BACKGROUND

Atrial fibrillation (AF) is one of the most common clinical arrhythmias. This study aims to predict the risk of post-stroke AF through electrocardiographic changes in sinus rhythm.

METHODS

We searched the MEDLINE (PubMed) and EMBASE databases to identify relevant research articles published until August 2023. Prioritized items from systematic reviews and meta-analyses were screened, and data related to AF detection rate were extracted. A meta-analysis using a random-effects model was conducted for data synthesis and analysis.

RESULTS

A total of 32 studies involving electrocardiograms (ECG) were included, with a total analysis population of 330,284 individuals. Among them, 16,662 individuals (ECG abnormal group) developed AF, while 313,622 individuals (ECG normal group) did not. ECG patterns included terminal P-wave terminal force V1, interatrial block (IAB), advanced interatrial block, abnormal P-wave axis, pulse rate prolongation, and atrial premature complexes. Overall, 15,762 patients experienced AF during the study period (4.77%). In the ECG abnormal group, the proportion was 14.21% (2367/16,662), while in the control group (ECG normal group), the proportion was 4.27% (13,395/313,622). The pooled risk ratio for developing AF was 2.45 (95% confidence interval [CI]: 2.02-2.98, P < .001), with heterogeneity (I2) of 95%. The risk ratio values of alAB, P-wave terminal force V1, interatrial block, abnormal P-wave axis, pulse rate prolongation and atrial premature complexes were 4.12 (95% CI, 2.99-5.66), 1.47 (95% CI, 1.19-1.82), 2.54 (95% CI, 1.83-3.52), 1.70 (95% CI, 0.98-2.97), 2.65 (95% CI, 1.88-3.72), 3.79 (95% CI, 2.12-6.76), respectively.

CONCLUSION

There is a significant correlation between ECG patterns and the occurrence of AF. The alAB exhibited the highest level of predictability for the occurrence of AF. These indicators support their use as screening tools to identify high-risk individuals who may benefit from further examinations or empirical anticoagulation therapy following stroke.