Incident Heart Failure Hospitalization and Subsequent Mortality inChronic Heart Failure: A Propensity-Matched Study

Ali Ahmed, MD, MPH,University of Alabama at Birmingham, and VA Medical Center, Birmingham, AL

Richard M. Allman, MD,Birmingham/Atlanta VA Geriatric Research, Education, and Clinical Center and the University ofAlabama at Birmingham

Gregg C. Fonarow, MD,University of California in Los Angeles, Los Angeles, CA

Thomas E. Love, PhD,Case Western Reserve University, Cleveland, OH

Faiez Zannad, MD, PhD,Université Henri Poincaré, Nancy, France

Louis J. Dell’Italia, MD,University of Alabama at Birmingham, and VA Medical Center, Birmingham, AL

Michel White, MD, andMontreal Heart Institute and University of Montreal, Montreal, Canada

Mihai Gheorghiade, MDNorthwestern University, Chicago, IL

AbstractBackground—Hospitalization due to worsening heart failure (HF) is common and is associatedwith high mortality. However, the effect of incident HF hospitalization (compared to no HFhospitalization) on subsequent mortality has not been studied in a propensity-matched population ofchronic HF patients.

Methods and Results—In the Digitalis Investigation Group trial, 5501 patients had no HFhospitalizations (4512 alive at two years after randomization) and 1732 had HF hospitalizationsduring the first two years (1091 alive at two years). Propensity scores for incident HF hospitalizationduring the first two years after randomization were calculated for each patient, and were used tomatch 1057 (97%) patients who had two-year HF hospitalization with 1057 patients who had no HFhospitalization. We used matched Cox regression analysis to estimate the effect of incident HFhospitalization during the first two years after randomization on post-two-year mortality. Comparedwith 153 deaths (rate, 420/10,000 person-years) in the no HF hospitalization group, 334 deaths (rate,964/10,000 person-years) occurred in the HF hospitalization group (hazard ratio 2.49; 95%

Name and complete address for correspondence: Ali Ahmed, MD, MPH, University of Alabama at Birmingham, 1530 3rd Ave South,CH-19, Ste-219, Birmingham AL 35294-2041; Telephone number: 1-205-934-9632; Fax number: 1-205-975-7099; Email:aahmed@uab.edu.Author ContributionsDr. Ahmed conceived the study hypothesis and design. Dr. Ahmed wrote the first and subsequent drafts of the manuscript incorporatingimportant intellectual content from all authors. Dr. Ahmed had full access to the data and conducted the statistical analyses in consultationwith Dr. Love. All authors interpreted the data, participated in critical revision of the paper and approved the final version of the article.

NIH Public AccessAuthor ManuscriptJ Card Fail. Author manuscript; available in PMC 2009 November 1.

Published in final edited form as:J Card Fail. 2008 April ; 14(3): 211–218. doi:10.1016/j.cardfail.2007.12.001.

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confidence interval 1.97–3.13; p<0.0001). Respective hazard ratios (95% confidence intervals) forcardiovascular and HF mortality were respectively 2.88 (2.23–3.74; p <0.0001) and 5.22 (3.34–8.15;p <0.0001).

Conclusions—Hospitalization due to worsening HF was associated with increased risk ofsubsequent mortality in ambulatory patients with chronic HF. These results highlight the importanceof HF hospitalization as a marker of disease progression and poor outcomes in chronic HF,reinforcing the need for prevention of HF hospitalizations and strategies to improve post-dischargeoutcomes.

KeywordsHeart failure; hospitalization; mortality; propensity scores

Heart failure (HF) is common and is a main reason for hospitalizations among older adults.1With the aging of the United States population, the prevalence of HF is projected to doubleover the next several decades, further increasing the burden of HF hospitalization. Data fromhospitalized HF patients suggest that HF hospitalization is associated with high in-hospital,and short- and long-term post-discharge mortalities.2–6 However, little is known about theeffect of incident HF hospitalization, compared with no HF hospitalization, on subsequentmortality in chronic HF. In this study, we test the hypothesis that incident HF hospitalizationwould be associated with increased subsequent mortality in a propensity score-matched cohortof ambulatory chronic HF patients.

