Predicting all-cause mortality by means of a multisensor implantable defibrillator algorithm for heart failure

Antonio D'Onofrio1, Gennaro Vitulano2, Leonardo Calò3

  • 1Unità Operativa di Elettrofisiologia, Studio e Terapia delle Aritmie", Monaldi Hospital, Naples, Italy.

Heart Rhythm
|March 26, 2023
PubMed

Insights

The HeartLogic algorithm effectively predicts heart failure decompensation. Its alert states significantly identify patients at higher risk for mortality, aiding proactive care.

Area of Science:

  • Cardiology
  • Medical Devices
  • Predictive Analytics

Background:

  • The HeartLogic algorithm is a sensitive predictor of impending heart failure decompensation.
  • It integrates multiple physiological parameters into a single index for monitoring.

Purpose of the Study:

  • To evaluate if remotely monitored HeartLogic data can identify patients at high risk for mortality.
  • To assess the algorithm's utility in predicting all-cause mortality in heart failure patients.

Main Methods:

  • The HeartLogic algorithm, combining heart sounds, impedance, respiration, and activity, was activated in 568 patients with implantable cardioverter-defibrillators (ICDs).
  • Data from 26 centers were analyzed over a median follow-up of 26 months, focusing on "IN-alert" and "OUT of alert" states.
  • Multivariate analysis controlled for baseline confounders to assess mortality risk.

Main Results:

  • 1200 alerts were recorded in 370 patients (65%), with the "IN-alert" state comprising 13% of the observation period.
  • Patients in the "IN-alert" state had a significantly higher mortality rate (0.25 deaths/patient-year) compared to those "OUT of alert" (0.02 deaths/patient-year).
  • The "IN-alert" state remained a strong predictor of death (hazard ratio 9.18) after adjusting for baseline factors.

Conclusions:

  • The HeartLogic algorithm's index can identify patients at elevated risk for all-cause mortality.
  • The "IN-alert" state signifies periods of substantially increased risk of death, enabling timely clinical intervention.
Abstract

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