Prediction of all-cause mortality using a multisensor implantable defibrillator algorithm for HF monitoring

Background: The HeartLogic algorithm combines multiple implantable defibrillator (ICD) sensor data and has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation. Purpose: We determined if remotely monitored data from this algorithm can be used to identify patients at high risk of mortality. Methods: The HeartLogic feature was activated in 568 ICD patients from 26 centers. Results: During a median follow-up of 26 months [25th–75th percentile: 16-37], 1200 HeartLogic alerts were recorded in 370 (65%) patients. Overall, the time IN the alert state was 13% of the total observation period (151 out of 1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (37 in the group with alerts). Experiencing any alert episode was associated with a substantially increased risk of death [hazard ratio (HR): 2.08, 95% confidence interval (CI): 1.16–3.73, P = 0.039]. Additionally, a time IN alert ≥20%wasassociated with death (HR: 4.07, 95%CI: 2.19-7.54, p<0.001, Figure), even after multivariate correction for age, atrial fibrillation on implantation, chronic kidney disease, ischemic cardiomyopathy (HR: 3.26, 95%CI:1.87-5.70, p<0.001). The rate of death was 0.25/patient-year (95%CI: 0.17-0.34) with the HeartLogic IN the alert state and 0.02/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<0.001). Conclusions: The HeartLogic algorithm provides an index that can be used to identify patients at higher risk of all-cause mortality. The index status identifies periods of significantly increased risk of death.