METHODSStudy Design and Patients

This is a post-hoc propensity-matched study of the Digitalis Investigation Group (DIG) trial,conducted in 302 centers (186 in the US and 116 in Canada) during 1991–1993.7 Detaileddescription of the rationale, design, implementation, patient characteristics and results of theDIG trial have been reported elsewhere.7 Of the 7888 ambulatory chronic HF patients withnormal sinus rhythm enrolled in the DIG trial, 6800 had ejection fraction ≤45%.

Heart Failure HospitalizationDuring a mean follow up of 37 months, 5128 (66%) patients were hospitalized from all causes,of whom 2287 (45%) were due to worsening HF. Of the 2287 HF hospitalizations, 1732 (76%)occurred during the first two years after randomization. After excluding 641 (37%) patientswho either died (n=629) or were lost to follow up (n=12) during the first two years, there were1091 patients who had HF hospitalization during the first two years of follow up (Figure 1).Of the 5501 patients without any HF hospitalization, we excluded 989 (18%) patients whoeither died (n=941) or were lost to follow up (n=48) during the first two years afterrandomization. We matched 1057 (97%) of the 1091 patients who had HF hospitalizationsduring the first two years with 1057 patients who had no HF hospitalizations by theirpropensities to have HF hospitalizations during the first two years. Thus, our analysis focuseson a cohort of 1057 pairs of propensity score matched patients (Figure 1). DIG investigatorsascertained incident hospitalizations and the primary diagnoses leading to hospitalizations byreviewing patients’ charts. There was no centralized adjudication of incident hospitalizations,including those due to worsening HF.

Primary and Secondary OutcomesThe primary outcome was all-cause mortality after the second year of follow up. In addition,we also studied mortalities due to cardiovascular causes, HF, due to non-HF cardiovascular

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causes, and non-cardiovascular causes. Study investigators, who were blinded to patients’treatment assignment, ascertained causes of death. Vital status was collected up to December31, 1995 and was ascertained for 99% of the patients.8 The median follow up in this analysiswas 16 months from the end of first two years. As in randomized clinical trial, the current studywas designed (i.e. a risk-adjusted balanced study cohort was assembled using propensity scorematching) without access to the mortality data.

Estimation of Propensity Scores and MatchingBecause there were significant differences in baseline patient characteristics between patientswho had and did not have a HF hospitalization during the first two years of follow-up (Table1, left hand panels), we used propensity score matching to achieve balance. The propensityscore is the conditional probability of receiving an exposure (e.g. hospitalization for worseningHF) given a vector of measured covariates, and can be used to adjust for selection bias whenassessing causal effects in observational studies.9–15 We estimated propensity scores for HFhospitalization during the first two years for all patients using a non-parsimonious multivariablelogistic regression model. In that model, all baseline patient characteristics displayed in Table1 (except those marked as derived variables) and clinically plausible interactions were includedas covariates. The use of baseline covariates at randomization in the model allowed us toestimate prospectively propensity scores for incident HF hospitalizations.

Our propensity score model discriminated well between patients with and without HFhospitalization (c statistic=0.73). We then used propensity score, to match each patient withHF hospitalization with another patient without HF hospitalization, but who had a very similarpropensity score, thus matching 1057 (97% of the 1091 patients with HF hospitalization duringthe first two years) patients to 1057 patients without HF hospitalization.13–16 We used a greedymatching algorithm, which first looked for matches to five decimal places, and those matchedwere removed from the files.13, 14, 17 Then, the process was repeated to four, three, two andone decimal places. We assessed residual imbalances in baseline covariates between treatmentgroups after propensity score matching by estimating absolute standardized differences (Figure2).13, 18, 19 Standardized differences quantify the bias in the means (or proportions) ofcovariates across the groups, expressed as a percentage of the pooled standard deviation.

Statistical AnalysisWe used chi-square tests and independent sample t-tests, as appropriate, for descriptive analysisto compare baseline characteristics between pre-match patients with and without HFhospitalization. For descriptive analysis of post-match cohorts, McNemar tests and paired-sample t-tests were used as appropriate. We used Kaplan-Meier survival analyses, and matchedCox proportional hazards models to estimate the association between incident HFhospitalizations during the first two years of follow up and subsequent mortality. We confirmedthe assumption of proportional hazards by a visual examination of the log (minus log) curves.

