10). Abbreviations: PHQ, patient health questionnaire.

All-cause mortalityS

urvi

val (

%)

0 6 12 18 24 30 36 42 48

0

10

20

30

40

50

60

70

80

90

100

PHQ <10PHQ ≥10

P<.0001

All-cause rehospitalization

Reh

ospi

taliz

atio

n fre

e (%

)0 3 6 9 12

0

10

20

30

40

50

60

70

80

90

100

PHQ <10PHQ ≥10

P<.0001

A B

All-cause mortality

Sur

viva

l (%

)

0 6 12 18 24 30 36 42 48

0

10

20

30

40

50

60

70

80

90

100

PHQ <10PHQ ≥10

P<.0001

All-cause rehospitalization

Reh

ospi

taliz

atio

n fre

e (%

)

0 3 6 9 12

0

10

20

30

40

50

60

70

80

90

100

PHQ <10PHQ ≥10

P<.0001

A B

Chapter 12

Discussion

12

274 Chapter 12 - Discussion

The rationale of this thesis was based on two observations: the need to develop and distribute ap-propriate disease-specific health status instruments and the need to increase awareness of the psy-chological burden in PAD patients. The ultimate goal of this thesis, however, is to provide researchers and clinicians with reasonable arguments and evidence on the scope of these problems and as a next step, to stimulate initiatives that are able to undertake appropriate action in this context.

The need for a PAD-specific health status instrument

What is known from previous research?The primary goal of PAD treatment is to improve patients’ symptoms, their functioning, and their qual-ity of life. Therefore, considerable agreement exists among researchers and clinicians in the field, that objective outcome measures in PAD management should be complemented with patient-centered outcome assessment. These measures have the potential to gauge the impact of the disease and treatment from a patient’s perspective. Preferably, disease-specific health status instruments should be used to evaluate these aspects, as these questionnaires refer to specific characteristics of the disease and may be more responsive and sensitive to subtle, but clinically relevant nuances and changes. Multiple efforts have been performed to develop PAD-specific health status questionnaires, but currently, there is no golden standard on which instrument to use in outcomes research and in clinical practice. Most instruments that are developed are relatively new, have not extensively been validated or have not been translated into other languages to enable further dissemination of these questionnaires.

Instruments like the Walking Impairment Questionnaire (WIQ),1 the Claudication Scale (CLAUS),2 the Kings College Vascular Quality of Life Questionnaire (VASCUQOL),3 the Sickness Impact Profile-Intermittent Claudication (SIPIC), and the Intermittent Claudication Questionnaire (ICQ)4 are among the most frequently reported PAD-specific health status questionnaires. Although highly relevant and related to the condition of PAD, the 14-item WIQ is an instrument that only assesses walking distance, walking speed, and stair-climbing ability, and does not evaluate other facets of patients’ functioning that may be affected by their PAD (e.g., social or mental functioning) or does not examine the degree of dissatisfaction with their functional limitations. Questionnaires like the CLAUS or the SIPIC were

1


largely based on existing instruments and adapted for use in patients with intermittent claudication: four of the nine subscales of the 47-item CLAUS were derived from the Profile of Mood States, and the 12-item SIPIC was based on the generic Sickness Impact Profile and included those items that may be relevant for patients with PAD. However, the use of parts of larger generic questionnaires to develop a disease-specific instrument requires additional independent validation; evidence of this validation is currently lacking.5

The VASCUQOL and the ICQ on the other hand, were specifically designed for patients with PAD. Both instruments tap a broad range of domains that may be affected by PAD. However, the main concern with the VASCUQOL (25 items) is the fact that it contains both items referring to intermittent claudication, as well as specific items related to critical leg ischemia, making the instrument more generic and possibly less sensitive to subtle changes that may be important for intermittent claudica-tion, but not for critical leg ischemia and vice versa. The 16-item ICQ is a newly developed instrument including items on patients’ symptoms, and their physical, mental, and social functioning. However, this instrument rather lists the frequency of experienced disability on these domains, and does not deal with the degree to which patients are dissatisfied with these limitations. As an example, an 85-year old PAD patient, who is not able to climb several flights or stairs or who is not able to walk more than a kilometer, can still be satisfied with his or her current state of living. This possible discordance cannot be captured by the ICQ.

How this research advances the fieldRecently, a new PAD-specific health status instrument – the Peripheral Artery Questionnaire (PAQ) – was developed and validated in PAD patients that underwent peripheral revascularization.6 The 20-item questionnaire consists of six subscales referring to patients’ physical limitations, symptoms and symptom stability, social function, treatment function, and quality of life. Its construct validity was established against standardized health status instruments, exercise times and ABIs. Furthermore, test-retest reliability, sensitivity to change, and internal consistency of the questionnaire’s subscales were all satisfactorily addressed.6 Its unique features include the treatment satisfaction scale and the inclusion of genuine quality of life items that evaluate the degree of dissatisfaction with patients’ limitations (e.g., “If you had to spend the rest of your life with your peripheral vascular disease the way it is right now, how would you feel about this?”) in addition to the mere registration of patients’ limita-tions. Finally, the questionnaire was successfully used in a larger sample of PAD patients to quantify patients’ improvement in health status following peripheral endovascular revascularization.7


Based on these observations, it was decided to develop and validate a Dutch version of the PAQ in a multicenter registry of PAD patients (Chapter 2). The dimensions of the original instrument were based on similar existing cardiovascular health status questionnaires, unstructured interviews with patients, and consultations with experts in the field. Since its factorial validity was not specifically ad-dressed in prior work with the PAQ, we further validated its underlying factors using the data obtained from the Dutch PAQ. Three clinically meaningful factors were discriminated that explained most of the observed variance in the data: patients’ physical function, their perceived disability, and treatment satisfaction. The reduction in the number of dimensions will likely facilitate its interpretability when focussing on the individual domains in, for example, individual disease-management or in medical decision making. The PAQ Summary score, based on the diverse dimensions of the instrument, may be easy to use for purposes of outcome assessment in clinical trials and for quality assessment or improvement.

The construct validity of the PAQ was also confirmed in the Dutch sample using the generic EQ-5D. The association between relevant clinical indices of PAD and the PAQ subscales and Summary scale demonstrated good clinical validity (Chapter 3), with the PAQ being able to discriminate well between patients with or without symptomatic PAD and its severity as defined by walking distance. In addition, the PAQ subscales and Summary score were directly proportional to the presence and number of risk factors relevant for PAD (i.e., undergoing open vascular surgery, history of congestive heart failure, history of cerebrovascular disease, insulin therapy for diabetes, and renal failure). The generic EQ-5D index8, 9 proved to be less sensitive for these clinical differences as compared with the PAQ. Overall, these observations support the need for further evaluating the applications of the PAQ instrument for PAD care and research (See Table 1).10 11


Tabl

e 1 –

Pote

ntial

appl

icatio

ns o

f the

Per

iphe

ral A

rtery

Que

stio

nnair

e.

Abbr

eviat

ions:

PAD,

per

ipher

al ar

teria

l dise

ase.

Appl

icatio

nEx

ampl

e1.

Quan

tifying

bene

fits of

trea

tmen

t stra

tegies

in cl

inica

l tria

ls.Ev

aluat

e th

e im

pact

of h

igh-d

ose

ator

vasta

tin o

n PA

D pa

tient

s’ he

alth

statu

s in

a do

uble

blind

plac

ebo

cont

rolle

d tri

al.

2.Me

dical

decis

ion m

aking

and i

denti

fying

vulne

rable

PA

D pa

tient

grou

ps th

at ma

y nee

d mor

e inte

nsive

fol

low-u

p.

Patie

nts w

ith lo

w he

alth

statu

s sco

res m

ay b

e at

risk

of a

n ad

vers

e pr

ogno

sis a

nd m

ay re

quire

mor

e agg

ress

ive fo

llow-

up a

nd tr

eatm

ent.

3.Qu

ality

of ca

re im

prov

emen

t, eva

luatin

g dise

ase

mana

geme

nt pr

ogra

ms.

Healt

h sta

tus s

core

s can

be

com

pare

d to

iden

tify re

giona

l diffe

renc

es

betw

een

simila

r dise

ase

man

agem

ent p

rogr

ams a

cros

s site

s.

Evalu

ate

the

impa

ct of

a q

uality

of c

are

impr

ovem

ent p

rogr

am o

n pat

ients’

tre

atm

ent s

atisf

actio

n sc

ores

.4.

Monit

oring

trea

tmen

t suc

cess

in ro

utine

clini

cal c

are.

Iden

tify n

on-re

spon

ders

of p

eriph

eral

endo

vasc

ular r

evas

cular

izatio

n wi

th

PAQ

sum

mar

y cha

nge

scor

es <

8.7

5.A

tool fo

r pati

ent-e

duca

tion,

shar

ed de

cision

mak

ing

and a

n ins

trume

nt for

desig

ning a

tailo

r-mad

e dise

ase

mana

geme

nt pr

ogra

m.

Expla

in to

pat

ients

how

a ce

rtain

treat

men

t may

impa

ct pa

tient

s’ he

alth

statu

s, as

opp

osed

to o

ther

trea

tmen

t mod

alitie

s.

Iden

tify a

reas

of c

once

rns t

oget

her w

ith th

e pa

tient

and

disc

uss w

hat e

xtra

supp

ort is

nee

ded

to a

ddre

ss th

ese

conc

erns

. A p

atien

t with

mor

e pe

rceiv

ed d

isabil

ity (r

egar

ding

his/h

er so

cial fu

nctio

ning,

qua

lity o

f life

, ...)

m

ay n

eed

extra

eva

luatio

n fro

m o

ther

hea

lth ca

re sp

ecial

ists (

socia

l wor

k, m

enta

l hea

lth ca

re p

rofe

ssion

als, …

).


Limitations The current research was a first attempt to validate the use of the PAQ in Dutch PAD patients and should be interpreted against the following potential limitations: first, although both psychometrics and clinical validity were satisfactorily, we only had access to cross-sectional data in a rather hetero-geneous cohort of PAD patients that underwent noncardiac vascular repair and that consisted of both asymptomatic and symptomatic patients. Preferably, uniform cohorts with comparable disease sever-ity and indications for treatment are needed to quantify treatment benefits in terms of health status improvement assessed at multiple assessment points. Ideally, patient-centered evaluations of treat-ment success should be complemented with objective PAD severity indices, such as hemodynamic measurements. In this way, we can establish patient-centered thresholds for treatment success as a function of the prescribed treatment modality and its specific population under study. For example, the rate and magnitude of progress that is obtained in patients with conservative treatment will be substantially different from patients that undergo a successful endovascular revascularization.

Second, we used exploratory factor analysis to establish factorial validity and to reduce the number of factors as this may have the potential to improve clinical interpretability. This analysis identified three factors and as such, is not consistent with the six subscales that were specified in the original instrument. Confirmatory factor analyses in both US and European samples are required to identify whether the three or six factor structure provides the best fit in order to obtain a sound and uniform in-terpretative framework. In the meantime, the Summary PAQ score can be used across populations.

Third, evaluating the validity of a disease-specific health status instrument is not straightforward, as there is currently no golden standard available to which we could compare the current instrument. We did not compare the PAQ against other available PAD-specific instruments but used a standardized and widely used generic instrument, the EuroQol instrument or EQ-5D.8, 9

Future directionsFuture research needs to compare the available PAD-specific health status instruments and identify the most sensitive, reliable, and reproducible instrument that captures a broad range of PAD-specific health status domains. An interpretative framework needs to be established for this instrument as a function of different treatment modalities available for PAD patients; we should be able to explain to patients what health status benefits can be expected from medical management, exercise therapy, endovascular, and surgical procedures and provide them a window on when these benefits can be


expected. In order to realize this, we need to stimulate its use to obtain data from both observational studies including ‘real-world’ patients and data from randomized trials evaluating treatment modalities for PAD and consider health status as an outcome measure that is equivalent to the traditional PAD outcomes (e.g., patency rates, mortality). Further use of a PAD-specific instrument should also be encouraged in daily clinical practice. Cur-rently, clinical decision making is based on patients’ clinical risk profile, history, medical examinations, and patients’ individual stories of burden they experience and how this interferes with their daily lives. To obtain this information from the patient, to discuss medical results and a treatment plan with the patient, there is just a very limited amount of time available. It would be helpful if patients could complete a brief health status questionnaire before they meet their clinician, as these results could be readily used as an instrument to guide clinicians on concerns that are most important to the patient. Both clinician and patient can use this information to obtain an agreed upon treatment plan, and can evaluate the results of this treatment plan by reassessment of patients’ health status scores at subsequent visits. Finally, we need to be able to identify subpopulations that are at increased risk of treatment failure or non-response in terms of their health status. Currently, few clinical indices are consistently associ-ated with adverse health status outcomes. Other than clinical factors – such as socio-economic and psychosocial variables – are possibly more reliably associated with health status responses in car-diovascular patients.12-15 These correlates of health status (e.g., depression or chronic distress) are tangible targets of interventions that can be addressed in order to optimize health status outcomes in cardiovascular patients.


The need to increase awareness of the psychological burden in PAD

Another unaddressed need pertains to PAD patients’ mental health. The second part of this thesis summarizes research findings on the extent to which a substantial group of PAD patients experiences significant depressive symptoms and on the interrelatedness between these symptoms with health status and symptom reporting. A personality trait prone to experiencing depressive feelings may be the distressed personality type (Type D personality). Evidence will be provided on the link between Type D and outcomes following exercise therapy. Finally, preliminary findings will be presented on Type D personality and adverse long-term prognosis in PAD patients.

Depressive symptoms

What is known from previous research?Significant depressive symptoms have been associated with both incident PAD and established PAD.16-21 Approximately one out of five patients with PAD experience significant depressive symp-toms,18-21 while the average prevalence of depression in later life has been estimated to be 1.8% for a major depressive disorder and 9.8% for minor depression in community-dwelling people.22 Although significant depressive symptoms in PAD have been shown to be associated with greater impairment in lower extremity functioning and more functional decline,20, 21 none of the formal guidelines23, 24 that are currently available actually refer to the increased prevalence of depressive symptoms and its as-sociated disability in PAD.

New insights from the present research

“Depressive symptoms tend to persist over time”

Patients with newly diagnosed PAD were followed-up for a period of 18 months. Patients received guideline recommended treatment as appropriate from their vascular surgeon (Chapter 3). During this period of active treatment for their PAD, depressive symptom levels persisted over time, potentially indicating that standard clinical treatment of PAD did not substantially impact on levels of experi-enced depressive symptoms. Approximately 40% of patients experienced either clinical or subclinical

2


depressive symptoms throughout the extended period of follow-up and these patients were more likely to perform worse on a treadmill exercise test and to be without a partner. Importantly, less than one in three patients with significant depressive symptoms received pharmacological treatment for their symptoms and although no data were available on how many patients received counseling for experienced psychological burden, one of the later studies in this thesis (Chapter 5), indicates that numbers for this type of treatment was even lower for a similar group of PAD patients seen at a vas-cular outpatient clinic.

“Depressive symptoms prevail in younger women with PAD”

In a search for which patient groups seem to be particularly at increased risk of experiencing signifi-cant depressive symptoms, we focussed (Chapter 5) on women with premature cardiovascular dis-ease (commonly defined as women <65 years). Younger women have been increasingly recognized as a vulnerable subgroup of patients in terms of depressive symptoms and adverse outcomes in cardiac disease.25-28 In this particular study, we found that younger women with PAD had a 3- to 4-fold increased risk of experiencing significant depressive symptoms, as compared with other gender-age groups. Approximately one in three younger women (compared to 11-16% in other gender-age groups) experienced significant depressive symptoms at baseline and these numbers increased to 40% (compared to 17 to 21% in other gender-age groups) at six months follow-up.

We could not identify mechanisms that explained this increased prevalence of depressive symptoms – adjusting for sociodemographics like education, working or marital status or clinical risk factors such as a history of cardiac disease did not alter our findings. The associations between younger women and depressive symptoms remained significant, even after adjusting for disease severity and clinical risk factors. Importantly, changes in PAD severity or undergoing invasive treatment were not able to explain the association between gender-age and depressive symptoms at six months follow-up. Other possible explanations, such as hormone factors, differential social roles, care responsibilities, and job inequalities need to be evaluated as candidate mechanisms for the association between gender-age and depressive symptoms.29-31

The observation that younger women had among the highest smoking rates (>71%) should be a major concern to clinicians. Apart from the fact that smoking is one of the most important risk fac-tors of PAD, the combination of having depressive symptoms and smoking is especially a difficult


one.32 Smoking can be considered as a way of self-medicating patients’ levels of stress and efforts to stimulate smoking cessation will be challenging: additional supportive strategies and follow-up may be necessary and one should be particularly careful about the possibility that smoking cessation may further exacerbate their depressive symptoms.32

“Depressive symptoms are associated with diminished health status benefits”

From clinical practice and clinical research we know that outcomes in terms of health status and quality of life gains may vary substantially after undergoing a vascular procedure.7, 33-36 One of the most consistent predictors of diminished health status benefits in cardiovascular patients are depres-sive symptoms13, 14, 37 Although the relationship between depressive symptoms and impaired lower-extremity functioning20 and functional decline21 has been addressed within PAD, its association with health status has not been evaluated from a patient’s perspective. Depressive symptoms were consistently associated with diminished health status benefits at one year follow-up in a sample of PAD patients that underwent peripheral endovascular revascularization (Chapter 6). Health status benefits were quantified with the PAD-specific PAQ instrument. Although patients with depressive symptoms improved modestly on most subscales of the PAQ, their qual-ity of life and treatment satisfaction did not improve. Importantly, the extent to which patients with depressive symptoms improved, was significantly reduced as compared with patients without these symptoms. Furthermore, this study indicated that baseline evaluation of depression alone is not suf-ficient. Persistence or worsening of depressive symptoms, and not baseline depressive symptoms, were associated with reduced health status benefits following revascularization. Of note, the majority of patients who experienced worsening of depressive symptoms during follow-up were those who did not classify for significant depressive symptoms at baseline. Explanations for the multidirectional association between depressive symptoms and cardiovascular disease are generally not conclusive and include both biological and behavioral mechanisms. Examples of possible explanations for the particular relationship between depressive symptoms and diminished health status benefits may in-clude worse patency rates,38 that failure to improve led to the development of depressive symptoms, or not being able to be compliant with prescribed cardiovascular prevention strategies.12


“Depressive symptoms and other mood states are intertwined with PAD symptoms”

Symptomatic presentation of PAD is usually associated with typical intermittent claudication com-plaints: muscle pain or discomfort in the calves, reproducibly evoked by exercise and relieved at rest within 10 minutes. However, observations from ‘real-world’ clinical practices indicate that complaints of PAD patients do not always fall into this circumscribed category of intermittent claudication.18, 39 Patients may be rather asymptomatic, present with pain at rest (not to be confused with critical leg ischaemia), or with other atypical complaints (e.g., exertional leg symptoms that do not begin at rest and do not include the calves). The spectrum of leg symptoms in PAD has been shown to correlate poorly with the ABI or other PAD specific indices.18, 40 Factors that were previously found to be associ-ated with PAD complaints were: levels of activity, comorbidities like neuropathy or spinal stenosis, with patients reporting pain at rest having more comorbid conditions and asymptomatic patients being less active.18, 40 The current research (Chapter 8) indicated that having pain at rest or atypical leg symptoms were in-dependently associated with an approximately 2-fold risk of experiencing significant symptoms of de-pression, anxiety, and anhedonia (=lack of positive affect) and having comorbid mood problems, while there was no independent relationship with intermittent claudication and mood states. The finding that somatic symptom reporting is closely related with psychological factors was previously reported in coronary artery disease, where impaired mood is associated with increased symptom reporting and more atypical symptoms.41, 42 Reporting atypical symptoms in PAD should elicit a red flag in clinicians, as these patients may be at increased risk of having an impaired mood status that may warrant fur-ther evaluation or follow-up. Currently, patients with atypical symptoms are more likely to be referred to other specialists (e.g., orthopedic surgeon or rheumatologist) to rule out other pathophysiologic conditions that may explain their complaints. However, referral to mental health care specialists to evaluate the existence of comorbid mood disorders is not a standard clinical practice. The current research may be an impetus for a greater awareness of the observed associations in daily clinical practice and for further replication of our work in future research.

