Risk prediction in patients with heart failure with preserved ejection fraction: the LIFE-Preserved model
European Heart Journal

Abstract
Heart failure (HF) with preserved ejection fraction (HFpEF) constitutes a heterogeneous disease with varying prognosis. Given the rising incidence of HFpEF, accurate risk prediction for these patients is needed to identify high-risk individuals, who may benefit the most from preventive treatments. The LIFE-Preserved model was developed and validated for the prediction of individual short-term and lifetime risk for HF hospitalization or cardiovascular (CV) death in patients with HFpEF.
LIFE-Preserved was derived in 20 332 patients aged 40–90 years with a left ventricular ejection fraction ≥ 50% from the Swedish HF Registry. Cause- and sex-specific Cox models were derived to predict the risk of HF hospitalization or CV death using 14 routinely available predictors. Use of age as the timescale allowed for predictions beyond the maximum follow-up duration in the derivation data, adjusted for competing risks. External validation was performed in two trials (EMPEROR-Preserved and TOPCAT-Americas) and three registries (NHS England Secure Data Environment, Veterans Affairs, and HF-Particles). Model performance was assessed by discrimination and calibration.
During a median follow-up of 1.8 years (interquartile range .6–4.2, maximum 19 years), 9341 first HF hospitalizations or CV deaths (46%) were observed in Swedish HF Registry. External validation included data from 28 062 patients with HFpEF [9930 (35%) first HF hospitalizations or CV deaths]. Pooled C-statistics were .714 (95% confidence interval .652–.775) in trials and .658 (95% confidence interval .599–.717 in registries, with adequate calibration in all external validation sources. Performance was similar in men and women. An interactive calculator of the LIFE-Preserved model has been made available
The LIFE-Preserved model enables prediction of short-term and lifetime risk of HF hospitalization or CV death in patients with HFpEF. The model could serve as a tool to identify high-risk HFpEF patients, guiding clinical management and shared decision-making.
Contributors

Tessa H Reitsma
Author

Łukasz Kuźma
Author

Salil V Deo
Author

Lisa Pennells
Author
University of Cambridge Cambridge , United Kingdom of Great Britain & Northern Ireland

Steven H J Hageman
Author

Joris Holtrop
Author

Lina Benson
Author

Nathalie Conrad
Author

Lars H Lund
Author

Stephen Kaptoge
Author

Spencer J Keene
Author

Chimweta Chilala
Author

Matilda Pitt
Author

Robert A Fletcher
Author

Kamlesh Khunti
Author

Xavier Rossello
Author

Jennifer S Lees
Author
University of Glasgow Glasgow , United Kingdom of Great Britain & Northern Ireland

John William McEvoy
Author

Angela M Wood
Author

Charlotte Andersson
Author

Frank L J Visseren
Author

Stefan Koudstaal
Author

Emanuele Di Angelantonio
Author
University of Cambridge Cambridge , United Kingdom of Great Britain & Northern Ireland

Emanuele Angelantonio
Author

Ana Abreu
Author

Frank Visseren
Author

Maryam Kavousi
Author

John William McEvoy
Author
You may be interested in









