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. Author manuscript; available in PMC: 2014 Feb 1.
Published in final edited form as: JACC Heart Fail. 2013 Feb;1(1):40–47. doi: 10.1016/j.jchf.2012.08.001

Aldosterone Antagonists and Outcomes in Real-World Older Patients with Heart Failure and Preserved Ejection Fraction

Kanan Patel 1, Gregg C Fonarow 2, Dalane W Kitzman 3, Inmaculada B Aban 1, Thomas E Love 4, Richard M Allman 5,1, Mihai Gheorghiade 6, Ali Ahmed 1,5,*
PMCID: PMC3694622  NIHMSID: NIHMS462005  PMID: 23814702

Abstract

Objectives

The purpose of this study was to examine the clinical effectiveness of aldosterone antagonists in older patients with heart failure and preserved ejection fraction (HF-PEF).

Background

Aldosterone antagonists improve outcomes in HF and reduced EF. However, their role in HF-PEF remains unclear.

Methods

Of the 10,570 hospitalized older (age ≥65 years) HF-PEF (EF ≥40%) patients in Medicare-linked OPTIMIZE-HF (Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure) trial, 8013 had no prior aldosterone antagonist use and no current contraindications, of whom 492 (6% of 8013) received new prescriptions for aldosterone antagonists. We assembled a matched cohort of 487 pairs of patients receiving and not receiving aldosterone antagonists, who had similar propensity to receive these drugs, and were balanced on 116 baseline characteristics.

Results

Patients had a mean age of 80 years, a mean EF of 54%, 59% were women, and 8% were African American. During 2.4 year of mean follow-up (through December, 2008), the primary composite endpoint of all-cause mortality or HF hospitalization occurred in 392 (81%) and 393 (81%) patients receiving and not receiving aldosterone antagonists, respectively (hazard ratio {HR}, 0.97; 95% confidence interval {CI}, 0.84–1.11; p=0.628). Aldosterone antagonists had no association with all-cause mortality (HR, 1.03; 95% CI, 0.89–1.20; p=0.693) or HF hospitalization (HR, 0.88; 95% CI, 0.73–1.07; p=0.188). Among 8013 pre-match patients, multivariable-adjusted HR for primary composite endpoint associated with aldosterone antagonist use was 0.93 (95% CI, 0.83–1.03; p=0.144).

Conclusions

In older HF-PEF patients, aldosterone antagonists had no association with clinical outcomes. Findings from the ongoing randomized controlled TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial will provide further insights into their effect in HF-PEF.

Keywords: Aldosterone antagonists, Heart failure, Preserved ejection fraction

Aldosterone antagonists have been shown to reduce the risk of mortality and hospitalization in heart failure and reduced ejection fraction (HF-REF) (1-3). HF and preserved ejection fraction (HF-PEF) comprise nearly half of all HF patients, and have similar prognosis as for HF-REF (4,5). Because activation of the mineralocorticoid receptor by aldosterone may be associated with pathophysiologic changes in HF-PEF such as myocardial fibrosis, left ventricular hypertrophy, renal fibrosis, and vascular injury, this may be a key therapeutic target in these patients (6). Further, these drugs have been shown to reduce myocardial fibrosis and improve diastolic function in HF-PEF (7,8). However, the role of aldosterone antagonists on clinical outcomes in HF-PEF remains unclear.

The effect of spironolactone, an aldosterone antagonist, on morbidity, mortality, and quality of life in patients with HF-PEF is currently being studies in the ongoing multi-center, randomized, double-blind, placebo-controlled Treatment Of Preserved Cardiac function heart failure with an Aldosterone anTagonist (TOPCAT) trial (9). Propensity-matched studies can be a tool for deriving bridge evidence when randomized clinical trial (RCT) based evidence is not readily available (10,11). Further, real-world HF patients are often characteristically and prognostically different from those enrolled in RCTs (12,13). Therefore, in the current study, we examined clinical effectiveness of aldosterone antagonists in real-world older HF-PEF patients.

