Heart Rate Variability and renal organ damage in hypertensive patients

P. Melilllo1, R. Izzo2, N. De Luca2, and L. Pecchia1 1Department of Department of Electronics, Computer Science and Systems,

University of Bologna, Italy 2Departments of Clinical Medicine, Cardiovascular and Immunological

Sciences, Federico II University Hospital, Italy3Faculty of Engineering, University of Nottingham, United Kingdom

paolo.melillo2@unibo.it

EMBC 2012 AbstractThe aim of this research activity is to investigate the relationship between Heart Rate Variability (HRV) and kidney organ damage

P. Melilllo, C. Formisano, U. Bracale, and L. Pecchia

Introduction Methods and materials

Results Discussion Conclusion

STUDY POPULATION:Hypertensive patients

METHODS and MATERIALS:Retrospective analysis on a centralized database

Linear analysis of Heart Rate Variability

EMBC 2012 Da fareThe aim of this research activity is to investigate the relationship between Heart Rate Variability (HRV) and kidney organ damage

P. Melilllo, C. Formisano, U. Bracale, and L. Pecchia

Introduction Methods and materials

Results Discussion Conclusion

STUDY POPULATION:Hypertensive patients

METHODS and MATERIALS:Retrospective analysis on a centralized database

Linear analysis of Heart Rate Variability

EMBC 2012 Study populationHypertensive patients registered in the Campania Salute Network

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Hypertensive subjects referred to the Hypertension Clinic of the University of Naples Federico II from 2000 to 2010

Cardiac and carotid ultrasonography evaluation

24h Holter ECG after one-month antihypertensive therapy wash-out

Exclusion criteria: diagnosis of secondary resistant and/or uncontrolled hypertension;previous CV disease; clinical history of cancer, liver cirrhosis and/or failure;narcotics abuse or lifestyle changes in the last 12 months

Ethical issues• compliance with the Human Study Committee regulations of the University of

Naples "Federico II“;• Informed consent by each subjects.

Introduction Methods and materials

Results Discussion Conclusion

EMBC 2012 Clinical protocolKidney organ damage assessed by Glomerular Filtration Rate

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Glomerular filtration rate (GFR) estimated by the Modification of Diet in Renal Disease (MDRD) formula

no kidney organ damage kidney organ damage

Normal GFR Mild GFR Moderate GFR

GFR≥90 mL/min/1.73 m2 60<GFR<90 mL/min/1.73 m2 GFR≤60 mL/min/1.73 m2

Specifics lifestyle behaviors assessed by a detailed questionnaire

Blood pressure measurement according to the current guidelines

Serum creatinine, fasting plasma glucose, total-cholesterol, and triglycerides measured with the standard methods

Introduction Methods and materials

Results Discussion Conclusion

EMBC 2012 Linear HRV analysisstandard long-term 24-h HRV analysis according to International Guidelines

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia6

TIME DOMAIN MEAURES

FREQUENCY DOMAIN MEASURES

NN INTERVALS TIME SERIES

SPECTRUM

TP: total spectral power of all NN intervals up to 0.4 Hz [ms2]ULF: spectral power of all NN intervals between 0 and 0.003 Hz [ms2]VLF: spectral power of all NN intervals between 0.003 and 0.04 Hz ([ms2]),LF:spectral power of all NN intervals between 0.04 and 0.15 Hz [ms2]HF: spectral power of all NN intervals between 0.15 and 0.4 Hz [ms2]LF/HF: ratio of low to high frequency power (LF/HF),

AVNN : Average of all NN intervals [ms]SDNN : Standard Deviation of all NN intervals [ms]SDANN : Standard Deviation of the averages of NN intervals in all 5 min segments of the entire recording [ms]SDNN IDX: Mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording [ms]rMSSD: square Root of the Mean of the Sum of the Squares of Differences between adjacent NN intervals [mspNN50: percentage of differences between adjacent NN intervals that are longer than 50 ms

Automatic QRS detectorHRV analysis according to International Guidelines* using PhysioNet's HRV Toolkit

Introduction Methods and materials

Results Discussion Conclusion

*Malik, M., J. T. Bigger, et al. (1996). "Heart rate variability: Standards of measurement, physiological interpretation, and clinical use." Eur Heart J 17(3): 354-381.

