Systematic review and meta-analysis on the impact on outcomes of device algorithms for minimizing right ventricular pacing.
Davide Antonio MeiJacopo Francesco ImbertiMarco VitoloNiccolò BoniniKevin SerafiniMarta MantovaniEnrico TartagliaChiara BirtoloMarco ZuinMatteo BertiniGiuseppe BorianiPublished 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 (2024)
Algorithms for RVPm may be effective in reducing the risk of PerAF and CV hospitalization in patients requiring anti-bradycardia therapies, without an increased risk of adverse symptoms. These results are also consistent for studies enrolling a high percentage of AVB patients.
Keyphrases
- end stage renal disease
- ejection fraction
- machine learning
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- emergency department
- type diabetes
- adipose tissue
- deep learning
- physical activity
- depressive symptoms
- patient reported outcomes
- atrial fibrillation
- left ventricular
- insulin resistance
- sleep quality
- adverse drug