Although our propensity score match achieved excellent balance in all measured covariatesbetween patients with and without HF hospitalization, we could not rule out bias due tounmeasured confounders. Like any non-randomized study, the conclusions of our study maybe sensitive to potential hidden confounders. Therefore, we conducted formal sensitivityanalyses to describe the weight of our evidence by quantifying the degree of hidden bias thatwould need to be present to invalidate our main conclusions.20, 21 We then examined theassociation of HF hospitalization and mortality in subgroups of patients in the pre-match cohort,adjusted for raw propensity scores. All statistical tests were evaluated using 2-tailed 95%confidence levels, and data analyses were performed using SPSS for Windows version 14.22

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ResultsThe median age of the 2114 propensity score-matched patients was 65 years, (range 22–92),621 (29%) were women and 398 (19%) were non-whites. Baseline patient characteristics byHF hospitalizations, before and after propensity score matching are displayed in Table 1 andFigure 2. Before matching, patients with incident HF hospitalizations were likely to be olderand sicker with a higher burden of comorbidity. After matching, patients with and without HFhospitalization were balanced in all of measured baseline covariates (Table 1 and Figure 2).Our propensity score matching reduced absolute standardized differences for all observedcovariates below 10% (most were below 5%), demonstrating substantial improvement incovariate balance across the groups (Figure 2).

Total MortalityDuring a median follow-up of 16 months, 487 (23.0%) patients died from all causes, 411(19.4%) due to cardiovascular causes, 202 (9.6%) died due to HF, 209 (9.9%) due tocardiovascular causes other than HF, and 76 (3.6%) died from non-cardiovascular causes.Kaplan-Meier plots for mortalities due to all causes, cardiovascular causes, and progressiveHF are displayed in Figures 3 (a, b and c).

Mortality due to all causes occurred in 153 patients without HF hospitalization during a totalof 3,644 years of follow up (mortality rate, 420/10,000 person-yearss) and 334 patients withHF hospitalization during a total of 3,463 years of follow up (mortality rate, 964/10,000 person-yearss; hazard ratio [HR], when patients with HF hospitalization were compared with thosewithout, 2.49, 95% confidence interval [CI], 1.97–3.13; p <0.0001; Table 2). Our sensitivityanalysis suggests that an unmeasured binary covariate would need to increase the odds of HFhospitalization by >91% to explain away this association (z-statistic=7.02; 2-tailed p=0.0001),suggesting that these results are not sensitive to a hidden binary variable.

In the full (pre-match) cohort (n=5,603), 11% and 32% of patients without and with HFhospitalizations subsequently died (unadjusted HR, 3.29, 95% CI, 2.87–3.77; p <0.0001). Theassociation remained strong and significant when we adjusted for all baseline covariates (HR,2.65, 95% CI, 2.30–3.05; p <0.0001), or propensity scores (HR, 2.61, 95% CI, 2.25–3.02; p<0.0001).

Cardiovascular MortalityMortality due to cardiovascular causes occurred in 296 (rate, 855/10,000 person-yearss) and115 patients (rate, 316/10,000 person-yearss) with and without HF hospitalizations,respectively (HR, 2.88, 95% CI, 2.23–3.74; p <0.0001; Table 2). A hidden unmeasuredcovariate would need to increase the odds of HF hospitalization by >110% to explain awaythis association (z=6.79; p <0.0001).

HF MortalityMortality due to HF occurred in 162 patients (rate, 468/10,000 person-years) and 40 patients(rate, 110/10,000 person-years), respectively, with and without HF hospitalizations (HR, 5.22,95% CI, 3.34–8.15; p <0.0001; Table 2). The odds of HF hospitalization must be increased by>140% by an unmeasured covariate to confound this association (z=6.79; p<0.0001).

Mortality due to Other CausesMortality due to cardiovascular causes other than HF occurred in 134 (rate, 387/10,000 person-years) and 75 patients (rate, 206/10,000 person-years) with and without and HFhospitalizations, respectively (HR, 1.89, 95% CI, 1.36–2.63; p <0.0001; Table 2).

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HF hospitalization had no effect on mortality due to non-cardiovascular causes, which occurredin 38 patients in each group, respectively during 3,463 years (110/10,000 person-years) and3,644 years (104/10,000 person-years) of follow up, respectively in patients with and withoutHF hospitalization (HR, 1.21, 95% CI, 0.70–2.08; p =0.493; Table 2).

