Performance of a multisensory implantable cardioverter-defibrillator algorithm for remote heart failure management: the RE-HEART registry
Authors: De Juan Baguda J , Pachon Iglesias M , Gavira Gomez J J , Martinez Mateo V , Arcocha Torres M F , Iniesta Manjavacas A M , Rivas Gandara N , Alonso Salinas G L , Goirigolzarri Artaza J J , Macias Gallego A M , Medina Moreno O , Martinez Martinez J G , Rubin Lopez J M , Cozar Leon R , Salguero Bodes R ,   RE-HEART registry group
Published: December 2021

Abstract

Background
The HeartLogic algorithm measures data from multiple implantable cardioverter-defibrillator-based (ICD) sensors and combines them into a single index. The associated alert has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation.

Objective
To analyze the association between HeartLogic alerts and clinical events and to describe the implementation in clinical practice of the algorithm for remote management of HF patients.

Methods
The association between HeartLogic alerts and clinical events has been analyzed in the blinded study Phase 1 (from ICD implantation to HeartLogic alert activation) and in the following unblinded Phase 2 and 3 (after HeartLogic activation). During Phase 1, patients were managed according to the standard clinical practice and physicians were blinded to the alert status. During Phase 2 physicians reacted to alerts according to their clinical practice, while during Phase 3 they followed a standardized protocol in response to alerts.

Results
We enrolled 288 patients who received HeartLogic-enabled ICD or CRT-D at 15 centers. 101 patients contributed to Phase 1. During a median observation period of 10 [95% CI: 5 – 19] months, the HeartLogic index crossed the alert-threshold value 73 times (0.72 alerts/patient-year) in 39 patients. 8 HF hospitalizations and 2 emergency room admissions occurred in 9 patients (0.10 events/patient-year) during HeartLogic IN alert state. Other 10 minor events (HF in-office visits and non-HF hospitalization) were associated with HeartLogic alerts. During the active phases 267 patients were observed for a median follow-up of 16 [95% CI: 15 – 22] months. 277 HeartLogic alerts (0.89 alerts/patient-year) occurred in 136 patients. Thirty-three HeartLogic alerts were associated with hospitalizations for HF or with HF death (n=6), and 46 alerts were associated with unplanned in-office visits for HF. In 78 cases, HeartLogic alerts were associated with other clinically relevant events. The rate of unexplained alerts was low (0.39 alerts/patient-year). During the active phases, one HF hospitalization and one unplanned in-office visit for HF occurred when patients were in OUT of alert state. Patient phone contacts or in-person assessments were performed more frequently in Phase 3 (85%) than in Phase 2 (73%; p=0.047), while alert-triggered actions were similar in the two phases. Most alerts in both Phases (82% in 2 and 81% in 3; p=0.861) were managed remotely. The total number of patient phone contacts performed during Phase 2 was 35 (0.65 contacts/patient-year) and during Phase 3 was 287 (1.12 contacts/patient-year; p=0.002).

Conclusions
HeartLogic index was frequently associated with HF-related clinical events, with a low rate of unexplained events. The HeartLogic alert and a standardize protocol of actions allowed to remotely detect impending decompensation events and to implement clinical actions with a low workload for the centers.

Funding Acknowledgement
Type of funding sources: None.