Prediction of ineffective elective cardioversion of atrial fibrillation: a retrospective multi-center patient cohort

Tapio Hellman1, Tuomas Kiviniemi2, Tuija Vasankari2

  • 1Department of Medicine, Turku University Hospital and University of Turku, Hämeentie 11, PO Box 52, 20521, Turku, Finland.

Insights

Predictors for ineffective elective cardioversion (ECV) for atrial fibrillation (AF) were identified. Female gender, longer AF history, and certain patient characteristics increase the risk of ECV failure or recurrence.

Area of Science:

  • Cardiology
  • Electrophysiology

Background:

  • Elective cardioversion (ECV) is a standard treatment for restoring normal sinus rhythm in patients with atrial fibrillation (AF).
  • Predictors for the effectiveness of ECV, defined as failure to maintain sinus rhythm within 30 days, remain largely unknown.

Purpose of the Study:

  • To identify clinical predictors associated with ineffective ECV in a large cohort of patients with AF.
  • To analyze factors contributing to both ECV failure and early recurrence of AF post-procedure.

Main Methods:

  • A retrospective multi-center study involving 1998 ECV procedures for AF lasting over 48 hours in 1342 patients.
  • Data collection included follow-up information up to 30 days post-ECV to assess outcomes.

Main Results:

  • Overall, 15.2% of ECVs failed, and 32.4% of successful ECVs resulted in AF recurrence within 30 days, leading to an overall ineffective ECV rate of 42.6%.
  • Independent predictors for ECV failure included long AF history (>5 years) and AF duration (>30 days).
  • Predictors for recurrence and overall ineffective ECV included female gender, higher ventricular rate, renal failure, and antiarrhythmic drug use at discharge.

Conclusions:

  • Female gender, antiarrhythmic drug therapy, and renal failure are significant predictors for both AF recurrence and overall ineffective ECV.
  • This study provides novel insights into clinical predictors of ineffective ECV in a large, real-world patient population.
Abstract

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