Subgroup AnalysesHF hospitalization significantly increased subsequent total mortality in all the subgroups ofHF patients studied (Figure 4), regardless of age, sex, race, HF etiology, left ventricular ejectionfraction, New York Heart Association functional class, comorbidities and use of medications.There were no significant interactions between HF hospitalization and any of the subgroups,except for diabetes (p for interaction=0.050). This subgroup interaction, however, was nolonger significant when adjusted for other covariates (adjusted p=0.150).

DiscussionThe findings of the current analysis demonstrate that incident hospitalization due to worseningHF is associated with significant increase in subsequent mortality in ambulatory chronic HFpatients. These findings are important, as worsening HF is the number one reason forhospitalization for HF patients. Further, HF is the number one reason for hospitalization amongolder adults. Most HF patients are 65 years and older, and with the aging of the population, thenumber of elderly HF patients is expected to double over the next several decades.

HF is a progressive disorder with poor prognosis.23–25 Common identifiable causes of HFhospitalizations include acute coronary syndrome, uncontrolled hypertension, arrhythmias anduse of anti-arrhythmic drugs, pulmonary infections, and noncompliance with medications anddiet.26–28 Our data suggest that HF hospitalization may be a marker of disease progression andpoor prognosis in HF. There is cumulative evidence that serum troponin levels may be elevatedin HF, which in turn may be associated with worsening HF, HF hospitalization, and mortality.29, 30 Elevated serum troponin levels in acute HF have been associated with increased risk ofsubsequent mortality and hospitalizations.31 Other explanations for poor post-dischargeoutcomes include bed rest and restricted mobility during hospitalizations.32, 33

As the number one reason for hospitalization among population ≥65 years, HF hospitalizationis already a cause for significant burden to the health care system. HF hospitalizations alsosignificantly impair quality of life of HF patients, most of whom are older adults. Our findingsfurther highlight the negative consequence of HF hospitalizations and suggest that theprevention of HF hospitalizations should be a high priority for clinicians caring for HF patients.Clinicians should optimize the use of interventions proven to reduce HF hospitalizations, toimprove quality of life and reduce burden on health care system. Whether use of such drugswould also reduce subsequent mortality in these patients is currently unknown. Cliniciansshould also counsel ambulatory chronic HF patients on the importance of compliance withmedications and salt and fluid restrictions, use evidence-based HF therapies as appropriate,and treat comorbidities such as hypertension, coronary artery disease, hypertension and chronickidney disease.

The findings of our study support the use of HF hospitalization as a hard endpoint in HF trials.In the SOLVD trial, the survival benefit of enalapril was observed only among the patientswho were hospitalized at least once during the trial 34. Because treatment effects often dependon severity or stage of disease,35 a history of HF hospitalization may be used as an inclusioncriteria in future HF trials. This is important as event rates in contemporary systolic HF patientsreceiving optimal therapy and in those with diastolic HF (clinical HF with normal or nearnormal ejection fraction) are expected to be low. Future studies are need to investigate whethercardiac resynchronization therapy during hospitalization and the prescription of beta-blockers

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at the time of hospital discharge might favorably reduce post-discharge mortality compared topatients without HF hospitalizations.36–38

A recent post hoc analysis of CHARM database demonstrated that post-baseline “dischargefor first hospitalization for HF” was independently associated with increased mortality (HR3.15; 95% CI, 2.83–3.50; p<0.0001).39 This is very similar to the association observed in thecurrent study (HR, 2.49, 95%CI, 1.97–3.13; p<0.0001) and provide cumulative evidence ofthe deleterious effect of HF hospitalization on subsequent survival in chronic HF.