Methods

Data sources and study population

The OPTIMIZE-HF (Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure) is a national registry of hospitalized HF patients, the details of the design and implementation of which have been previously reported (14-16). Briefly, extensive data on baseline demographics, medical history including admission and discharge medications, hospital course, and discharge disposition were collected by chart abstraction from 48,612 hospitalizations due to HF occurring in 259 hospitals in 48 states during March 2003 – December 2004 (14). A primary discharge diagnosis of HF was based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes for HF (14,15). Considering that HF patients with EF 40% to 50% are characteristically and prognostically similar to those with EF >50% (5), we used EF ≥40% to define HF-PEF and of the 48,612 HF hospitalizations, 20,839 occurred in those with HF-PEF. To obtain long-term outcomes data, we linked OPTIMIZE-HF to Medicare claims data consisting of 100% Medicare Provider Analysis and Review (MedPAR) File and 100% Beneficiary Summary File between January 1, 2002 and December 31, 2008. We were able to link 13,270 of the 20,839 HF-PEF hospitalizations to Medicare data, occurring in 11,997 unique patients, of whom 10,889 were ≥65 years, and 10,570 were discharged alive (13).

Assembly of an eligible cohort

Data on admission and discharge use of aldosterone antagonists and other key HF medications were collected by chart abstraction. Except for beta-blockers, data on individual drugs and dosages were not available for other drugs including aldosterone antagonists. To assemble a cohort eligible for aldosterone antagonist therapy, we excluded patient who had contraindications to the use of these drugs. As such, patients with impaired renal function, defined as serum creatinine of >2.5 mg/dl in males and >2.0 mg/dl in females (n=1443), and an estimated glomerular filtration rate (eGFR) <30 ml/min/1.73 m2 (n=602) were excluded (17). In addition, 193 patients receiving both angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) were excluded (18). Because data on admission serum potassium were unavailable, we also excluded 91 patients whose pre-admission aldosterone antagonist was discontinued before hospital discharge. Thus, after excluding a total of 2329 patients with potential contraindications and intolerance, the remaining 8241 patients were considered eligible for discharge aldosterone antagonist therapy.

Assembly of an inception cohort

Because the receipt of study drug prior to study baseline may affect baseline characteristics and may also causes left censoring, both potentially leading to selection bias, we assembled an inception cohort of patients who had not received aldosterone antagonists in the past (19-21). This was achieved by excluding 228 patients who were receiving aldosterone antagonists during admission. Thus, the final sample size for our inception cohort consisted of 8013 hospitalized patients not receiving aldosterone antagonists and of these, 492 (6.1%) received a new discharge prescription of aldosterone antagonist.

Assembly of a balanced cohort

Because of the significant imbalances in many prognostically important baseline characteristics between patients receiving and not receiving a new discharge prescription for aldosterone antagonists (Table 1 and Figure 1), we used propensity scores for the receipt of aldosterone antagonists to assemble a cohort in which the two treatment groups would be balanced on all measured baseline characteristics (22-24). We estimated propensity scores for each of the 8013 patients using a non-parsimonious multivariable logistic regression model, in which the receipt of aldosterone antagonists was the dependent variable, and 116 baseline characteristics were used as covariates (25-27). Using a greedy matching protocol, we were able to match 487 of the 492 patients receiving aldosterone antagonists with another 487 patients not receiving these drugs but had similar propensity to receive them (28,29).

Table 1.

Baseline characteristics of older patients with heart failure and preserved ejection fraction (HF-PEF), by new discharge prescription of aldosterone antagonists, before and after propensity score matching

