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

Abstract

Objective: To identify ECG changes in sinus rhythm that may be used to predict subsequent development of new AF. Method: We identified prospective and retrospective cohort or case control studies evaluating ECG patterns from a 12-lead ECG in sinus rhythm taken in hospital or community predicting subsequent development of new AF. For each identified ECG predictor, we then identify absolute event rates and pooled risk ratios (RR) using an aggregate level random effects meta-analysis. Results: We identified 609,496 patients from 22 studies. ECG patterns included P wave terminal force V1 (PTFV1), interatrial block (IAB) and advanced interatrial block (aIAB), abnormal P wave axis (aPWA), PR prolongation and atrial premature complexes (APCs). Pooled risk ratios reached significance for each of these; PTFV1 RR 1.48 (95% CI 1.04–2.10), IAB 2.54 (95% CI 1.64–3.93), aIAB 4.05 (95% CI 2.64–6.22), aPWA 1.89 (95% CI 1.25–2.85), PR prolongation 2.22 (95% CI 1.27–3.87) and APCs 3.71 (95% CI 2.23–6.16). Diabetes reduced the predictive value of PR prolongation. Conclusion: APC and aIAB were most predictive of AF, while IAB, PR prolongation, PTFV1 and aPWA were also significantly associated with development of AF. These support their use in a screening tool to identify at risk cohorts who may benefit from further investigation, or following stroke, with empirical anticoagulation.