Our study has several limitations. Like any non-randomized study, propensity score analysiscannot account for confounding due to unmeasured covariates. However, our sensitivityanalyses suggest that our findings were rather insensitive to hidden biases. We were able tofind near-exact matching for about 97% of patients with HF hospitalization. This is in contrastto about 60% adequate matching in other studies 17, 19. The results of our study are based onpredominantly white, male, and relatively younger HF patients with normal sinus rhythm.Therapy for systolic HF has evolved since the DIG trial was conducted. We also had no dataon use of beta-blockers and aldosterone antagonists. Lack of data of diuretic dosage is anotherlimitation of our study.40

ConclusionsIncident hospitalization due to worsening HF was associated with significant increase in all-cause and cardiovascular mortality in a wide spectrum of ambulatory patients with chronicmild to moderate systolic and diastolic HF. These findings highlight the importance of HFhospitalization as a marker of disease progression and poor outcomes in HF, and emphasizeon the need for prevention of HF hospitalization, and treatment strategies for hospitalized HFpatients to improve post-discharge outcomes.

Acknowledgments“The Digitalis Investigation Group (DIG) study was conducted and supported by the NHLBI in collaboration with theDIG Investigators. This Manuscript was prepared using a limited access dataset obtained by the NHLBI and does notnecessarily reflect the opinions or views of the DIG Study or the NHLBI.”

Funding/Support

Dr. Ahmed is supported by the National Institutes of Health (NIH) through grants from the National Heart, Lung, andBlood Institute (1-R01-HL085561-02 and P50-HL077100). Dr. Allman is supported by grants R01-AG15062 fromthe National Institute on Aging. Dr. Dell’Italia is supported by a Specialized Center for Clinically Oriented Research(SCCOR) in Cardiac Dysfunction grant P50HL077100 from the National Heart, Lung, and Blood Institute and theOffice of Research and Development, Medical Service, Department of Veteran Affairs.

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Figure 1.Flow chart for the assembly of matched cohort

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Figure 2.Absolute standardized differences of baseline covariates between patients with and withouthospitalization for heart failure, before and after propensity score matching

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Figure 3.Kaplan-Meier plots for cumulative risk of death due to (a) all causes, (b) cardiovascular causes,and (c) progressive heart failure (HF). HFH, heart failure hospitalization; HR, hazard ratio; CI,confidence interval.

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Figure 4.Hazard ratios (HR) and 95% confidence intervals (CI) for post two-year all-cause mortalitywhen heart failure hospitalization (HFH) during the first two years was compared with no HFHin subgroups of patients with chronic heart failure (ACE, angiotensin-converting enzyme;HFH, heart failure hospitalization; NYHA, New York Heart Association)

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0.37

5H

eart

failu

re d

urat

ion,

mo

29 (±

36)

30 (±

38)

0.21

728

(±35

)30

(±37

)0.

369

Ejec

tion

frac

tion,

per

cent

34 (±

12)

30 (±

13)

<0.0

001

30 (±

12)

30 (±

13)

0.95

6Ej

ectio

n fr

actio

n >4

5% *

701

(16%

)10

6 (1

0%)

<0.0

001

110

(10%

)10

6 (1

0%)

0.82

3Et

iolo

gy o

f hea

rt fa

ilure

 Is

chem

ic31

32 (6

9%)

701

(64%

)

0.00

2

688

(65%

)68

5 (6

5%)

0.81

6 

Hyp

erte

nsiv

e45

1 (1

0%)

131

(12%

)12

1 (1

1%)

122

(12%

) 

Idio

path

ic65

6 (1

5%)

168

(15%

)16

7 (1

6%)

164

(16%

) 

Oth

ers

273

(6%

)91

(8%

)81

(8%

)86

(8%

)C

omor

bid

cond

ition

s 

Prio

r myo

card

ial i

nfar

ctio

n28

98 (6

4%)

639

(59%

)0.

001

627

(59%

)62

3 (5

9%)

0.89

1 

Cur

rent

ang

ina

1193

(26%

)30

6 (2

8%)

0.28

228

9 (2

7%)

293

(28%

)0.

886

 H

yper

tens

ion

2075

(46%

)54

2 (5

0%)

0.02

852

1 (4

9%)

521

(49%

)>0.

999

 D

iabe

tes

1041

(23%

)39

2 (3

6%)

<0.0

001

372

(35%

)37

1 (3

5%)>

0.99

9 

Chr

onic

kid

ney

dise

ase*‡

1826

(41%

)53

9 (4

9%)

<0.0

001

536

(51%

)51

8 (4

9%)

0.45

9M

edic

atio

ns 

Dig

oxin

(pre

-tria

l use

)17

07 (3

8%)

555

(51%

)<0

.000

149

6 (4

7%)

526

(50%

)0.

