Brian L. Claggett
Christopher B. Granger
John J. V. McMurray, Australian Catholic University
Marc A. Pfeffer
Scott D. Solomon
Vazir, A., Claggett, B. L, Jhund, P., Castagno, D., Skali, H., Yusuf, S., Swedberg, K., Granger, C. B, McMurray, J. J, Pfeffer, M. A & Solomon, SD. (2015). Prognostic importance of temporal changes in resting heart rate in heart failure patients: An analysis of the CHARM program. European Heart Journal,36(11), 669-675. United Kingdom: Oxford University Press. Retrieved from https://doi.org/10.1093/eurheartj/ehu401
Background: Resting heart rate (HR) is a predictor of adverse outcome in patients with heart failure (HF). Whether changes in HR over time in patients with chronic HF are also associated with adverse outcome is unknown. We explored the relationship between changes in HR from a preceding visit, time-updated HR (i.e. most recent available HR value from a clinic visit) and subsequent outcomes in patients with chronic HF. Methods and results: We studied 7599 patients enrolled in the candesartan in heart failure: assessment of reduction in mortality and morbidity program. We calculated change in HR from the preceding visit and explored its association with outcomes in Cox proportional hazards models, as well the association between time-updated HR and outcome. An increase in HR from preceding visit was associated with a higher risk of all-cause mortality and the composite endpoint of cardiovascular death or hospitalization for HF (adjusted hazard ratio 1.06, 95% confidence intervals, CI: 1.05–1.08, P < 0.001, per 5 b.p.m. higher HR), with lowering of HR being associated with lower risk, adjusting for covariates, including time-updated β-blocker dose and baseline HR. Time-updated resting HR at each visit was also associated with risk (adjusted hazard ratio 1.07, 95% CI: 1.06–1.09; P < 0.001, per 5 b.p.m. higher HR). Conclusions: Change in HR over time predicts outcome in patients with chronic HF, as does time-updated HR during follow-up. These data suggest that frequent outpatient monitoring of HR, and identification of changes over time, possibly with remote technologies, may identify patients with HF who may be at increased risk of rehospitalization or death.
Mary MacKillop Institute for Health Research