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Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Pre-emptive treatment of heart failure exacerbations in patients managed with the HeartLogic™ algorithm
Rodrigue Garcia1,2, Daniel Gras3, Jacques Mansourati4
1Department of Cardiology, University Hospital of Poitiers, Poitiers, France.
Insights
This study evaluates the HeartLogic™ algorithm for predicting heart failure (HF) episodes. Remote monitoring of the HeartLogic™ index enables pre-emptive treatment, aiming to reduce hospitalizations in HF patients.
Area of Science:
- Cardiology
- Biomedical Engineering
Background:
- Heart failure (HF) affects millions globally, causing high mortality and healthcare costs.
- Current management often involves reactive treatment of decompensation.
- The HeartLogic™ algorithm offers a novel approach for proactive HF management.
Purpose of the Study:
- To assess the impact and security of pre-emptive heart failure management using the HeartLogic™ index.
- To evaluate the effectiveness of the HeartLogic™ algorithm in reducing HF hospitalizations.
- To gather real-world data on managing HF exacerbations.
Main Methods:
- Prospective, multi-centre, non-randomized study of 310 HF patients.
- Remote monitoring of the HeartLogic™ index for 12 months.
- Intervention triggered by HeartLogic™ index ≥16, including patient assessment and treatment adjustment.
Main Results:
- Primary endpoint: unscheduled heart failure hospitalization.
- Secondary endpoints include mortality, cardiovascular death, HF-related death, and arrhythmia hospitalizations.
- Safety of HeartLogic™-guided diuretic therapy initiation/increase will be assessed.
Conclusions:
- The HeartLogic™ France Cohort Study will yield robust real-world data.
- This data will support pre-emptive treatment strategies for heart failure exacerbations.
- The study aims to demonstrate the value of the HeartLogic™ algorithm in clinical practice.
Aims:
Heart failure (HF) is a chronic disease affecting 64 million people worldwide and places a severe burden on society because of its mortality, numerous re-hospitalizations and associated costs. HeartLogic™ is an algorithm programmed into implanted devices incorporating several biometric parameters which aims to predict HF episodes. It provides an index which can be monitored remotely, allowing pre-emptive treatment of congestion to prevent acute decompensation. We aim to assess the impact and security of pre-emptive HF management, guided by the HeartLogic™ index.
Methods And Results:
The HeartLogic™ France Cohort Study is an investigator-initiated, prospective, multi-centre, non-randomized study. Three hundred ten patients with a history of HF (left ventricular ejection fraction ≤40%; or at least one episode of clinical HF with elevated NT-proBNP ≥450 ng/L) and implanted with a cardioverter defibrillator enabling HeartLogic™ index calculation will be included across 10 French centres. The HeartLogic™ index will be monitored remotely for 12 months and in the event of a HeartLogic™ index ≥16, the local investigator will contact the patient for assessment and adjust HF treatment as necessary. The primary endpoint is unscheduled hospitalization for HF. Secondary endpoints are all-cause mortality, cardiovascular death, HF-related death, unscheduled hospitalizations for ventricular or atrial arrhythmia and HeartLogic™ index evolution over time. Blood samples will be collected for biobanking, and quality of life will be assessed. Finally, the safety of a HeartLogic™-triggered strategy for initiating or increasing diuretic therapy will be assessed. A blind and independent committee will adjudicate the events.
Conclusions:
The HeartLogic™ France Cohort Study will provide robust real-world data in a cohort of HF patients managed with the HeartLogic™ algorithm allowing pre-emptive treatment of heart failure exacerbations.
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