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The effect of peripheral arterial disease (PAD) on outcomes in patients with chronic heart failure (HF) has not been examined in propensity-matched studies.
Of the 2689 patients with advanced chronic systolic HF in the Beta-Blocker Evaluation of Survival Trial, 441 had a history of PAD. Propensity scores for a history of PAD, calculated for each patient using a multivariable logistic regression model, were used to assemble a matched cohort of 299 and 1015 patients respectively with and without PAD who were well-balanced on 65 measured baseline characteristics. Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between PAD and outcomes during 4.1 years of follow-up. Patients had a mean age of 63 (±11) years, 19% were women and 19% were African Americans. All-cause mortality occurred in 43% and 33% of patients with and without a history of PAD, respectively (HR when PAD was compared with no-PAD, 1.40; 95% CI, 1.14–1.72; p=0.001). All-cause hospitalization occurred in 75% and 63% of patients with and without PAD, respectively (HR when PAD was compared with no-PAD, 1.36; 95% CI, 1.16–1.58; p<0.0001). PAD-associated HRs for cardiovascular mortality, HF mortality and HF hospitalization were respectively 1.31 (95% CI, 1.04–1.63; p=0.019), 1.40 (95% CI, 0.97–2.02; p=0.076) and 1.05 (95% CI, 0.86–1.29; p=0.635).
In a well-balanced propensity-matched population of chronic systolic HF patients, a history of PAD was independently associated with increased mortality and hospitalization.
Peripheral arterial disease (PAD) is a manifestation of systemic atherosclerosis and predicts adverse cardiovascular outcomes.1–7 In a propensity-matched cohort of community-dwelling older adults, we have previously demonstrated that the presence of PAD had an independent association with increased all-cause and cardiovascular mortality.8 However, the extent to which PAD may be independently associated with outcomes in heart failure (HF) patients has not been previously examined in a propensity-matched study. In the current study, we used a public-use copy of the Beta–Blocker Evaluation of Survival Trial (BEST)9 dataset to determine the association between a baseline history of PAD and long-term outcomes in a propensity-matched population of advanced chronic systolic HF patients in which those with and without PAD were well-balanced in all measured baseline characteristics.
The BEST was a multicenter randomized placebo-controlled clinical trial of bucindolol, a beta-blocker, in advanced systolic HF, methods and results of which have been previously published.9 Briefly, 2708 patients with advanced systolic HF were enrolled from 90 different sites across the United States and Canada between May 1995 and December 1998. At baseline, patients had a mean duration of 49 months of HF and had a mean left ventricular ejection fraction of 23%. All patients had New York Heart Association class III–IV symptoms and over 90% of all patients were receiving angiotensin-converting enzyme (ACE) inhibitors, diuretics, and digitalis.
The public-use copy of the BEST dataset included 2707 patients (one patient did not consent to be included in the public-use copy). After excluding 18 patients without data on smoking pack-years, a total of 2689 patients were included in the current analysis. Overall, 441 (16%) patients had a history of PAD at baseline. Data on a history of PAD were collected by study investigators and were not centrally adjudicated. Data on socio-demographic, clinical, sub-clinical and laboratory variables were collected at baseline. BEST participants were enrolled during a 3-year period and were followed up for a minimum of 18 months and a maximum of 4.5 years.9 Primary outcomes for the current analysis were all-cause mortality and all-cause hospitalization during 4.1 years of follow-up (mean, 2 years; range, 10 days to 4.14 years). Secondary outcomes were mortality due to cardiovascular causes, heart failure and sudden cardiac death and hospitalizations due to HF.
As there were significant imbalances in baseline characteristics between patients with and without PAD before matching (Table 1), we used propensity score matching to assemble a cohort of patients whereby those with and without PAD would be well-balanced on all measured baseline covariates.10–12 The propensity score for PAD for a patient would be that patient’s probability of having PAD given his or her measured baseline characteristics. Propensity scores for PAD were estimated for each of the 2689 patients using a non-parsimonious multivariable logistic regression model. In the model, PAD was the dependent variable and 65 baseline characteristics displayed in Figure 1 were used as covariates in the model. A number of clinically relevant interactions such as age by smoking, coronary artery disease (CAD) by smoking etc were also were included in initial models but were excluded from the final model due to lack of statistical significance. We used a greedy matching protocol, described in detail elsewhere, to match one patient with PAD with up to 4 patients without PAD. Using this approach, we were able to match 299 patients with PAD with 1015 patients without PAD.13–17
Because propensity score models are sample-specific adjusters and are not intended to be used for out-of-sample prediction or estimation of coefficients, measures of fitness and discrimination are not important for the assessment of the model’s effectiveness. As such, measures of fitness and discrimination are irrelevant for the assessment of the model’s effectiveness.13–17 We assessed propensity score models by estimating pre- and post-match absolute standardized differences for measured baseline covariates between patients with and without PAD. Absolute standardized differences directly quantify bias in the means (or proportions) of covariates across the groups. They are expressed as a percentage of the pooled standard deviation and are presented in Love plots.13–17 An absolute standardized difference of 0% indicates no residual bias and differences <10% are considered inconsequential.
Kaplan-Meier and Cox regression analyses were used to determine associations between PAD and outcomes during 4.1 years of follow-up. Log-minus-log scale survival plots were used to check proportional hazards assumptions. Formal sensitivity analyses were conducted to quantify the degree of a hidden bias that would need to be present to invalidate our conclusions based on significant association between PAD and primary outcomes among matched patients.18 Subgroup analyses were conducted to determine the homogeneity of association between a history of PAD and all-cause mortality. All statistical tests were two-tailed with a p-value <0.05 considered significant. All data analyses were performed using SPSS for Windows version 15 (SPSS Inc., Chicago, IL).19
Matched patients had a mean age of 63 (±11) years, 19% were women and 19% were African Americans. Significant imbalances in several baseline characteristics before matching and the balances achieved after matching are displayed in Table 1 and Figure 1. After matching, standardized differences for all measured covariates were <10% (most were <5%), suggesting substantial covariate balance across the groups (Figure 1).
All-cause mortality occurred in 43% and 33% of patients with and without PAD respectively (hazard ratio, 1.40; 95% confidence interval, 1.14–1.72; p=0.001; Figure 2a and Table 2). In the absence of hidden bias, a sign-score test for matched data with censoring provides relatively strong evidence (p=0.035) that patients without PAD clearly outlived those with PAD. A hidden covariate that is a near-perfect predictor of mortality may potentially explain away the association between PAD and all-cause mortality if that would increase the odds of PAD by only 1. 3%. No heterogeneity of association between PAD and all-cause mortality was detected in any of the subgroups of patients (Figure 3). Associations of PAD with mortality due to cardiovascular causes, HF, and sudden cardiac death are displayed in Table 2.
All-cause hospitalization occurred in 75% and 63% patients with and without PAD respectively (HR, 1.36; 95% CI, 1.16–1.58; p<0.0001; Figure 2b and Table 2). In the absence of hidden bias, a sign-score test for matched data with censoring provides strong evidence (p=0.001) that patients without PAD clearly had fewer hospitalizations due to all causes than those with PAD. A hidden covariate that is a near-perfect predictor of hospitalization, could potentially explain away our observed association between PAD and all-cause hospitalization, should it increase the odds of PAD by 9.4%. Other pre- and post-match associations of PAD with hospitalizations are displayed in Table 2.