Variables
Mean (±SD) or n (%)		 Before propensity score matching After propensity score matching
Aldosterone antagonists
 P value Aldosterone antagonists
 P value
No (n=7521) Yes (n=492) No (n=487) Yes (n=487)
Age (years) 81 (±8) 80 (±7) 0.094 80 (±7) 80 (±7) 0.839
Female 4754 (63) 297 (60) 0.206 278 (57) 295 (61) 0.288
African American 681 (9) 37 (8) 0.248 42 (9) 37 (8) 0.630
Left ventricular ejection fraction (%) 55 (±9) 54 (±10) <0.001 54 (±9) 54 (±10) 0.812
Past medical history
 No prior heart failure hospitalization 1139 (15) 64 (13) 0.199 70 (14) 64 (13) 0.643
 Coronary artery disease 3453 (46) 229 (47) 0.785 237 (49) 226 (46) 0.526
 Hypertension 5618 (75) 366 (74) 0.879 353 (73) 363 (75) 0.505
 Diabetes mellitus 2764 (37) 172 (35) 0.424 169 (35) 170 (35) 1.000
 Atrial fibrillation 2865 (38) 227 (46) <0.001 219 (45) 223 (46) 0.845
 Ventricular arrhythmia 175 (2) 27 (5) <0.001 23 (5) 25 (5) 0.878
 Peripheral vascular disease 977 (13) 78 (16) 0.069 65 (13) 76 (16) 0.351
 Chronic kidney disease 4423 (59) 270 (55) 0.086 267 (55) 267 (55) 1.000
 Depression 849 (11) 75 (15) 0.008 72 (15) 74 (15) 0.925
Admission clinical presentation
 Dyspnea on exertion 4707 (63) 334 (68) 0.018 338 (69) 330 (68) 0.622
 Orthopnea 1812 (24) 143 (29) 0.013 131 (27) 140 (29) 0.571
 Paroxysmal nocturnal dyspnea 963 (13) 89 (18) 0.001 88 (18) 85 (18) 0.866
 Dyspnea at rest 3300 (44) 221 (45) 0.652 221 (45) 218 (45) 0.901
 Chest pain 1652 (22) 89 (18) 0.043 74 (15) 88 (18) 0.258
 Pulse (beats per minute) 85 (±21) 83 (±20) 0.133 83 (±19) 83 (±20) 0.916
 Systolic blood pressure (mmHg) 149 (±31) 146 (±30) 0.061 146 (±30) 146 (±29) 0.657
 Diastolic blood pressure (mmHg) 75 (±18) 75 (±19) 0.917 75 (±18) 75 (±19) 0.450
 Jugular venous pressure elevation 1935 (26) 149 (30) 0.026 151 (31) 148 (30) 0.888
 Pulmonary râles 4828 (64) 350 (71) 0.002 339 (70) 346 (71) 0.659
 Lower extremity edema 4882 (65) 369 (75) <0.001 369 (76) 365 (75) 0.813
Admission laboratory values
 Serum creatinine (mg/dL) 1.2 (±0.4) 1.2 (±0.4) 0.252 1.2 (±0.4) 1.2 (±0.4) 0.446
 Serum brain natriuretic peptide (pg/mL) 871 (±780) 906 (±751) 0.343 895 (±704) 908 (±754) 0.780
 Serum troponin elevation* 1068 (14) 86 (18) 0.045 81 (17) 86 (18) 0.733
Length of hospital stay 8 (±169) 6 (±5) 0.826 6 (±5) 6 (±5) 0.614
Hospital characteristics
 Interventional 5652 (75) 387 (79) 0.080 392 (81) 382 (78) 0.477
 Transplant 985 (13) 48 (10) 0.032 62 (13) 48 (10) 0.161
Hospital location by region
 Midwest 2338 (31) 117 (24) 119 (24) 117 (24)
 Northeast 1345 (18) 87 (18) 0.004 84 (17) 87 (18) 0.322
 South 2355 (31) 178 (36) 169 (35) 175 (36)
 West 1483 (20) 110 (22) 115 (24) 108 (22)
In-hospital treatment/procedure
 Dobutamine 93 (1) 14 (3) 0.003 16 (3) 13 (3) 0.690
 Nesiritide 480 (6) 64 (13) <0.001 68 (14) 60 (12) 0.451
Discharge medication
 Angiotensin-converting enzyme inhibitors 3656 (49) 267 (54) 0.015 254 (52) 265 (54) 0.512
 Angiotensin receptors blockers 972 (13) 77 (16) 0.082 80 (16) 75 (15) 0.735
 Beta-blockers 4402 (59) 343 (70) <0.001 348 (72) 338 (69) 0.502
 Diuretics 6206 (83) 439 (89) <0.001 431 (89) 434 (89) 0.832
 Digoxin 1678 (22) 147 (30) <0.001 143 (29) 144 (30) 1.000
 Nitrates 1809 (24) 134 (27) 0.110 132 (27) 132 (27) 1.000
 Warfarin 2035 (27) 188 (38) <0.001 173 (36) 185 (38) 0.441
 Anti-platelet drugs 1080 (14) 61 (12) 0.228 59 (12) 60 (12) 1.000
 Aspirin 3504 (47) 226 (46) 0.778 227 (47) 224 (46) 0.900
 Statins 2345 (31) 172 (35) 0.080 177 (36) 170 (35) 0.693
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*

Determined by local laboratories

Figure 1. Love plot for absolute standardized differences.

