Combining home monitoring temporal trends from implanted defibrillators and baseline patient risk profile to predict heart failure hospitalizations: results from the SELENE HF study.

ABSTRACT:

Aims

We developed and validated an algorithm for prediction of heart failure (HF) hospitalizations using remote monitoring (RM) data transmitted by implanted defibrillators.

Methods and results

The SELENE HF study enrolled 918 patients (median age 69 years, 81% men, median ejection fraction 30%) with cardiac resynchronization therapy (44%), dual-chamber (38%), or single-chamber defibrillators with atrial diagnostics (18%). To develop a predictive algorithm, temporal trends of diurnal and nocturnal heart rates, ventricular extrasystoles, atrial tachyarrhythmia burden, heart rate variability, physical activity, and thoracic impedance obtained by daily automatic RM were combined with a baseline risk-stratifier (Seattle HF Model) into one index. The primary endpoint was the firs

SUBMITTER: D'Onofrio A 

PROVIDER: S-EPMC8824514 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature