Performance of a multisensor implantable defibrillator algorithm for HF monitoring in the presence of atrial fibrillation.
Giuseppe BorianiMatteo BertiniMichele ManzoLeonardo CalòLuca SantiniGianluca SavareseAntonio Dello RussoVincenzo Ezio SantobuonoCarlo LavalleMiguel ViscusiClaudia AmelloneRaimondo CalvaneseAmato SantoroAntonio RapacciuoloMatteo ZiacchiGiuseppe ArenaJacopo Francesco ImbertiMonica CampariSergio ValsecchiAntonio D'OnofrioPublished in: 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 (2023)
Patients received more alerts during periods of AF. The ability of the algorithm to identify increased risk of HF events was confirmed during AF, despite a lower IN/OUT-of-alert incidence rate ratio in comparison with non-AF periods and non-AF patients.
Keyphrases
- atrial fibrillation
- end stage renal disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- machine learning
- heart failure
- prognostic factors
- deep learning
- catheter ablation
- percutaneous coronary intervention
- left atrial
- acute coronary syndrome
- left atrial appendage
- left ventricular
- patient reported
- acute heart failure
- cardiac resynchronization therapy