LimitationsThe following potential limitations should be considered when interpreting the findings of the current research. First of all, no causality can be inferred from the present findings. Although three out of five studies were prospective studies, all studies were performed in patients with established PAD


and psychological risk factors did not precede the occurrence of disease. However, all associations persisted even when adjusting for PAD severity indices. Second, repeated vascular laboratory assessment was only available for the gender-age study, and as such, we cannot rule out the possibility that observed associations may have been explained by worsening of patients’ disease. Nevertheless, if this was the case, this would not trivialize our findings as depression is a burdensome condition that requires further evaluation and treatment on its own and requires follow-up because this condition is known to be associated with difficulties to adhere to the treatment regimen,43 increased health care costs,44 and adverse prognosis.45

Third, only the gender-age study was a multi-center study and therefore our findings may not be gen-eralizable to all PAD patients; future research need to replicate our findings across multiple settings and PAD populations. Finally, all studies were observational registries and therefore, we need to take into account the possibility of residual confounding that may have explained our results. However, all these studies included ‘real world’ patients seen in daily clinical practice and this type of research is important, as it may provide us with a more realistic clinical picture of the patients involved, as op-posed to the pre-selected trial populations.46, 47

Depressive symptoms in PAD: a call for recognitionThe current observations on depressive symptoms in PAD are relatively new and poorly disseminated across the scientific and clinical community. Recently, depressive symptoms assessed at baseline have been shown to be associated with worse prognosis in predominantly male PAD patients.38,

45 Add these findings to the chronic experienced burden that patients with depressive symptoms experience over time and it should be clear that ignoring this problem means that we are willing to accept that up to 20% of PAD patients may experience suboptimal benefits from therapies offered, clearly undermining the efforts of clinicians to achieve optimal results in this patient group. Finally, the increased vulnerability of younger women in terms of their mental health, and the challenge of teasing out symptom reporting attributable to actual PAD related symptoms or to psychopathology should be major concerns for clinicians involved in PAD care and will require novel strategies to deal with these problems.


Type D personality or when negative feelings bottle up

What is known from previous findings?One of the explanations why cardiovascular patients are at increased risk of experiencing depressive symptoms may be the possibility that they have a predisposition to depression, or a genetic liability that interacts with environmental factors and may confer a pessimistic personality.48-50 This genetic liability has been suggested to predispose patients both to the development of depression and car-diovascular disease.51 Personality and temperament factors have been shown to be strong correlates of depressive symptoms.52-55 A candidate personality type that has been proposed to result from complex gene-environment interactions is the Type D personality.56, 57 The Type D concept is a dispo-sition that has been formulated in the nineties based on prior literature and clinical observations.58-60 Essentially, patients with a Type D personality tend be pessimistic, tend to experience a broad range of negative feelings and are not able to share these feelings in social interactions.60 This personality construct has been associated with an increased risk of depressive symptoms, impaired health status in both in cardiac and PAD patients53-55, 61 and has been associated with adverse prognosis in cardiac patients.62, 63

What the current research addsType D Personality was associated with diminished benefits in PAD patients that underwent a super-vised exercise protocol (Chapter 9). Type D patients had shorter walking distances both at the start of the treatment and throughout the 1-year follow-up. Compared with non Type D’s, Type D patients improved at a similar pace on walking distance during follow-up, however, their mean walking dis-tances were systematically shorter during follow-up. Type D patients rated the exercise treatment as less beneficial as compared with non Type D’s, and eventually, Type D’s were more likely to undergo an invasive treatment, despite the fact that exercise therapy was the first-choice of treatment. The other Type D study in this thesis (Chapter 10) was a pilot study in PAD patients that evaluated the association between this personality construct and 4-year all-cause mortality. Type D patients had a more than 3-fold risk of death, after adjustment for disease severity and clinical factors.

Limitations and recommendationsBoth Type D studies were observational studies in clinical populations and no causal relationship can be demonstrated based on these findings. Sample size was limited and therefore, our findings need


to be replicated using larger multi-center samples allowing us to address further confounding. Spe-cifically, we did not address the possible mediating role of depressive symptoms in their relationship with personality and outcomes in the analyses. Since Type D personality has been shown to be a robust predictor of depressive symptoms,53, 64 further mediation studies both in clinical and commu-nity samples are indicated to tease out the contribution of depressive symptoms for the association between personality and adverse health outcomes. Ideally, addressing genetic underpinnings of the construct, the contribution of early learning experiences, and its overlap with other personality traits are future research goals worthwhile pursuing as they will add substantially to the foundations of the Type D personality construct.


Holding up a mirror: reflections of patient-centered research in cardiac disease

When comparing the amount of patient-centered research and the body of literature on psychologi-cal burden that is available in cardiac disease with similar research in PAD, the contrast could not be much greater. Both the quantity as well as the advanced level of outcomes research in cardiac populations is tremendous. Considering this different pace of development in outcomes research in cardiac and PAD populations, it is interesting to see that PAD patients’ physical health status may be equally or even more affected, when comparing their health status levels with the health status of patients diagnosed with chronic heart failure (Chapter 11). The advances in outcomes research in cardiac disease could serve as an example on how we could further develop this field within PAD. Disease-specific health status questionnaires in cardiac disease have matured substantially65-67 as clinical interpretative frameworks have been developed and prognostic frameworks for the interpreta-tion of health status scores have been applied across cardiac populations.68-74

