The goal of the study is to calibrate the algorithmic model of the TakeCoeur AI device to detect early heart failure decompensation in patients with heart failure, using physiological data (clinical) actively and passively collected through connected medical devices (watch, blood pressure monitor, and scale).
Age ≥ 18 years
Hospitalization in the past 12 months for a heart failure exacerbation.
NYHA class II to IV (New York Heart Association) at the time of inclusion, with elevated natriuretic peptide levels (BNP > 100 pg/mL or NT-proBNP > 1000 pg/mL).
French speaking patient
Patient undergoing dialysis for renal failure
Patient who has received or is scheduled to receive a heart transplant or circulatory assistance within the next 12 months
Patient with a left ventricular ejection fraction ≥ 50% (for non-diastolic heart failure)
Obese patient with a body mass index ≥ 40 kg/m²
Participation in the study will be offered to any patient consulting a cardiologist/cardio-geriatrician at one of the participating centers who meets the inclusion criteria and non inclusion criteria.
Cohort
Prospective
Not listed
Concordance between the detection of heart failure decompensation by the TakeCoeur AI device and the occurrence of heart failure decompensation
calibrate the algorithmic model of the TakeCoeur IA device for early detection of cardiac decompensation in patients suffering from heart failure.
Evaluate the time (in days) to anticipate cardiac decompensation
time to predict (in days) the risk of cardiac decompensation
Evaluate the compliance of patients with heart failure to the Takecoeur IA device and its connected collection accessories
\- Monthly questionnaire (scale 0 to 4 for edema and shortness of breath) completion rate defined by the following formula: (number of completed questionnaires / total number of questionnaires to be completed) x 100
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This trial is not recruiting at the moment. You can still explore other options:
