Importance of Temporal Heart Rate Changes in HFpEF
What is the relationship between baseline heart rate (HR), changes in HR from a preceding visit, and time-updated HR with subsequent outcomes in patients with heart failure with preserved ejection fraction (HFpEF) in the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial?
The TOPCAT study investigators examined the association between baseline resting HR, as well as change in HR from the preceding visit (i.e., time-updated HR) and ΔHR and clinical outcomes (the composite of cardiovascular [CV] death, aborted cardiac arrest, and admission for worsening HF and also the outcomes of all-cause mortality, CV death, hospitalization for HF, non-CV death, fatal and nonfatal myocardial infarction [MI], and stroke), in 1,767 patients from the Americas, enrolled in the TOPCAT trial. They used Cox proportional hazards models, as well the association between HR at each visit and outcome.
The median age was 72 (64-79) years, 50% of the cohort was female, and the mean left ventricular EF (LVEF) was 58 ± 8%. At baseline, 72% had entered the study based on an HF admission in the past 12 months. Ninety percent of the patients had a history of hypertension, and one fifth had a previous MI. Atrial fibrillation was present in just over 40% at baseline. Both baseline HR (adjusted hazard ratio [AHR], 1.08 [HR, 1.04-1.12]) and change in HR from the preceding visit (AHR, 1.09; 95% confidence interval, 1.05-1.14; p < 0.001 per 5 bpm higher HR), after adjusting for covariates, were associated with a higher risk of the primary endpoint of CV death, hospitalization for HF, or aborted cardiac arrest. A resting HR above 76 bpm at any time during follow-up was associated with a higher risk of the primary endpoint. Time-updated resting HR at each visit was also associated with risk (AHR, 1.11; 95% confidence interval, 1.07-1.15; p < 0.001, per 5 bpm higher HR). Furthermore, the investigators observed a rise in resting HR of approximately 10 bpm beginning approximately 10 days prior to the primary endpoint. The use of a beta-blocker at baseline in the study did not affect the relationship between ΔHR and outcomes (p for interaction of 0.90 for the primary endpoint) nor did the presence of atrial fibrillation at the time of randomization (p for interaction of 0.41) for the primary endpoint.
The investigators concluded that baseline resting HR and change in HR over time predict outcome in patients with HFpEF, as does time-updated HR during follow-up. The authors suggested that frequent outpatient monitoring of HR, possibly with remote technologies, may identify patients with HFpEF who may be at increased risk of re-hospitalization or death.
This is an important study because it suggests that HR is an important predictor of outcomes in HFpEF patients—similar conclusions were reached by post-hoc analysis of the participants of the OPTIMIZE-HF study (reviewed recently). The next step would be to prospectively determine whether modulating HRs with pharmacotherapy improves outcomes.
Clinical Topics: Arrhythmias and Clinical EP, Geriatric Cardiology, Heart Failure and Cardiomyopathies, Prevention, Implantable Devices, SCD/Ventricular Arrhythmias, Atrial Fibrillation/Supraventricular Arrhythmias, Acute Heart Failure, Hypertension
Keywords: Adrenergic beta-Antagonists, Atrial Fibrillation, Geriatrics, Heart Arrest, Heart Failure, Heart Rate, Hypertension, Myocardial Infarction, Outcome Assessment (Health Care), Secondary Prevention, Stroke, Stroke Volume
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