Additionally, researchers in the field of cardiac disease are studying multiple candidate psychological prognostic risk factors such as anxiety,75 stress,76 anger,77 and personality factors (e.g., optimism,78 hostility,77 and Type D personality62). Studies on depression and cardiac disease are more clearly dif-ferentiating the nature of this association by focussing on its biological substrates and by identifying racial and gender disparities in terms of patients’ mental health.25, 79 Increased inflammation,80 auto-nomic imbalance,81 increased platelet activation,82 genetic liability,83, 84 and health behaviors85 are all plausible mechanisms that may contribute to the complex and multidirectional relationship between depression and cardiac disease. As an example of these trends, Chapter 12 illustrates that we should look at the phenomenological diversity of depressive symptoms: somatic depressive symptoms (e.g., fatigue, loss of energy, or sleep disturbances), but not cognitive symptoms (e.g., negative mood, hopelessness, or feelings of guilt) are associated with long-term outcomes in acute myocardial in-farction patients. When evaluating what type of symptoms are more easily recognized by clinicians, the study indentified a possible discordance: only cognitive symptoms of depression are associated with depression recognition in depressed hospitalized MI patients. This complexity of the association between depression and outcomes also challenges us in how we should organize and coordinate depression monitoring and treatment. Lessons from past experiences,86 experiences in the field of primary care,87 and further differentiation of the relationship between depression and cardiac disease will enable us to optimize screening and treatment opportunities in cardiac disease.

3


Psychological burden in peripheral arterial disease: a call to action

We are facing multiple challenges in the development of the field of patient-centered outcomes re-search and in addressing the psychological burden in PAD (see Figure 1). Concurrent efforts are needed in research and in clinical practice to further mature this field. First of all, epidemiologic stud-ies on the assessment of psychological factors should be encouraged. Although most information is currently available for depression, this should not withhold us from evaluating diverse modifiable psychological factors such as anxiety or distress in multiple settings and PAD populations. As a next step, we need to be able to measure these characteristics with valid, reliable, and responsive instruments. Identifying subpopulations at risk of experiencing increased psychological burden will be necessary, as these subgroups may be more likely to receive suboptimal benefits from standard clinical treatment. Furthermore, studying patient characteristics x (PAD) treatment interactions will be important to address questions of sources allocation (e.g., “Do depressed patients rather benefit from endovascular revascularization or would supervised exercise therapy and additional counseling be the preferred choice of treatment?”). In these studies, different outcomes need to be assessed, including traditional PAD outcomes (e.g., patency rates, death, rehospitalization) complemented both with patient-centered outcomes (preferably disease-specific health status instruments) and cost-ef-fectiveness evaluations. Finally, using the behavioral and biological candidate mechanisms identified in cardiac research, we need to evaluate which specific pathways are underlying the association between psychological factors and PAD outcomes. How can we translate these developments into clinical practice? First of all, depression affects be-tween 5 to 10% in the general population and is soon becoming the second leading cause of disability worldwide.88, 89 To put this in perspective, prevalence numbers are at least twice as high in PAD, increasing to 30-40% in younger women with PAD, and yet, these facts do not get through to the organization and coordination of PAD management. Several barriers can be identified in this context: mental health concerns still carry a stigma with them, clinicians have to deal with time constraints in clinical practice, and there is a lot of unawareness of mental health issues, how mental health can interfere with somatic care, and how this can weight on our health care system.90 Increasing awareness should start early on in medical training by educating residents on the impor-tance of psychological factors and by organizing rotations in mental health care departments. Psy-

4


chological and socio-economic factors should be documented in the anamnesis when seeing a new patient. Obviously, clinicians involved in PAD care should not become generalists, but should attribute a greater role to non-medical specialists such as nurse practioners and mental health specialists. Col-laborative care protocols should be designed for this purpose including a team led by a depression care manager with the following tasks: focus on case finding, optimizing referral, patient education and activation, organizing care provider education, implementation of guideline-based treatment, and being proactive (depression case finding registry, active follow-up, communication with primary care, access to mental health care specialists).91, 92 To improve current standards of care, we will need to be prepared to evaluate our care by assessing the impact on outcomes and comparing our care across multiple centers. Hopefully, the research findings of the current thesis may act as a leverage to address the multiple challenges in PAD research and clinical practice. Needless to say efforts in research and clinical practice should be combined, as they may act in a synergistic way to achieve success.

Figure 1 – Psychological burden in peripheral arterial disease: a call to action.

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Appendix

Letter to the editor regarding Cherr et al. – Depression and screening

cardiovascular events

300 Appendix

Smolderen KG, Aquarius AE, Denollet J. Depression and screening cardiovascular events. J Gen Intern Med 2008; 23:1543; author reply 1544.

To the editor: - Peripheral arterial disease (PAD) remains an under treated disease1 and information about risk factors and prognosis is poorly disseminated in the population.2 Nevertheless, PAD and coronary artery disease (CAD) patients share the same risk factors and risks of future cardiovascular events in PAD patients are comparable with those in CAD patients.3 Depression may adversely impact prognosis in CAD patients,4 but little is known about depression and prognosis in PAD. Therefore, we read with great interest the work of Cherr and colleagues5 on the relationship between psychological factors and cardiovascular events in PAD. Their study generated interesting findings, but there are also a number of concerns we would like to address here.

First, the screening method used by the authors probably led to an overestimation of depression rates. The General Health Questionnaire is not a depression scale but was developed to assess non-specific psychological distress in community samples,6 and a higher cut-off score (≥8) has been recommended to screen for depressive symptoms in patients with chronic somatic disease.7

Second, 80% of depressed patients received antidepressant therapy. Analyses were not adjusted for type of antidepressant, while studies warn for the use of tricyclic antidepressants in cardiovascular populations because these are associated with an increased risk of myocardial infarction.8, 9 There-fore, we cannot rule out the influence of antidepressant use on adverse outcomes in depressed patients.

Finally, in the adjusted analyses, only a rough parameter of disease severity was included (indica-tion for intervention). Table 2 shows us that the group that underwent revascularization was very heterogeneous in terms of disease severity; indication for intervention ranged from claudication to critical leg ischemia and gangrene or tissue loss. It would have been more appropriate to include the lowest ankle-brachial index in the adjusted analyses due to its strong prognostic value for adverse cardiovascular events in PAD.10 Likewise, in CAD, the relation between depression and increased risk of mortality seems to be confounded by cardiac disease severity or left ventricular dysfunction.11 Future studies examining the link between psychological factors and prognosis in PAD need to take into account reliable indices of disease severity.


REFERENCES


2. Hirsch AT, Murphy TP, Lovell MB, Twillman G, Treat-Jacobson D, Harwood EM, et al. Gaps in public knowledge of peripheral arterial disease: the first national PAD public awareness survey. Circulation 2007;116:2086-94.