EMBC 2012 Study sampleCharacteristics of the selected sample of 200 Hypertensive patients

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Introduction Methods and materials

Results Discussion Conclusion

Overall eGFR Normal Mild ModerateAge (years) 62.4±12 56±11.4 63±11.6 69.7±9.2**Sex (male/female, %) 63.5/46.5 64.6/35.4 64.2/35.8 59.4/40.6Family history of hypertension (yes/no, %) 57/43 52.1/47.9 58.3/41.7 59.4/40.6Family history of stroke (yes/no, %) 18/82 20.8/79.2 18.3/81.7 12.5/87.5Smokers (yes/ex/no, %) 17.5/20.5/62 27/17/56 14/23/63 16/19/66Diabetes (yes/no, %) 18/82 18.8/81.2 16.7/83.3 21.9/78.1Diastolic BP (mmHg) 75.6±11.9 73.2±13.8 77.3±11.4* 72.6±9.6Systolic BP (mmHg) 133±22.6 124±23 137±20** 129.5±27Pulse pressure (mmHg) 57.5±17.8 51.3±14 60±16.8* 57±23.2Fasting blood glucose (mmHg) 102.9±24 99.7±31.9 102.9±19.9 107.4±23.5Total Cholesterol (mg/dl) 186±40.5 178.9±36 187.7±40.4 190.3±45.2Beta-blockers (yes/no, %) 33.5/66.5 31.3/68.7 34.2/65.8 34.4/65.6Alphabeta-blockers (yes/no,%) 10/90 10.4/89.6 11.7/88.3 3.1/96.9Alpha-blockers (yes/no, %) 8/92 6.3/93.7 6.7/93.3 15.6/84.4Diuretics (yes/no, %) 43/57 35.4/64.6 40.8/59.2 62.5/37.5*ACE inhibitor (yes/no, %) 37/63 33.3/66.7 40/60 31.3/68.7Dihydropyridine (yes/no, %) 26/74 25/75 25/75 31.3/68.7GFR 77.3±18.5 51.5±6.2 74.3±8.7 101.9±11.8Kidney Involvement (1/2 /3,%) 24/60/16 IMT max 2.24±1.56 1.8±0.76** 2.23±1.21 2.9±2.85Vascular Involvement (no/ thickening/plague, %) 13.5/11/75.5 19/12/69 13/11/76 6/10/84LVMi 130.2±30.8 124.3±25.9 132.8±32.1 128.9±30.9Left Ventricular hypertrophy (no/yes, %) 40.5/59.5 50/50 37.5/62.5 37.5/62.5

Normal GFR Mild GFR Moderate GFR p

Median Percentiles Median Percentiles Median Percentiles

25 th 75 th 25 th 75 th 25 th 75 th

AVNN 848.9 784.9 915.9 852.4 772.6 953.3 876.0 806.3 963.4 0.36

SDNN 119.5 102.3 146.0 111.1 92.2 141.3 113.8 98.3 141.1 0.31

SDANN 108.6 90.2 137.0 99.8 78.4 129.4 105.6 86.0 132.4 0.33

SDNN IDX 51.43 43.87 58.77 47.10 40.78 61.04 45.04 36.86 58.25 0.24

RMSSD 30.06 24.50 37.74 30.53 22.41 42.08 33.67 24.67 42.06 0.50

pNN50 7.68 3.94 11.74 7.88 2.73 17.71 10.06 4.07 12.85 0.66

TOTPWR 16124 11012 23626 13784 9042 21607 15175 10303 24713 0.36

ULF 12379 8864 18679 10708 7103 18480 12001 8215 20217 0.36

VLF 1592 1195 2368 1422 961 2405 1260 813 1959 0.11

LF 711.2 485.8 1102.0 600.6 370.2 916.7 577.2 373.5 925.4 0.15

HF 471.3 298.8 724.5 493.4 201.8 801.5 549.7 28.8 1230.2 0.44

LF/HF 1.44 1.17 2.10 1.25 0.91 1.75 0.87 0.72 1.25 <0.001

EMBC 2012 HRV and GFRHRV measures in the three patient groups

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Introduction Methods and materials

Results Discussion Conclusion

EMBC 2012 Adjusted modelHRV measures in the three patient groups

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Introduction Methods and materials

