Predicting risk of AF in ischaemic stroke using sinus rhythm ECG abnormalities: A meta-analysis

Area of Science:

• Cardiology
• Electrophysiology
• Preventive Medicine

Background:

• Atrial fibrillation (AF) is a common arrhythmia with significant health implications.
• Identifying individuals at risk for developing new-onset AF is crucial for timely intervention.
• Electrocardiogram (ECG) in sinus rhythm may offer predictive insights into future AF development.

Approach:

• A systematic review and meta-analysis of 22 studies involving 609,496 patients.
• Evaluation of specific ECG patterns in sinus rhythm as predictors of new AF.
• Pooled risk ratios (RR) were calculated for identified ECG predictors.

Key Points:

• Several ECG patterns significantly predicted new AF: P wave terminal force V1 (PTFV1), interatrial block (IAB), advanced interatrial block (aIAB), abnormal P wave axis (aPWA), PR prolongation, and atrial premature complexes (APCs).
• Advanced interatrial block (aIAB) (RR 4.05) and atrial premature complexes (APCs) (RR 3.71) demonstrated the highest predictive value.
• Diabetes mellitus was found to diminish the predictive accuracy of PR prolongation.

Conclusions:

• ECG findings like APCs and aIAB are strong predictors of future AF.
• These ECG markers can be integrated into screening tools to identify at-risk populations.
• Early identification facilitates targeted investigations or empirical anticoagulation, particularly post-stroke.