3. A randomised, blinded, trial of clopidogrel versus aspirin in patients at risk of ischaemic events (CAPRIE). CAPRIE Steering Committee. Lancet 1996;348:1329-39.

4. van Melle JP, de Jonge P, Spijkerman TA, Tijssen JG, Ormel J, van Veldhuisen DJ, et al. Prognostic as-sociation of depression following myocardial infarction with mortality and cardiovascular events: a meta-analysis. Psychosom Med 2004;66:814-22.


6. Pevalin DJ. Multiple applications of the GHQ-12 in a general population sample: an investigation of long-term retest effects. Soc Psychiatry Psychiatr Epidemiol 2000;35:508-12.

7. Härter M, Woll S, Wunsch A, Bengel J, Reuter K. Screening for mental disorders in cancer, cardiovascular and musculoskeletal diseases. Comparison of HADS and GHQ-12. Soc Psychiatry Psychiatr Epidemiol 2006;41:56-62.

8. Cohen HW, Gibson G, Alderman MH. Excess risk of myocardial infarction in patients treated with antide-pressant medications: association with use of tricyclic agents. Am J Med 2000;108:2-8.

9. Zellweger MJ, Osterwalder RH, Langewitz W, Pfisterer ME. Coronary artery disease and depression. Eur Heart J 2004;25:3-9.


11. van Melle JP, de Jonge P, Ormel J, Crijns HJ, van Veldhuisen DJ, Honig A, et al. Relationship between left ventricular dysfunction and depression following myocardial infarction: data from the MIND-IT. Eur Heart J

2005;26:2650-6.

Dutch summary

304 Dutch summary

Patiënten met perifeer vaatlijden – een vernauwing in de bloedvaten in de benen veroorzaakt door atherosclerose – hebben een verhoogd risico op een slechte prognose. Risicofactoren voor perifeer vaatlijden bestaan uit dezelfde factoren als bij andere atherosclerotische aandoeningen, al lijken roken en diabetes in het bijzonder een belangrijke plaats in te nemen bij het risico op het ontstaan en progressie van perifeer vaatijden. Patiënten met symptomatisch perifeer vaatlijden ervaren ongemak, pijn of krampen tijdens het lopen en merken dat deze klachten verdwijnen bij stilstaan en rust (clau-dicatio intermittens). De aandoening heeft een grote impact op het fysiek functioneren, de ervaren gezondheidstoestand, en kwaliteit van leven.

Hoewel de subjectieve gezondheidstoestand als één van de belangrijkste criteria wordt beschouwd voor het evalueren van behandelsucces en ziektebeloop, is de aandacht voor het subjectieve welbe-vinden en gezondheidstoestand van de patiënt met perifeer vaatlijden slechts recentelijk ontstaan. Voor het meten van behandelsucces vanuit het standpunt van de patiënt wordt bij voorkeur een ziekte-specifieke vragenlijst gebruikt. Echter, er bestaat op dit ogenblik geen gouden standaard voor het meten van ziekte-specifieke gezondheidstoestand bij patiënten met perifeer vaatlijden. Er zijn een aantal nieuwe ziekte-specifieke lijsten in omloop die nog verdere validatie behoeven. In dit proef-schrift werd de Peripheral Artery Questionnaire (PAQ) vertaald en verder gevalideerd in Nederlandse vaatpatiënten uit verschillende medische centra (Hoofdstuk 1). De oorspronkelijke Engelstalige versie van deze ziekte-specifieke lijst bestaat uit 20 items met zes factoren (Fysiek Functioneren, Sympto-men, Symptoom Stabiliteit, Sociale Beperkingen, Tevredenheid met de Behandeling, en Kwaliteit van Leven). De data verkregen uit de Nederlandse studie, werden geanalyseerd met een factoranalyse en bracht het aantal factoren terug van zes naar drie. De drie factoren bestaan uit zowel het Fysieke als het Subjectieve Functioneren, en de Tevredenheid met de Behandeling die patiënten kregen. De meetkwaliteiten van de PAQ waren bevredigend en de samenhang met relevante klinische factoren zoals loopafstand en de aanwezigheid van atherosclerotische risicofactoren was aanzienlijk (Hoofd-stuk 2).

Naast de fysieke beperkingen en de verminderde kwaliteit van leven die gepaard gaan met de ver-nauwingen in de perifere bloedvaten, blijkt uit de bevindingen van dit proefschrift dat patiënten met perifeer vaatlijden te kampen hebben met depressieve klachten. Ongeveer één op drie patiënten blijkt klinisch relevante depressieve klachten te hebben en deze klachten lijken chronisch te zijn, zoals blijkt uit follow-up onderzoek van 18 maanden bij pas gediagnosticeerde patiënten met peri-feer vaatlijden (Hoofdstuk 4). Een belangrijke bevinding uit dit proefschrift is dat deze depressieve


klachten dubbel zo vaak voorkomen bij relatief jongere vrouwen met perifeer vaatlijden (<65 jaar) en dat deze groep ook een verhoogd risico loopt op verergering van de klachten overheen de tijd, vergeleken met andere leeftijds-geslacht groepen (vrouwen ≥65 jaar, mannen <65 jaar, en mannen ≥65 jaar) (Hoofdstuk 5). Bovendien lijken depressieve klachten de belangrijkste voorspeller te zijn van een slechte gezondheidstoestand één jaar nadat patiënten een perifere revascularizatie hebben ondergaan (Hoofdstuk 6). Stemmingsproblemen zijn ook relevant bij het klachtenpatroon dat patiën-ten met perifeer vaatlijden rapporteren. Patiënten die angstig, depressief of een gebrek aan positieve gevoelens ervaren rapporteren vaker atypische klachten met betrekking tot hun perifeer vaatlijden (Hoofdstuk 7). Omdat het typische klachtenpatroon bij perifeer vaatlijden ‘claudicatio intermittens’ is, kan het zijn dat patiënten met perifeer vaatlijden die atypische klachten rapporteren, minder goed herkend worden. Het is daarom belangrijk om weten dat stemmingsproblemen kunnen samenhangen met atypische klachten bij perifeer vaatlijden en een aanleiding vormen tot een verhoogde waak-zaamheid en eventuele verdere evaluatie van aanwezige stemmingsproblematiek.