Findings from the current study demonstrate that the prevalence and the burden of CAD was high among systolic HF patients with a history of PAD, and a history of PAD was associated with increased risk of mortality and hospitalization in these patients. Significant strong bivariate associations of PAD with major natural history endpoints suggest that the presence of PAD may be used to identify advanced systolic HF patients who are at an increased risk for poor outcomes. The significant associations of PAD with all-cause mortality and all-cause hospitalization after propensity score matching suggest that the effect of PAD was independent of the 65 measured baseline characteristics that included major cardiovascular risk factors. These findings are important as PAD is common in patients with advanced systolic HF.20
Strong bivariate associations between PAD and outcomes are likely due to confounding by covariates such as age, smoking, CAD, and diabetes mellitus, the prevalence of which was higher in those with PAD than in those without PAD. However, associations between PAD and all-cause mortality and all-cause hospitalization persisted despite risk adjustments using multiple approaches including propensity matching. This suggests an intrinsic association between PAD and outcomes in HF that was independent of the measured covariates in our study. However, we are not aware of any mechanistic pathway of a direct and intrinsic effect of PAD on death or hospitalization. One possible explanation is that atherosclerotic diseases in PAD patients are of a greater severity and more advanced or widespread.1, 21, 22 This is evident from the higher prevalence and burden of CAD and other morbidities in pre-match patients with PAD. While these and other measured confounders were well-balanced after matching, it is possible that atherosclerosis progressed at a faster rate during follow-up in patients with PAD than in those without PAD. Findings from our subgroup analysis also suggest a significant PAD-associated increase in mortality among those with CAD. It is also possible that HF patients with clinical PAD may restrict their physical activity to avoid claudication pain, potentially leading to deconditioning and deterioration of cardiovascular fitness and poor outcomes.23
Findings from population-based studies suggest that age, smoking, systolic blood pressure, and serum glucose are significantly associated with large vessel PAD.24 Before matching patients with PAD in our study were older, with a significantly higher prevalence of current smokers and higher pack-years of smoking, higher systolic blood pressure and higher serum glucose, all indicating the presence of large vessel PAD. Large vessel PAD has been shown to be independently associated with increased mortality.4 Smoking is one of the strongest predictors for progression of large vessel PAD.6, 25 Although our matched patients were balanced on pack-years of smoking and prevalence of current smokers, it is possible that the deleterious effects of continued smoking was more profound in the presence of PAD.26, 27
An examination of the associations between PAD and cause-specific mortalities provide further insight into how PAD may affect mortality in advanced systolic HF patients. Sudden cardiac death was a major mode of death in our study, accounting for over half of all deaths. However, PAD apparently was not associated with fatal cardiac arrhythmias underlying sudden deaths. This lack of a statistically significant association between PAD and sudden death suggests that the effect of PAD in HF may be predominantly non-sudden in nature. PAD, however, had significant associations with cardiovascular death, and its association with HF death was of borderline significance. PAD has also been shown to be associated with increased risk of fatal acute myocardial infarction (AMI).5 However, only <5% of all deaths in our study were due to AMI, which may explain the non-significant association between PAD and AMI death. PAD-associated increase in the risk of other cardiovascular mortality highlights its impact on vascular deaths such as those due to stroke. Unfortunately, we had limited data on cause-specific hospitalizations with which to gain insights into the PAD-associated increase in all-cause hospitalization in advanced systolic HF patients. Extrapolating from cause-specific mortality data, it may be suggested that PAD-associated increase in hospitalization was primarily due to cardiovascular causes. However, recent reports have suggested an association between PAD and non-cardiovascular morbidities.28, 29
To the best of our knowledge this is the first report of an association of PAD with mortality and hospitalization in a propensity matched population of advanced chronic systolic HF patients. Our findings of increased mortality and morbidity in chronic HF patients with PAD have important clinical and public health implications. PAD may be a manifestation of more severe and/or advanced systemic atherosclerosis, and thus its presence can be used to identify HF patients with poorer prognosis. This may be useful as an inexpensive clinical tool in developing nations to risk stratify HF patients. Importantly PAD may often be asymptomatic and hence under-diagnosed. It is relatively easy, however, to accurately diagnose the presence and severity PAD by measures such as the ankle-brachial pressure index. Our findings of independent associations of PAD with poor outcomes highlight the importance of prevention and timely detection of PAD, and aggressive treatment of atherosclerotic risk factors in HF patients.
