Developing and validating models to predict sudden death and pump failure death in patients with heart failure and prese
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ORIGINAL PAPER
Developing and validating models to predict sudden death and pump failure death in patients with heart failure and preserved ejection fraction Li Shen1,2 · Pardeep S. Jhund2 · Inder S. Anand3 · Peter E. Carson4 · Akshay S. Desai5 · Christopher B. Granger6 · Lars Køber7 · Michel Komajda8 · Robert S. McKelvie9 · Marc A. Pfeffer5 · Scott D. Solomon5 · Karl Swedberg10 · Michael R. Zile11 · John J. V. McMurray2 Received: 25 August 2020 / Accepted: 24 November 2020 © The Author(s) 2020
Abstract Background Sudden death (SD) and pump failure death (PFD) are leading modes of death in heart failure and preserved ejection fraction (HFpEF). Risk stratification for mode-specific death may aid in patient enrichment for new device trials in HFpEF. Methods Models were derived in 4116 patients in the Irbesartan in Heart Failure with Preserved Ejection Fraction trial (I-Preserve), using competing risks regression analysis. A series of models were built in a stepwise manner, and were validated in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM)-Preserved and Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trials. Results The clinical model for SD included older age, men, lower LVEF, higher heart rate, history of diabetes or myocardial infarction, and HF hospitalization within previous 6 months, all of which were associated with a higher SD risk. The clinical model predicting PFD included older age, men, lower LVEF or diastolic blood pressure, higher heart rate, and history of diabetes or atrial fibrillation, all for a higher PFD risk, and dyslipidaemia for a lower risk of PFD. In each model, the observed and predicted incidences were similar in each risk subgroup, suggesting good calibration. Model discrimination was good for SD and excellent for PFD with Harrell’s C of 0.71 (95% CI 0.68–0.75) and 0.78 (95% CI 0.75–0.82), respectively. Both models were robust in external validation. Adding ECG and biochemical parameters, model performance improved little in the derivation cohort but decreased in validation. Including NT-proBNP substantially increased discrimination of the SD model, and simplified the PFD model with marginal increase in discrimination.
Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s0039 2-020-01786-8. * John J. V. McMurray [email protected] 1
Department of Medicine, Hangzhou Normal University, Hangzhou 310003, China
British Heart Foundation Cardiovascular Research Centre, University of Glasgow, 126 University Place, Glasgow G12 8TA, UK
2
6
Duke Clinical Research Institute, Duke University, Durham, NC, USA
7
Rigshospitalet Copenhagen University Hospital, Copenhagen, Denmark
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Department of Cardiology, Hospital Saint Joseph, Paris, France
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Western University, London, ON, Canada
3
Department of Medicine, University of Minnesota Medical School and VA Medical Center, Minneapolis, USA
10
Department o
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