Personalizing configuration for atrial fibrillation external electrical cardioversion to improve first shock efficacy
Giulia Massaro1, Stefano Spagni1, Cristian Martignani1
1Cardiology Unit, Cardio-Thoracic-Vascular Building, S.Orsola-Malpighi Policlinic, University of Bologna, Bologna.
Optimizing electrical cardioversion (ECV) for atrial fibrillation (AF) involves choosing electrode configurations based on patient height and weight. A new algorithm improves first shock success and reduces impedance for effective AF treatment.
Area of Science:
- Cardiology
- Medical Devices
- Electrophysiology
Background:
- Biphasic electrical cardioversion (ECV) is commonly used for atrial fibrillation (AF) conversion.
- Current recommendations for electrode configuration in ECV are lacking.
- This study addresses the need for evidence-based guidance on electrode selection.
Purpose of the Study:
- To compare the efficacy of antero-apical pads (AAP) and antero-posterior adhesive patches (APP) for ECV in AF patients.
- To develop and validate a decision algorithm for personalizing ECV electrode configuration.
- To optimize ECV success rates and reduce energy requirements.
Main Methods:
- A quasi-experimental design was employed, enrolling all candidates for ECV for AF.
- The study involved two stages: initial comparison of AAP and APP, followed by validation of a developed decision algorithm.
- Patient data, including body surface area (BSA), height, and weight, were analyzed to inform the algorithm.
Main Results:
- Both APP and AAP configurations showed similar initial conversion rates (86.9% vs. 87.4%).
- BSA was an independent predictor of success; height (≤1.73m) was significant for AAP, while weight (<83kg) was significant for APP.
- The validated algorithm improved first shock efficacy (93.2% vs. 87.2%) and significantly reduced shock impedance (70.8 ± 15.3 vs. 81.8 ± 15.6).
Conclusions:
- Patient characteristics like BSA, height, and weight influence the choice of electrode configuration for ECV in AF.
- A personalized approach using a decision algorithm can optimize ECV outcomes.
- These findings offer potential for improving the clinical practice of ECV for AF management.
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