Monitoring for atrial fibrillation prior to patent foramen ovale closure after cryptogenic stroke

Hans-Christoph Diener1, Rolf Wachter2, Andrew Wong3

  • 1Department of Neuroepidemiology, Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), Medical Faculty of the University of Duisburg-Essen, Essen, Germany.

Insights

For cryptogenic stroke patients undergoing patent foramen ovale closure, personalized atrial fibrillation monitoring is key. This strategy identifies patients most likely to benefit from extended cardiac monitoring to prevent recurrent strokes.

Area of Science:

  • Cardiology
  • Neurology
  • Medical Diagnostics

Background:

  • Cryptogenic stroke (CS) patients with patent foramen ovale (PFO) are candidates for PFO closure.
  • Screening for atrial fibrillation (AF) is crucial in these patients.
  • Optimal AF monitoring strategies (technology, duration) for CS patients with PFO lack clear guidance.

Purpose of the Study:

  • To review cardiac rhythm monitoring practices in CS patients considered for PFO closure.
  • To analyze stroke recurrence, monitoring findings, and predictors of AF detection in CS patients.
  • To propose a personalized AF monitoring strategy for CS patients undergoing PFO closure.

Main Methods:

  • Narrative literature review.
  • Analysis of factors predicting AF detection.
  • Evaluation of risk scores (CHA 2 DS 2 -VASc, AF-ESUS, RoPE, PASCAL).

Main Results:

  • Predictors for AF detection include age, left atrial enlargement, PR interval, premature atrial contractions, conduction block, diabetes, prior infarctions, leukoaraiosis, elevated natriuretic peptides, and family history.
  • Risk scores like CHA 2 DS 2 -VASc and AF-ESUS, along with PFO-specific scores (RoPE, PASCAL), aid risk stratification.
  • A personalized approach considers AF detection likelihood and PFO features.

Conclusions:

  • A personalized AF detection strategy is proposed for CS patients undergoing PFO closure.
  • This approach aims to ensure confidence in the absence of AF.
  • The strategy incorporates factors predicting AF detection and high-risk PFO features.
Abstract

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