De neiging om stemmingsproblemen te ervaren kan zijn oorsprong vinden in het hebben van bepaalde persoonlijkheidskenmerken. Een voorbeeld hiervan is de Type D persoonlijkheidheid. Patiënten met een Type D persoonlijkheid ervaren vaak negatieve gevoelens en zijn geneigd om deze emoties op te kroppen. Patiënten met perifeer vaatlijden die zich herkennen in dit persoonlijkheidsprofiel vinden dat ze minder baat hebben bij het volgen van een looptraining en worden vaker invasief behandeld (Hoofdstuk 8). Ook de lange termijn uitkomsten lijken voor Type D patiënten met perifeer vaatlijden minder gunstig te zijn: uit een pilot-studie blijkt dat zij een grotere kans hebben op overlijden na vier jaar follow-up (Hoofdstuk 9). Deze bevindingen zijn nieuw en zijn nog nauwelijks doorgedrongen in de dagelijkse klinische praktijk.

De nood om de aandacht voor de subjectieve gezondheid bij perifeer vaatlijden te vergroten, blijkt des te meer uit een vergelijking van de gezondheidstoestand van patiënten met perifeer vaatlijden met deze van hartfalen patiënten (Hoofdstuk 10). De impact van de aandoening lijkt bij patiënten met perifeer vaatlijden nog groter te zijn dan voor patiënten met hartfalen bij het vergelijken van hun subjectieve fysieke gezondheidstoestand. Omdat we uit de literatuur van andere cardiovasculaire aandoeningen weten dat een verminderd welbevinden en depressie gepaard gaan met een verhoogd risico op een slechte prognose, is het van belang de bevindingen van dit proefschrift onder de aan-dacht te brengen. Bovendien verdienen een verminderd subjectief functioneren en een aandoening als depressie op zichzelf aandacht, en in het bijzonder wanneer dit voorkomt in de context van een

306 Dutch summary

chronische aandoening. Helaas laten recente cijfers bij myocard infarct patiënten zien dat slechts 30% van de klinisch relevante depressieve klachten door de arts herkend worden (Hoofdstuk 11). Bovendien blijken we vooral oog te hebben voor cognitieve depressieve klachten (zoals negatieve stemming, verlies van interesse en suicïdaliteit), maar niet voor somatische depressieve klachten (zoals een gebrek aan eetlust, vermoeidheid en slapeloosheid). Uit onderzoek bij myocard infarct patiënten blijkt echter dat juist deze somatische klachten voorspellend zijn voor een slechte prognose (Hoofdstuk 11).

De resultaten van dit proefschrift wil een stimulus zijn voor verder geavanceerd onderzoek naar me-chanismen die verklaren waarom depressie een significant probleem vormt bij deze patiëntengroep. Bovendien wil het onderzoek verder bijdragen aan de verdere verfijning en validering noodzakelijk om tot een goed ziekte-specifiek instrument te komen die de subjectieve gezondheidstoestand van de patiënt met perifeer vaatlijden gevoelig in kaart kan brengen. Maar nog belangrijker, dit onderzoek wil de discussie openen die nagaat hoe gevolg kan gegeven worden aan de resultaten van dit onder-zoek in de dagelijkse klinische praktijk. Hoe kunnen depressieve klachten beter herkend worden en welke behandelopties voor depressieve klachten zijn er mogelijk om uitkomsten van de behandeling van perifeer vaatlijden te maximaliseren? Hoe kunnen we onze behandeluitkomsten bij deze patiën-tengroep op een betrouwbare manier meten? Een multidisciplinaire aanpak en de uitbouw van een collaborative care model lijken alvast belangrijke onderdelen te zijn die een antwoord kunnen bieden om de mentale last die patiënten met perifeer vaatlijden dragen te verlichten en om voldoende aan-dacht voor de subjectieve gezondheidstoestand van de patiënt te garanderen.

De volgende logische stap lijkt de ontwikkeling van een multidisciplinair disease management pro-gramma voor patiënten met perifeer vaatlijden dat zich zowel richt op de aspecten van het fysieke ongemak, risicomanagement, als de mentale draaglast waarmee patiënten te maken krijgen. Het evalueren van een specifiek disease management programma gebeurt bij voorkeur onder de vorm van een randomized trial, waarin de uitkomsten op het vlak van zowel fysieke als mentale gezondheid en behandelwinst vergeleken wordt met reguliere zorg. Als blijkt dat het specifiek disease manage-ment program kosteneffectief is en aanzienlijk baat brengt voor patiënten met perifeer vaatlijden in verschillende settings, is het wenselijk dit soort initiatieven een breder draagvlak te geven en te implementeren in de klinische praktijk.

Acknowledgements

310 Acknowledgements

Acknowledgements – thesis

Being able to finish and publish this thesis fills me with mixed feelings of excitement, relief, and ner-vousness. I cannot wait to further share my research interest for this patient group with other experts in the field, to write some more reports on the research I have been doing over the past four years, and to meaningfully contribute to the optimalization of PAD management in daily clinical practice.

Before that, I want to present and thank the people who joined me on this 4-year journey. First of all, I want to thank Johan, my mentor – I can vividly remember the moment writing you a letter when the news on the VICI grant came out. Frans Hoogwegt – who served as my inspiring mentor during my clinical training at that time – and I thought that this PhD position would be a good match. We could not have been more right; I feel privileged to have had all the opportunities and freedom to explore the field of cardiovascular research. I am very grateful for all your guidance and support.

Patrick and Maria were the two key figures from the St. Elisabeth Hospital who have been so sup-portive from the very first start of my research. Patrick, your never ending enthusiasm, optimism, and dedication as a vascular surgeon made it a real joy for me to work with you. Thank you for being co-promotor of my thesis, for organizing the best promotion I can imagine, and to disseminate the findings of our work. Maria, thank you for all you hard work; thank you for all the patients you have enrolled. Without your help, I was not able to turn our study into a success story. Thank you also to all the vascular surgeons and other colleagues from the St. Elisabeth Hospital that contributed to this research: what a wonderful team to work with. Annelies, you have really set the bar for the ongoing PAD research in Tilburg. Thank you for introducing me into the world of vascular surgery, for passing on the enthusiasm for this research, and for the memorable coffee breaks at the hospital. I also would like to thank the vascular surgeons, Tini Vingerhoets, Angélique Gillis, the nurses, and all others from the Twee Steden Hospital who helped me with the logistics and enrollment for this study. Many thanks also go to the patients who participated in this research and to the master students that helped me with the data collection. This piece of work could not have been completed without their contributions.

