ArticleESC heart failure2023
Performance of a multisensor implantable defibrillator algorithm for heart failure monitoring related to co-morbidities.
Article in ESC heart failure, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Algorithm-based remote monitoring of heart failure risk data in people with cardiac implantable electronic devices: a systematic review and cost-effectiveness analysis.Health technology assessment (Winchester, England) · 2025Pooled it
- Impact of Multisensor CIED-based Heart Failure Monitoring on Mortality, Heart Failure Hospitalizations and Outpatient Visits: A Systematic Review.Current heart failure reports · 2025Pooled it
- Effect of sacubitril/valsartan and SGLT2 inhibitors on arrhythmia burden in ICD patients.BMC cardiovascular disorders · 2026Article
- AI-Enabled Sensor Technologies for Remote Arrhythmic Monitoring in High-Risk Cardiomyopathy Genotypes.Sensors (Basel, Switzerland) · 2026Review
- Sailing Across Contraception, Pregnancy, and Breastfeeding: The Complex Journey of Women with Cardiomyopathies.Journal of clinical medicine · 2025Review
- Evaluation of real-world application of cardiac implantable electronic device-based multi-sensor algorithm for heart failure management.European heart journal. Digital health · 2025Article
- Predicting New-Onset Atrial Fibrillation in Hypertrophic Cardiomyopathy: A Review.Journal of clinical medicine · 2025Review
- Remote Management of Heart Failure in Patients with Implantable Devices.Diagnostics (Basel, Switzerland) · 2024Review
- Missense and Non-Missense Lamin A/C Gene Mutations Are Similarly Associated with Major Arrhythmic Cardiac Events: A 20-Year Single-Centre Experience.Biomedicines · 2024Article
- Association between amount of biventricular pacing and heart failure status measured by a multisensor implantable defibrillator algorithm.Cardiovascular digital health journal · 2024Article
- Harmony in Chaos: Deciphering the Influence of Ischemic Cardiomyopathy and Non-Cardiac Comorbidities on Holter ECG Parameters in Chronic Heart Failure Patients: A Pilot Study.Medicina (Kaunas, Lithuania) · 2024Article
- Cardiac Magnetic Resonance as Risk Stratification Tool in Non-Ischemic Dilated Cardiomyopathy Referred for Implantable Cardioverter Defibrillator Therapy-State of Art and Perspectives.Journal of clinical medicine · 2023Review
- Performance of a multi-sensor implantable defibrillator algorithm for heart failure monitoring in the presence of atrial fibrillation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023Observational
- Performance of a multisensor implantable defibrillator algorithm for heart failure monitoring related to co-morbidities.ESC heart failure · 2023Article
Corrections and comments
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Authors and funding
20 authors at 16 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThe 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 in cardiac resynchronization therapy (CRT-D) patients. We evaluated the performance of this algorithm in non-CRT ICD patients and in the presence of co-morbidities. METHODS AND
resultsThe HeartLogic feature was activated in 568 ICD patients (410 with CRT-D) from 26 centres. The median follow-up was 26 months [25th-75th percentile: 16-37]. During follow-up, 97 hospitalizations were reported (53 cardiovascular) and 55 patients died. We recorded 1200 HeartLogic alerts in 370 patients. Overall, the time IN the alert state was 13% of the total observation period. The rate of cardiovascular hospitalizations or death was 0.48/patient-year (95% CI: 0.37-0.60) with the HeartLogic IN the alert state and 0.04/patient-year (95% CI: 0.03-0.05) OUT of the alert state, with an incidence rate ratio of 13.35 (95% CI: 8.83-20.51, P < 0.001). Among patient characteristics, atrial fibrillation (AF) on implantation (HR: 1.62, 95% CI: 1.27-2.07, P < 0.001) and chronic kidney disease (CKD) (HR: 1.53, 95% CI: 1.21-1.93, P < 0.001) independently predicted alerts. HeartLogic alerts were not associated with CRT-D versus ICD implantation (HR: 1.03, 95% CI: 0.82-1.30, P = 0.775). Comparisons of the clinical event rates in the IN alert state with those in the OUT of alert state yielded incidence rate ratios ranging from 9.72 to 14.54 (all P < 0.001) in all groups of patients stratified by: CRT-D/ICD, AF/non-AF, and CKD/non-CKD. After multivariate correction, the occurrence of alerts was associated with cardiovascular hospitalization or death (HR: 1.92, 95% CI: 1.05-3.51, P = 0.036).
conclusionsThe burden of HeartLogic alerts was similar between CRT-D and ICD patients, while patients with AF and CKD seemed more exposed to alerts. Nonetheless, the ability of the HeartLogic algorithm to identify periods of significantly increased risk of clinical events was confirmed, regardless of the type of device and the presence of AF or CKD.
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