Predicting atrial fibrillation in ischaemic stroke: a systematic review.

Abstract

Background and Aims

There has been renewed research interest in atrial fibrillation (AF) and increased stroke risk in the last decade. The occurrence of embolic stroke in the absence of AF has given rise to the new description of embolic stroke of undetermined source (ESUS). Current data suggests that AF is detected in approximately 30% of ESUS patients. Traditional methods, like 24-hour telemetry, detect AF in a small proportion of ESUS, while using prolonged Holter monitor or implantable loop recorders improves detection further. The latter, while being a more sensitive tool, is invasive and costly. Should we continue focusing on detection or expand to include accurate prediction of AF? In addition, do clinical predictors of AF exist? Method We conducted a systematic review of the literature to identify clinical predictors of AF. Results There is a body of research on predicting risk of AF. Identified variables include age, sex, cardiovascular risk factors, and ECG and echocardiogram abnormalities. We identified several tools ranging from moderate to strong predictive models for AF. However, none included recent biochemical tests and novel ECG changes. Conclusion We suggest that a mix of established and new variables and parameters be used to create a composite tool, enabling clinicians to accurately predict risk of AF in patients with ESUS, and informing decision-making regarding use of oral anticoagulants in preventing embolic events. Once developed, the tool will be tested in a suitable population. Generalizability should be a key feature of the tool to ensure equitability of use, in developed and developing economies.