Management of PAD in HF is similar to that in the general population with a few exceptions. Current recommendations for management of PAD patients are mainly based on reduction of systemic cardiovascular risk, which include smoking cessation, exercise, treatment of hypertension and diabetes, and the use of antiplatelet agents and statins.30 Walking and physical training have been shown to improve claudication distance in patients with PAD.31, 32 Cilostazol, a phosphodiesterase-3 inhibitor approved for use in symptomatic PAD, is contraindicated in HF (a black-box warning). Pentoxifylline, a phosphodiesterase-4 inhibitor, also approved for use in symptomatic PAD, may be safe in HF.33 However, its efficacy in improving walking distance is very limited.32 Statins and ACE inhibitors have shown some efficacy for walking distance, however there is no labeled indication for these drugs.34–37 Despite concerns that beta-blockers may cause or worsen claudication in patients with PAD these drugs are not contraindicated in these patients.30 We observed that the effect of PAD on mortality appeared to be heterogeneous between patients receiving and not receiving bucindolol, a beta-blocker. However, the lack of a significant interaction (p=0.140: Figure 3) precludes any inference of heterogeneity. It is possible that the non-significant interaction may be due to inadequate power. Considering the potential clinical importance of these findings, future studies with adequate sample sizes are needed to examine the heterogeneity of the effect of PAD on outcomes in HF patients receiving and not receiving beta-blockers.
Several limitations of the current study must be acknowledged. Findings of this study based on advanced systolic HF patients enrolled in a clinical trial may not be generalizable to patients with mild-moderate systolic HF or diastolic HF. Data on ankle-brachial pressure index were not available and diagnosis of PAD was based on patients’ medical history as assessed by study investigators. This may have misclassified some PAD patients and underestimated the true prevalence of PAD. Data were not available on the extent and severity of PAD. It is possible that patients without PAD at baseline may have developed PAD during follow-up, thus resulting in regression dilution bias, which is another potential source of underestimation of the true association between PAD and outcomes38. Finally, the findings of our sensitivity analyses suggest that our conclusions were rather sensitive to an unmeasured confounder. However, sensitivity analysis cannot determine if an unmeasured confounder exists or not. To be a confounder, an unmeasured covariate, in addition to being associated with PAD, would also need to have a near-perfect association with outcomes, without any strong association with any of the 65 measured baseline covariates used in our study, a possibility which seems highly unlikely.
In conclusion, PAD in advanced chronic systolic HF patients was associated with increased risk of death and hospitalization, which was independent of 65 baseline characteristics including major cardiovascular risk factors. PAD-associated poor outcomes in HF patients are likely non-sudden in nature and likely to be predominantly atherosclerotic in origin. PAD may be useful as an inexpensive screening tool to risk stratify HF patients.
Funding/Support: Dr. Ahmed is supported by the National Institutes of Health through grants (R01-HL085561 and R01-HL097047) from the National Heart, Lung, and Blood Institute and a generous gift from Ms. Jean B. Morris of Birmingham, Alabama
“The Beta–Blocker Evaluation of Survival Trial (BEST) is conducted and supported by the NHLBI in collaboration with the BEST Study Investigators. This Manuscript was prepared using a limited access dataset obtained from the NHLBI and does not necessarily reflect the opinions or views of the BEST or the NHLBI.”
Conflict of Interest Disclosures: None
Disclosures: Dr. Ali Ahmed reports no potential conflicts of interest.
Dr. Mustafa Ahmed reports no potential conflicts of interest.
Dr. Inmaculada Aban reports no potential conflicts of interest.
Dr. Wilbert Aronow reports no potential conflicts of interest.
Dr. Michael Criqui reports no potential conflicts of interest.
Dr. Eric Eichhorn reports no potential conflicts of interest.
Dr. Thomas Love reports no potential conflicts of interest.