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

Background: The HeartLogic algorithm (Boston Scientific) has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation. Objective: The purpose of this study was to determine whether remotely monitored data from this algorithm could be used to identify patients at high risk for mortality. Methods: The algorithm combines implantable cardioverter-defibrillator (ICD)–measured accelerometer-based heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume, night heart rate, and patient activity into a single index. An alert is issued when the index crosses a programmable threshold. The feature was activated in 568 ICD patients from 26 centers. Results: During median follow-up of 26 months [25th–75th percentile 16–37], 1200 alerts were recorded in 370 patients (65%). Overall, the time IN-alert state was 13% of the total observation period (151/1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (46 in the group with alerts). The rate of death was 0.25 per patient-year (95% confidence interval [CI] 0.17–0.34) IN-alert state and 0.02 per patient-year (95% CI 0.01–0.03) OUT of the alert state, with an incidence rate ratio of 13.72 (95% CI 7.62–25.60; P <.001). After multivariate correction for baseline confounders (age, ischemic cardiomyopathy, kidney disease, atrial fibrillation), the IN-alert state remained significantly associated with the occurrence of death (hazard ratio 9.18; 95% CI 5.27–15.99; P <.001). Conclusion: The HeartLogic algorithm provides an index that can be used to identify patients at higher risk for all-cause mortality. The index state identifies periods of significantly increased risk of death.