175

 D

igox

in (b

y ra

ndom

izat

ion)

2356

(52%

)44

8 (4

1%)

<0.0

001

447

(42%

)44

2 (4

2%)

0.85

6 

AC

E in

hibi

tors

4203

(93%

)102

9 (9

4%)

0.16

510

07 (9

5%)9

98 (9

4%)

0.43

5H

ydra

lazi

ne &

nitr

ates

40 (1

%)

18 (2

%)

0.02

518

(2%

)18

(2%

)>0

.999

 N

on-p

otas

sium

-spa

ring

diur

etic

s32

19 (7

1%)

958

(88%

)<0

.000

192

8 (8

9%)

924

(87%

)0.

816

 Po

tass

ium

-spa

ring

diur

etic

s34

6 (8

%)

80 (7

%)

0.70

774

(7%

)77

(7%

)0.

867

 Po

tass

ium

supp

lem

ents

1043

(23%

)41

3 (3

8%)

<0.0

001

404

(38%

)39

0 (3

7%)

0.54

0Sy

mpt

oms/

sign

s of h

eart

failu

re 

Dys

pnea

at r

est

796

(18%

)31

2 (2

9%)

<0.0

001

299

(28%

)28

9 (2

7%)

0.64

9 

Dys

pnea

on

exer

tion

3238

(72%

)87

9 (8

1%)

<0.0

001

835

(79%

)84

6 (8

0%)

0.58

5 

Act

ivity

lim

itatio

n32

47 (7

2%)

887

(81%

)<0

.000

185

6 (8

1%)

854

(81%

)0.

954

 Ju

gula

r ven

ous d

iste

nsio

n44

2 (1

0%)

184

(17%

)<0

.000

116

8 (1

6%)

169

(16%

)0.

953

 Th

ird h

eart

soun

d90

2 (2

0%)

301

(28%

)<0

.000

130

8 (2

9%)

291

(28%

)0.

446

 Pu

lmon

ary

râle

s55

9 (1

2%)

227

(21%

)<0

.000

120

5 (1

9%)

207

(20%

)0.

956

 Lo

wer

ext

rem

ity e

dem

a80

7 (1

8%)

265

(24%

)<0

.000

125

1 (2

4%)

248

(24%

)0.

917

NY

HA

func

tiona

l cla

ss 

I78

7 (1

7%)

118

(11%

)

<0.0

001

121

(11%

)11

5 (1

1%)

0.35

8 

II26

29 (5

8%)

551

(51%

)54

6 (5

2%)

545

(52%

) 

III

1047

(23%

)40

2 (3

7%)

367

(35%

)37

9 (3

6%)

 IV

49 (1

%)

20 (2

%)

23 (2

%)

18 (2

%)

Hea

rt ra

te, p

er m

inut

e77

(±13

)81

(±13

)<0

.000

181

(±13

)80

(±12

)0.

311

Blo

od p

ress

ure,

mm

Hg

 Sy

stol

ic12

8 (±

20)

127

(±22

)0.

018

127

(±20

)12

7 (±

22)

0.86

7 

Dia

stol

ic76

(±11

)75

(±12

)0.

005

75 (±

11)

75 (±

12)

0.98

6C

hest

radi

ogra

ph fi

ndin

gs 

Pulm

onar

y co

nges

tion

473

(11%

)19

1 (1

8%)

<0.0

001

186

(18%

)17

6 (1

7%)

0.59

8 

Car

diot

hora

cic

ratio

> 0

.524

39 (5

4%)

746

(68%

)<0

.000

170

8 (6

7%)

715

(68%

)0.

771

J Card Fail. Author manuscript; available in PMC 2009 November 1.

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

Ahmed et al. Page 14B

efor

e m

atch

Afte

r m

atch

Num

ber

(%) o

r M

ean

(±SD

)N

o H

FH(n

=45

12)

HFH

(n =

1091

)P

valu

eN

o H

FH(n

=10

57)

HFH

(n =

1057

)P va

lue

Seru

m c

once

ntra

tions

 C

reat

inin

e, m

g/dL

1.2

(±0.

3)1.

3 (±

0.4)

<0.0

001

1.3

(±0.

4)1.

3 (±

0.4)

0.76

1 

Pota

ssiu

m, m

Eq/L

4.3

(±0.

4)4.

3 (±

0.5)

0.41

64.

3 (±

0.4)

4.3

(±0.

5)0.

956

Estim

ated

glo

mer

ular

filtr

atio

n ra

te, m

l/min

per

1.73

m2 *†

66 (±

19)

62 (±

21)

<0.0

001

61 (±

19)

62 (±

21)

0.25

3* Th

ese

deriv

ed v

aria

bles

wer

e no

t use

d in

the

mul

tivar

iabl

e re

gres

sion

mod

el fo

r pro

pens

ity sc

ore

‡ Chr

onic

kid

ney

dise

ase

defin

ed a

s an

estim

ated

glo

mer

ular

filtr

atio

n ra

te <

60 m

L/m

in/1

.73m

2.

† Bas

ed o

n M

odifi

catio

n of

Die

t in

Ren

al D

isea

se S

tudy

form

ula

J Card Fail. Author manuscript; available in PMC 2009 November 1.

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

Ahmed et al. Page 15Ta

ble

2

Ass

ocia

tion

of m

orta

lity

with

hea

rt fa

ilure

hos

pita

lizat

ion

(HFH

) dur

ing

the

first

two

year

sN

o H

FH(N

=105

7)H

FH(N

=105

7)A

bsol

ute

rate

diff

eren

ce*

(per

10,

000

pers

on-y

ears

)

Haz

ard

ratio

(95%

con

fiden

ce in

terv

al)†

P va

lue

Num

ber

of d

eath

s / to

tal y

ears

of f

ollo

w u

p(d

eath

rat

e, p

er 1

0,00

0 pe

rson

-yea

rs)

All-

caus

e15

3 / 3

644

(420

)33

4 / 3

463

(964

)+

545

2.49

(1.9

7–3.

13)

<0.0

001

Car

diov

ascu

lar

115

/ 364

4(3

16)

296

/ 346

3(8

55)

+ 53

92.

88(2

.23–

3.74

)<0

.000

1

 H

eart

failu

re‡

40 /

3644

(110

)16

2 / 3

463

(468

)+

358

5.22

(3.3

4–8.

15)

<0.0

001

 O

ther

car

diov

ascu

lar§

75 /

3644

(206

)13

4 / 3

463

(387

)+

181

1.89

(1.3

6–2.

63)

<0.0

001

Non

-car

diov

ascu

lar

38 /

3644

(104

)38

/ 34

63(1

10)

+ 6

1.21

(0.7

0–2.

08)

0.49

3

* Abs

olut

e di

ffer

ence

s wer

e ca

lcul

ated

by

subt

ract

ing

the

perc

enta

ge o

f dea

ths i

n th

e he

art f

ailu

re h

ospi

taliz

atio

n gr

oup

from

the

perc

enta

ge o

f dea

ths i

n th

e no

n-he

art f

ailu

re h

ospi

taliz

atio

n gr

oup

(bef

ore

valu

es w

ere

roun

ded)

.

† Haz

ard

ratio

s and

con

fiden

ce in

terv

als (

CI)

wer

e es

timat

ed fr

om m

atch

ed C

ox p

ropo

rtion

al-h

azar

ds m

odel

s.

‡ This

cat

egor

y in

clud

es p

atie

nts w

ho d

ied

from

wor

seni

ng h

eart

failu

re, e

ven

if th

e fin

al e

vent

was

an

arrh

ythm

ia.

§ This

cat

egor

y in

clud

es d

eath

s pre

sum

ed to

resu

lt fr

om a

rrhy

thm

ia w

ithou

t evi

denc

e of

wor

seni

ng h

eart

failu

re a

nd d

eath

s due

to a

ther

oscl

erot

ic c

oron

ary

dise

ase,

bra

dyar

rhyt

hmia

s, lo

w-o

utpu

t sta

tes,

and

card

iac

surg

ery.

Thi

s cat

egor

y al

so in

clud

es d

eath

s due

to st

roke

, em

bolis

m, p

erip

hera

l vas

cula

r dis

ease

, vas

cula

r sur

gery

, and

car

otid

end

arte

rect

omy.

J Card Fail. Author manuscript; available in PMC 2009 November 1.