Results Discussion Conclusion

Compared groups HRV measure,factor or covariate β p OR 95% CI of OR

Normal eGFR versus Moderate eGFR

Intercept 5.856 0.020 LF/HF 0.977 0.033 2.655 1.079 to 6.531

Systolic BP -0.005 0.645 0.995 0.973 to 1.017

Age -0.104 <0.001 0.901 0.854 to 0.951

Absence of family history of hypertension 1.153 0.031 3.168 1.109 to 9.050

Mild eGFR versus Moderate eGFR

Intercept 0.322 0.885 LF/HF 0.993 0.023 2.699 1.149 to 6.341

Systolic BP 0.021 0.040 1.021 1.001 to 1.042

Age -0.051 0.034 0.950 0.906 to 0.996

Absence of family history of hypertension 0.758 0.091 2.134 0.887 to 5.138

EMBC 2012 Depressed HRVAutonomic imbalance and kidney damage

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Significant decreased LF/HF (marker of sympatho-vagal balance) in moderate eGFR patient group

Adjustment for factor / covariate contributing to the development of renal TOD Expected influence of age and hypertension

Previous study (Gargia-Gargia, 2012) failed to show significant relationship maybe because of the lack of frequency domain analysis

Consistence with findings of two recent studies:• lower HRV (particularly, frequency domain measures) associated with higher risk of

progression to end-stage renal disease;• autonomic imbalance may lead to kidney damage

Garcia-Garcia A, Gomez-Marcos MA, Recio-Rodriguez JI, Patino-Alonso MC, Rodriguez-Sanchez E, Agudo-Conde C, Garcia-Ortiz L: Office and 24-hour heart rate and target organ damage in hypertensive patients. BMC Cardiovasc Disord 2012, 12(1):19.Chandra P, Sands RL, Gillespie BW, Levin NW, Kotanko P, Kiser M, Finkelstein F, Hinderliter A, Pop-Busui R, Rajagopalan S et al: Predictors of heart rate variability and its prognostic significance in chronic kidney disease. Nephrol Dial Transplant 2012, 27(2):700-709.Brotman DJ, Bash LD, Qayyum R, Crews D, Whitsel EA, Astor BC, Coresh J: Heart rate variability predicts ESRD and CKD-related hospitalization. J Am Soc Nephrol 2010, 21(9):1560-1570.

Introduction Methods and materials

Results Discussion Conclusion

EMBC 2012 ConclusionHRV as risk factor or marker of progression of kidney organ damage?

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

HRV depression associated with kidney organ damage

Decreased LF/HF corroborates the role of autonomic imbalance in kidney damage

Autonomic imbalance may lead kidney damage

The mechanisms by which abnormal autonomic balance may lead to organ damage are unclear

Further studies are need ed:• longitudinal and prospective to investigate causal relationship• nonlinear and/or point process time-frequency analysis to extract more information

from HRV• other non-invasive parameters of ANS activity to provide addition information• automatic machine learning to develop classifiers able to detect / assess progression of

kidney disease

Introduction Methods and materials

Results Discussion Conclusion

EMBC 2012 Question timeThank you for your attention

P. Melilllo, R. Izzo, N. De Luca, and L. Pecchia

Brief bibliography:Similar studies• Chandra P, et al. Nephrol Dial Transplant 2012, 27(2):700-709.• Brotman DJ, et al. J Am Soc Nephrol 2010, 21(9):1560-1570.• Garcia-Garcia A, et al. BMC Cardiovasc Disord 2012, 12(1):19.Automatic classification• Pecchia L, et al. IEEE Trans Bio Med Eng 2011, 58(3):800-804.Other ANS parameters• Melillo P, Pecchia L, et al. Biomed Eng Online 2012, 11(1):40.Nonlinear and Point HRV analysis• Melillo P, et al. Biomed Eng Online 2011, 10(1):96.• Kodituwakku S, et al. Med Bio Eng Comput 2012, 50(3):261-275.

For further details, please refer also to: “Design and assessment of disease management program for cardiac patients via enhanced telemedicine with data-mining and pattern recognition” Ph.D. Thesis by Paolo Melillo, also under press in a book edited by Lambert Academic Publishing ISBN: 978-3-659-22103-3

Introduction Methods and materials

Results Discussion Conclusion