I would like to thank all the colleagues from our research group and two amazing colleagues in partic-ular, who I consider as personal friends: Alien en Brenda. The three of us make a good set. We have started our PhD traineeship at the same time and we made our way through together. I experienced


several hilarious moments with Alien; who could have thought that a trip to Utrecht with a French car could be so exciting? Alien, I am still convinced that you deserve to have your own stand-up comedian show. Brenda, thank you for being such a good friend and colleague. Those divine “rocky road slices” you made, really kept us going: I will keep volunteering to taste your great culinary experiments. Susanne, what a joy and honour to work with you: I admire your professionalism and your hard work. You are a great example for young investigators that are new into the field. You also introduced me to the researchers in the Erasmus Medical Center in Rotterdam, gave me the chance to expand my network and meet with some excellent researchers in the field: Professor Poldermans and Sanne Hoeks in particular, who I enjoyed working with. I look forward continuing this path and sharing our research interest in PAD. Other great researchers and clinicians that crossed my path were Professor Hamming, Joep Teijink, Lotte Kruidenier, and Saskia Nicolaï. Thank you all for having the opportunity to collaborate with you. Thank you also to all the members of my PhD committee; for their interest in my work and for sharing their perspectives with me.

A real turning point in my PhD traineeship was my encounter with Dr. John Spertus from the Mid America Heart Institute, Kansas City. What a wonderful and intense experience. I was able to work for six months with this inspiring mentor and his excellent research group. I cannot thank you enough for sharing your great insights, for your support, for creating so many opportunities, and for your en-thusiasm. Another meticulous researcher and great mentor from this group who I would like to thank is Paul Chan. Other colleagues from the Mid America Heart Institute I would like to thank for the great time I had with them and for the terrific collaboration are Carole, Donna, Kimberly, Elizabeth, Phil, Karen, Beth, Sarah, Fengming, Tracie, Kensey, Yang, Lakshmi, Dr. Safley, and many others. I will not easily forget the Jack Stack’s Barbeques, the Lucky Strike Bowling nights, and pot luck dinners. Tracie and Kurt, Sarah and Robert, and Dr. Spertus and his wife, Sarah, thank you so much for invit-ing me numerous times and for sharing the real Kansas City way of living with me.

Ik wil ook mijn familie en ouders in het bijzonder danken omdat ze altijd voor me klaar stonden met raad en daad. Thank you to my personal friends – Britt, I so much enjoyed our culinary expeditions, wine tasting, and working out sessions. Liesbet, another great person; thank you for our Skype ses-sions during my stay in the US, for your patience and help in lay-outing this thesis. You did a great job. Leen, Hanne, and Wendy – thank you for organizing these wonderful high school and social work school reunions and for keeping in touch.

312 Acknowledgements

Finally, I would like to thank my fiancée, Koen. These four years were a real journey for the both of us. In this period, we have built our own house (yes, with our own bare hands, as few people may seem to believe this), we started up our business that Koen had brought to a real success over the past two years, and we prepared our upcoming wedding over the internet during my stay in the US. It is a joy to see your energy, to have your support, and to work on our projects together.

Publications

316 Publications

Publications

• Smolderen KG, Hoeks SE, Pedersen SS, de Liefde II, van Domburg RT, Poldermans D. Lower-leg symptoms in peripheral arterial disease are associated with anxiety, depression, and anhe-donia. Vasc Med. In Press.

• Smolderen KG, Pelle AJ, Kupper N, Mols F, Denollet J. Impact of peripheral arterial disease on health status: a comparison with heart failure. J Vasc Surg. In Press.

• Aquarius AE, Smolderen KG, Hamming JF, de Vries J, Vriens PW, Denollet J. Type D personal-ity predicts mortality in peripheral arterial disease: a pilot study. Arch Surg 2009;144:728-23

• van den Broek KC, Smolderen KG, Pedersen SS, Denollet J. Type D personality mediates the relationship between remembered parenting and perceived health. Psychosomatics. In Press.

• Hoeks SE, Scholte op Reimer WJ, van Gestel WJ, van Gestel YR, Smolderen KG, Verhagen H, van Domburg RT, van Urk H, Poldermans D. Preoperative cardiac risk index predicts late mor-tality and long-term health status in peripheral arterial disease. Am J Med 2009;122:559-65.

• Smolderen KG, Spertus JA, Reid KJ, Buchanan D, Krumholz HM, Denollet J, Vaccarino V, Chan PS. The association of cognitive and somatic depressive symptoms with depression rec-ognition and outcomes after myocardial infarction. Circ Cardiovasc Qual Outcomes 2009;2:328-37.

• Hoeks SE, Smolderen KG, Scholte Op Reimer WJ, Verhagen HJ, Spertus JA, Poldermans D. Clinical validity of a disease-specific health status questionnaire: the Peripheral Artery Question-naire. J Vasc Surg 2009;49:371-7.

• Smolderen KG, Aquarius AE, Denollet J. Depression and screening cardiovascular events. J Gen Intern Med 2008;23:1544.

• Smolderen KG, Aquarius AE, de Vries, J, Smith RF, Hamming JF, Denollet J. Depressive symp-toms in peripheral arterial disease: a follow-up study on prevalence, stability, and risk factors. J Affect Disord 2008;110:27-35.

• Smolderen KG, Hoeks SE, Aquarius AE, Scholte op Reimer WJ, Spertus JA, Van urk H, Denol-let J, Poldermans D. Further validation of the Peripheral Artery Questionnaire: results from a pe-ripheral vascular surgery survey in The Netherlands. Eur J Vasc Endovasc Surg 2008;36:582-91.

• Denollet J, Smolderen KG, van den Broek KC, Pedersen SS. The 10-item Remembered Re-lationship with Parents (RRP10) scale: Two-factor model and association with adult depressive symptoms. J Affect Disord 2007;100:179-89.


• Smolderen KG, Vingerhoets AJ, Croon MA, Denollet J. Personality, psychological stress, and self-reported influenza symptomatology. BMC Public Health 2007;7:339.

• Denollet J, Aquarius A, Smolderen KG (2006). Ischemische hart- en vaatziekten. In: Kaptein e.a. (eds.): Psychologie en Geneeskunde, Houten/Diegem: Bohn Stafleu Van Loghum, pp. 95-114. [In Dutch]

• Smolderen KG, Vingerhoets AJ. Hospitalisation and Stressful Medical Procedures. In: French, Kaptein, Vedhara & Weinmain (eds.): Health Psychology, 2nd ed, Oxford, UK: Wiley-Blackwell, In Press.

• Hiddema F, Korne D, de Sol K, Vingerhoets AJJM, Smolderen KG (2007). “Don’t worry, get healthy!” Angstreductie als centrale bedrijfsfilosofie in een ziekenhuis. Kwaliteit in Beeld, 13-5. [In Dutch]

• Smolderen KG, Tilburg MAL van, & Vingerhoets AJJM (2004). Het mysterie van de liefde. Ned Tijdschr Geneesk 2004;4:72-3. [In Dutch]

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