Figure 1

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Love plot displaying absolute standardized differences comparing 116* baseline characteristics between older HF-PEF patients receiving new discharge prescriptions for aldosterone antagonists and not receiving any aldosterone antagonists, before and after propensity score matching. (Hx=past medical history, A=admission, D=discharge, H=in-hospital, PF=precipitating factor, ACE=angiotensin-converting enzyme, ICD=Implantable cardioverter-defibrillator, ARB=angiotensin receptor blocker, CABG=coronary artery bypass grafting, CCB=calcium channel blocker, COPD=chronic obstructive pulmonary disease, JVP=jugular venous pressure, PCI=percutaneous coronary intervention, PND=paroxysmal nocturnal dyspnea, TIA=transient ischemic attack; *4 regions entered as a single categorical variable in the model, dialysis during hospitalization was in the model but excluded from figure as there was no cases in the matched data)

Propensity score models are sample-specific adjusters and are not intended to be used for out-of-sample prediction or estimation of coefficients. Therefore, measures of fitness and discrimination are not important for the assessment of these models’ effectiveness. Instead, the efficacy of propensity score models is best assessed by estimating between-group post-match absolute standardized differences of baseline characteristics. Absolute standardized differences directly quantify bias in the means (or proportions) of covariates across the two treatments or exposure groups; a difference of 0% indicates no residual bias and values <10% are considered inconsequential. Therefore, we assessed the effectiveness of our propensity score model by estimating absolute standardized differences, which were presented as a Love plot (30,31).

We replicated the above process to assemble a second balanced propensity-matched cohort in which HF-PEF was defined EF ≥50%. Finally, to determine clinical effectiveness of any (new or continuation) discharge prescription of aldosterone antagonists, we repeated the above process in 8241 patients eligible for aldosterone antagonist therapy, of whom 720 (9%) received discharge prescriptions to initiate or continue their aldosterone antagonists. We were able to match 712 of the 720 patients receiving aldosterone antagonists with another 712 patients not receiving these drugs thus assembling a third balanced propensity-matched cohort.

Outcomes

The primary outcome for the current analysis was a composite endpoint of all-cause mortality or HF hospitalization during about 6 years of follow-up (mean, 2.4 years, median, 1.4 years). Secondary outcomes included all-cause mortality, HF hospitalization, and all-cause hospitalization. All outcomes data were obtained from Medicare claims data (13,32). Medicare-linked OPTIMIZE-HF patients have been shown to be characteristically and prognostically similar to HF patients in the general Medicare population (32).

Statistical analysis

Baseline characteristics were compared using Pearson’s Chi-square and Wilcoxon rank-sum tests for pre-match, and McNemar’s test and paired sample t-test for post-match comparisons, as appropriate. Kaplan-Meier plots and Cox regression analyses were used to determine associations of discharge prescriptions of aldosterone antagonists with outcomes. To determine the homogeneity of association between aldosterone antagonist use and the primary endpoint, we conducted subgroup analyses. A formal sensitivity analysis was conducted to estimate the degree of hidden bias that could potentially explain away a significant association among matched patients (33). We repeated our analyses in the pre-match cohort using three different approaches: (1) unadjusted; (2) multivariable-adjusted, using all 116 baseline characteristics; and (3) propensity score-adjusted. All statistical tests were two-tailed with a p-value <0.05 considered significant. SPSS for Windows version 20 (Release 2011, IBM Corp. Armonk, NY) was used for data analysis.

