Villafranca Di Verona

Researchers are evaluating the HeartInsight algorithm, designed to predict acute heart failure events in patients with implanted Biotronik ICD or CRT-D devices that have atrial sensing and Home Monitoring. Heart failure is a serious condition with high rates of hospitalizations and healthcare costs. HeartInsight analyzes trends in seven physiological variables to provide early warnings of worsening heart failure, with a median lead time of 42 days. This study aims to assess how HeartInsight alerts are managed in routine clinical practice across multiple centers in Italy. About 100 patients will be enrolled across 14 centers and followed for 12 months. Participants have implanted devices with Home Monitoring and will be monitored remotely. When HeartInsight generates an alert, a standardized workflow guides clinical responses such as device adjustments, therapy optimization, unscheduled visits, or hospital admissions. The study collects data on alert frequency, clinical actions triggered, and patient use of the HeartInsight Patient App. Participants will provide informed consent and undergo standard remote monitoring and clinical visits. Data will be gathered through electronic case report forms, focusing on the proportion of alerts that lead to clinical actions, alert patterns, hospitalizations, and app usage. Safety and data quality will be monitored throughout. The study results aim to improve integration of predictive monitoring into patient care, potentially enhancing management and outcomes for heart failure patients.