Background: The HeartLogic algorithm (Boston Scientific, St Paul, MN) integrates data from implantable cardioverter-defibrillator (ICD) sensors to predict heart failure (HF) decompensation: first (S1) and third (S3) heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume (RSBI), and night heart rate. Objective: This study assessed the relative changes in ICD sensors at the onset of HeartLogic alerts, their association with patient characteristics, and outcomes. Methods: The study included 568 patients with HF carrying ICDs (CRT-D, n = 410) across 26 centers, with a median follow-up of 26 months. HeartLogic alerts triggered patient contact and potential treatment. Results: A total of 1200 HeartLogic alerts were recorded in 370 patients. The sensor with the highest change at the alert's onset was S3 in 27% of alerts, followed by S3/S1 (25%). Patients with atrial fibrillation (AF) and chronic kidney disease (CKD) at implantation had higher prevalence of alerts (AF, 84% vs no AF, 58%; CKD, 72% vs no CKD, 59%; P < .05) and rate (AF, 1.51 per patient-year vs no AF, 0.88 per patient-year; CKD, 1.30 per patient-year vs no CKD, 0.89 per patient-year; P < .05). During follow-up, 247 patients experienced more than 1 alert; in 85%, the sensor with the highest change varied between successive alerts. Of the 88 (7%) alerts associated with HF hospitalization or death, respiration rate or RSBI (11%, P = .007 vs S3/S1) and night heart rate (11%, P = .031 vs S3/S1) were more commonly the sensors showing the highest change. Clinical events were more common with the first alert (12.6%) than subsequent alerts (5.2%, P < .001). Conclusion: HeartLogic alerts are mostly triggered by changes in heart sounds, but clinical events are more linked to respiration rate, RSBI, and night heart rate. Recurrent alerts often involve different sensors, indicating diverse mechanisms of HF progression.
Differentiating sensor changes in a composite heart failure ICD monitoring index: clinical correlates and implications / Compagnucci, Paolo; Santobuono, Vincenzo Ezio; D'Onofrio, Antonio; Vitulano, Gennaro; Calò, Leonardo; Bertini, Matteo; Santini, Luca; Savarese, Gianluca; Lavalle, Carlo; Viscusi, Miguel; Giammaria, Massimo; Pecora, Domenico; Calvanese, Raimondo; Santoro, Amato; Ziacchi, Matteo; Casella, Michela; Averina, Viktoria; Campari, Monica; Valsecchi, Sergio; Capucci, Alessandro; Dello Russo, Antonio. - In: HEART RHYTHM. - ISSN 1547-5271. - (2024). [10.1016/j.hrthm.2024.10.021]
Differentiating sensor changes in a composite heart failure ICD monitoring index: clinical correlates and implications
Santini, Luca;Lavalle, Carlo;Casella, Michela;
2024
Abstract
Background: The HeartLogic algorithm (Boston Scientific, St Paul, MN) integrates data from implantable cardioverter-defibrillator (ICD) sensors to predict heart failure (HF) decompensation: first (S1) and third (S3) heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume (RSBI), and night heart rate. Objective: This study assessed the relative changes in ICD sensors at the onset of HeartLogic alerts, their association with patient characteristics, and outcomes. Methods: The study included 568 patients with HF carrying ICDs (CRT-D, n = 410) across 26 centers, with a median follow-up of 26 months. HeartLogic alerts triggered patient contact and potential treatment. Results: A total of 1200 HeartLogic alerts were recorded in 370 patients. The sensor with the highest change at the alert's onset was S3 in 27% of alerts, followed by S3/S1 (25%). Patients with atrial fibrillation (AF) and chronic kidney disease (CKD) at implantation had higher prevalence of alerts (AF, 84% vs no AF, 58%; CKD, 72% vs no CKD, 59%; P < .05) and rate (AF, 1.51 per patient-year vs no AF, 0.88 per patient-year; CKD, 1.30 per patient-year vs no CKD, 0.89 per patient-year; P < .05). During follow-up, 247 patients experienced more than 1 alert; in 85%, the sensor with the highest change varied between successive alerts. Of the 88 (7%) alerts associated with HF hospitalization or death, respiration rate or RSBI (11%, P = .007 vs S3/S1) and night heart rate (11%, P = .031 vs S3/S1) were more commonly the sensors showing the highest change. Clinical events were more common with the first alert (12.6%) than subsequent alerts (5.2%, P < .001). Conclusion: HeartLogic alerts are mostly triggered by changes in heart sounds, but clinical events are more linked to respiration rate, RSBI, and night heart rate. Recurrent alerts often involve different sensors, indicating diverse mechanisms of HF progression.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