Results

Baseline characteristics

Matched patients (n=974) had a mean (±SD) age of 80 (±7) years, a mean (±SD) left ventricular ejection fraction (LVEF) of 54% (±9%), 59% were women, and 8% were African American. Patients receiving aldosterone antagonists had lower mean LVEF, a higher symptom burden, and more likely to receive other neurohormonal antagonists, but no difference in blood pressure or serum creatinine (Table 1 and Figure 1). After matching, patients receiving and not receiving a new discharge prescription for aldosterone antagonists were balanced on 116 baseline characteristics. All post-match absolute standardized differences were <10% suggesting that all 116 measured baseline characteristics were balanced between the two treatment groups.

New discharge prescriptions for aldosterone antagonists and outcomes

During 2.4 years of mean follow-up, the primary composite endpoint of all-cause mortality or HF hospitalization occurred in 392 (81% of 487) and 393 (81% of 487) of matched patients receiving and not receiving a new discharge prescription of aldosterone antagonists, respectively (hazard ratio {HR} associated with aldosterone antagonist use, 0.97; 95% confidence interval {CI}, 0.84–1.11; p=0.628; Figure 2 and Table 2). This association was rather homogeneous across various clinically relevant subgroups of patients (Figure 3). Similar association was observed when the Cox model was stratified by matching (HR, 0.93; 95% CI, 0.78–1.12; p=0.933). There was no significant association with the primary composite endpoint at the end of first and second year of follow-up. Aldosterone antagonists had no significant association with all-cause mortality, HF or all-cause hospitalization (Table 2). All associations were similar, when EF >50% was used to define HF-PEF.

Figure 2. Kaplan-Meier plots for outcomes.

Figure 2

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Kaplan-Meier plots of outcomes in a propensity-matched inception cohort of older HF-PEF patients receiving new discharge prescriptions for aldosterone antagonists and not receiving any aldosterone antagonists (HR=hazard ratio, CI=confidence interval)

Table 2.

Association of discharge prescriptions for aldosterone antagonists with outcomes in propensity-matched inception cohort of older patients with heart failure and preserved ejection fraction (HF-PEF)

Outcomes Events (%)
 Absolute risk
difference* 		Hazard ratio†
(95% CI)		 P value
Aldosterone antagonists
New prescription No (n=487) Yes (n=487)
All-cause mortality or HF hospitalization 393 (81%) 392 (81%) 0% 0.97 (0.84–1.11) 0.628
All-cause mortality 328 (67%) 335 (69%) +2% 1.03 (0.89–1.20) 0.693
HF hospitalization 219 (45%) 199 (41%) −4% 0.88 (0.73–1.07) 0.188
All-cause hospitalization 416 (85%) 446 (92%) +7% 1.10 (0.96–1.26) 0.156
Any (new or continuation) prescription No (n=712) Yes (n=712)
All-cause mortality or HF hospitalization 583 (82%) 587 (82%) 0% 1.00 (0.89–1.12) 0.991
All-cause mortality 502 (71%) 492 (69%) −2% 0.94 (0.83–1.07) 0.358
HF hospitalization 327 (46%) 326 (46%) 0% 0.99 (0.85–1.16) 0.918
All-cause hospitalization 616 (87%) 639 (90%) +3% 1.06 (0.94–1.18) 0.343
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*

Absolute risk differences were calculated by subtracting percent events in patients not receiving aldosterone antagonists from those receiving those drugs

†

Hazard ratios comparing patients receiving aldosterone antagonists versus those not receiving those drugs

Figure 3. Subgroup analysis for primary composite endpoint.

Figure 3

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Association of new discharge prescriptions for aldosterone antagonists with primary composite endpoint of all-cause mortality or HF hospitalization in subgroups of propensity-matched older HF-PEF patients (EF=ejection fraction, GFR=glomerular filtration rate, HF=heart failure)

Among the 8013 pre-match patients, the primary composite endpoint occurred in 81% (397/492) and 82% (6126/7521) of patients receiving and not receiving a new discharge prescription of aldosterone antagonists, respectively (HR associated with aldosterone antagonists use, 0.96; 95% CI, 0.87–1.07; p=0.452). Corresponding multivariable-adjusted and propensity score-adjusted HRs were 0.93 (95% CI, 0.83–1.03; p=0.144) and 0.95 (95% CI, 0.86–1.05; p=0.324), respectively.

