Related Experiment Video

Updated: Jul 27, 2025

A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation
16:40

A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation

Published on: February 28, 2012

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Performance of a multisensor implantable defibrillator algorithm for heart failure monitoring related to

Vincenzo Ezio Santobuono1, Stefano Favale1, Antonio D'Onofrio2

  • 1Interdisciplinary Department of Medicine, Cardiology Unit Polyclinic of Bari, University of Bari 'Aldo Moro', Bari, Italy.

ESC Heart Failure
|June 6, 2023
PubMed

Insights

The HeartLogic algorithm effectively predicts heart failure decompensation in ICD patients, even with co-morbidities like atrial fibrillation and chronic kidney disease. This tool enhances patient monitoring and risk stratification for better outcomes.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Medical Devices

Background:

  • The HeartLogic algorithm uses implantable cardioverter-defibrillator (ICD) sensor data to predict heart failure (HF) decompensation.
  • Its efficacy has been established in cardiac resynchronization therapy with defibrillator (CRT-D) patients.
  • This study aimed to assess its performance in non-CRT ICD patients and those with co-morbidities.

Purpose of the Study:

  • To evaluate the HeartLogic algorithm's performance in predicting heart failure decompensation in patients with standard ICDs, not just CRT-D devices.
  • To assess the algorithm's effectiveness in the presence of co-morbidities such as atrial fibrillation (AF) and chronic kidney disease (CKD).
  • To determine if the algorithm's predictive capability varies based on device type or specific co-morbidities.

Main Methods:

  • The HeartLogic algorithm was activated in 568 ICD patients across 26 centers, including 410 with CRT-D.
  • Patient data were followed for a median of 26 months, recording hospitalizations, deaths, and HeartLogic alerts.
  • Statistical analyses, including incidence rate ratios and hazard ratios, were used to assess the algorithm's predictive accuracy and the impact of patient characteristics.

Main Results:

  • HeartLogic alerts were associated with a 13.35-fold increased risk of cardiovascular hospitalization or death.
  • Atrial fibrillation and chronic kidney disease independently predicted a higher burden of HeartLogic alerts.
  • The algorithm's ability to identify high-risk periods was consistent across different patient groups (CRT-D/ICD, AF/non-AF, CKD/non-CKD).

Conclusions:

  • The HeartLogic algorithm reliably predicts increased risk for clinical events in ICD patients, irrespective of device type (CRT-D vs. ICD).
  • Patients with atrial fibrillation and chronic kidney disease experienced more alerts but the algorithm's predictive power remained robust.
  • HeartLogic demonstrates continued value in monitoring and risk stratification for heart failure decompensation across diverse patient populations.
Abstract

Keywords:
Atrial fibrillationCRTChronic kidney diseaseHeart failureICDRisk stratification

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