Any (new or continuation) prescription for aldosterone antagonists and outcomes

The primary composite endpoint of all-cause mortality or HF hospitalization occurred in 82% (587/712) of patients receiving any (new or continuation) discharge prescription for aldosterone antagonists versus 82% (583/712) of those not receiving any aldosterone antagonists (HR associated with aldosterone antagonists use, 1.00; 95% CI, 0.89–1.12; p=0.991; Table 2). Among the 8241 pre-match patients, unadjusted, multivariable-adjusted and propensity score-adjusted HRs (95% CIs) for the primary composite endpoint associated with any (new or continuation) use of aldosterone antagonists were 1.04 (0.96–1.14; p=0.311), 0.97 (0.89–1.06; p=0.492), and 0.98 (0.90–1.07; p=0.609), respectively. A discharge prescription for aldosterone antagonists (new or continuation) had no significant association with all-cause mortality or hospitalization among matched patients (Table 2). Similar associations were observed in patients using EF >50% to define HF-PEF.

Discussion

Findings from the current analysis demonstrate that a new discharge prescription for aldosterone antagonists had no unadjusted or independent association with any clinically important long-term outcomes in a wide spectrum of older HF-PEF patients who were balanced on over one hundred potential baseline characteristics and over 80% of whom experienced a primary endpoint event during six years of follow-up. Currently, there is no RCT evidence that aldosterone antagonists may improve outcomes in patients with HF-PEF. Findings from this rigorously conducted propensity-matched inception cohort study based on a nationally representative sample of real-world HF-PEF patients provide important insights about the potential role of aldosterone antagonists in HF-PEF. However, more definitive conclusions cannot be reached on the role of aldosterone antagonists in patients with HF-PEF until the TOPCAT trial results are available.

Aldosterone, a mineralocorticoid receptor agonist, is known to cause fibrosis and hypertrophy of the myocardium and be associated with poor cardiovascular outcomes (6). Spironolactone and eplerenone, drugs that block aldosterone receptors, on the other hand, have been shown to improve clinical outcomes in patients with HF-REF (1-3). As in HF-REF, HF-PEF is also associated with neurohormonal activation and myocardial fibrosis (34). However, findings from the current study suggest that unlike in HF-REF, these drugs may not improve clinical outcomes in HF-PEF. This is rather intriguing, as in the RALES (Randomized Aldactone Evaluation Study) trial, spironolactone significantly reduced both total mortality and HF hospitalization in HF-REF (1) and in the EMPHASIS (Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure) trial significantly reduced the composite endpoint of total mortality or HF hospitalization in HF-REF (3). Although OPTIMIZE-HF did not collect data on individual aldosterone antagonists, a post hoc analysis of a similar cohort suggests that spironolactone was the most common aldosterone antagonists during the study period (35). Further, the use of eplerenone has been shown to reduce myocardial fibrosis and improve left ventricular remodeling in several mechanistic studies in human HF-PEF (7,8).

The discordant effect of aldosterone antagonists in HF-PEF (vis-à-vis HF-REF) is not implausible as ACE inhibitors and ARBs, effective in HF-REF, also do not seem to improve clinical outcomes in HF-PEF (36-38). One potential explanation may lie in the differential modes of death between HF-PEF and HF-REF. While cardiovascular and HF deaths are more common in HF-REF, it is much less common in HF-PEF (39). The lack of unadjusted associations between aldosterone antagonist use and outcomes in our pre-match cohort is also intriguing and rather unusual in observational studies. One potential explanation is that because aldosterone antagonists are not recommended for use in HF-PEF, any potential selection bias was limited. However, contraindications for aldosterone antagonists such as hyperkalemia and renal insufficiency would be expected to similar in HF-PEF and HF-REF and exclusion of patients with contraindication would have selected a healthier cohort via bias by indication. Another potential explanation is regression dilution and underestimation of associations due to crossover of therapy during follow-up (40). Although data on post-discharge adherence were not available, such crossover would be expected to be modest (41), and unlikely to fully nullify true associations. Finally, as in any observational study, chance, bias and confounding are potential alternate explanations, but unlikely given the observed null associations. Similarly, bias due to unmeasured confounders is also unlikely, although it could be not estimated as the null association precluded formal sensitivity analysis.

Several smaller mechanistic studies of aldosterone antagonists in HF-PEF that have examined other endpoints which demonstrated mixed results. In one study of 44 patients with HF-PEF, therapy with eplerenone, an aldosterone antagonist, was associated with attenuation of myocardial fibrosis and improvement of diastolic function at 12 months but had no effect on clinical variables or brain natriuretic peptide (8). In another study of 44 HF-PEF patients, eplerenone similarly improved myocardial fibrosis and diastolic function but had no effect of exercise capacity (7). One clinical study also did not find any multivariable-adjusted association between aldosterone and outcome in HF-PEF (42). In contrast to those studies, the current study is distinguished by its use of robust methodology (propensity matching and inception cohort design), high event rates and long-term follow-up. Currently there is no RCT-evidence of benefit of aldosterone antagonists in HF-PEF and the findings from our study provide interim evidence regarding the role of these drugs in HF-PEF. The efficacy of aldosterone antagonists in HF-PEF is being studied in the ongoing TOPCAT trial, which is expected to be completed by July 2013 (9).

Our study has several limitations. Although we excluded patients receiving aldosterone antagonists during hospital admission, we had no data on remote use. However, misclassification of remote users as nonusers is unlikely to introduce any bias as aldosterone antagonists are often discontinued for reasons of renal insufficiency and hyperkalemia. HF hospitalization was not centrally adjudicated and cause-specific mortality data were not available. The analyses were restricted to fee-for-service older Medicare patients and hospital participation in OPTIMIZE-HF was voluntary. Finally, data for the current analysis were collected from medical records and thus dependent on the accuracy and completeness of clinical documentation.

Conclusions

A new discharge prescription for aldosterone antagonists had no association with mortality or HF hospitalization as composite or individual endpoints in real-world hospitalized older patients with HF-PEF. Whether these results would differ from trial-eligible ambulatory younger HF-PEF patients will await results of the ongoing randomized controlled TOPCAT trial.

Acknowledgments

Funding Sources: A.A. is supported by the NIH through grant (R01-HL097047) from the NHLBI, and a generous gift from Ms. Jean B. Morris of Birmingham, Alabama. R.M.A. is supported by the UAB CTSA grant (5UL1 RR025777). D.W.K. is supported in part by NIH R37AG18915. OPTIMIZE-HF was funded by GlaxoSmithKline.

Abbreviations

HF-REF

Heart failure and reduced ejection fraction

HF-PEF

Heart failure and preserved ejection fraction

TOPCAT

Treatment Of Preserved Cardiac function heart failure with an Aldosterone anTagonist

RCT

Randomized clinical trial

OPTIMIZE-HF

Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure

ACE inhibitors

Angiotensin-converting enzyme inhibitors

ARBs

Angiotensin receptors blockers

HR

Hazard ratio

CI

Confidence interval

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Disclosures: G.C.F. has been consultant to Medtronic, Novartis, and Gambro. D.W.K. has received research funding from Novartis, has been consultant for Boston Scientific, Abbott and Relypsa, has been on an advisory board for Relypsa, and has stock ownership (significant) for Gilead and stock options for Relypsa. M.G. has acted as consultant for the following: Abbott Laboratories, Astellas, AstraZeneca, Bayer Schering Pharma AG, Cardiorentis Ltd, CorThera, Cytokinetics, CytoPherx Inc, DebioPharm SA, Errekappa Terapeutici, GlaxoSmithKline, Ikaria, Intersection Medical Inc., Johnson & Johnson, Medtronic, Merck, Novartis Pharma AG, Ono Pharmaceuticals USA, Otsuka Pharmaceuticals, Palatin Technologies, Pericor Therapeutics, Protein Design Laboratories, Sanofi-Aventis, Sigma Tau, Solvay Pharmaceuticals, Sticares InterACT, Takeda Pharmaceuticals North America Inc., and Trevena Therapeutics; and has received significant (.US$10 000) support from Bayer Schering Pharma AG, DebioPharm Sa, Medtronic, Novartis Pharma AG, Otsuka Pharmaceuticals, Sigma Tau, Solvay Pharmaceuticals, Sticares InterACT, and Takeda Pharmaceuticals North America Inc. All other authors have no conflict of interest to declare.

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