Predictors of paroxysmal atrial fibrillation in patients with a cryptogenic stroke: Selecting patients for long-term rhythm monitoring

Abstract

BackgroundAfter a cryptogenic stroke, patients often will require prolonged cardiac monitoring; however, the subset of patients who would benefit from long-term rhythm monitoring is not clearly defined. ObjectiveThe purpose of this study was to create a risk score by identifying significant predictors of atrial fibrillation (AF) using age, sex, comorbidities, baseline 12-lead electrocardiogram, short-term rhythm monitoring, and echocardiographic data and to compare it to previously published risk scores. MethodsPatients admitted to Montefiore Medical Center between May 2017 and June 2022 with a primary diagnosis of cryptogenic stroke or transient ischemic attack who underwent long-term rhythm monitoring with an implantable cardiac monitor were retrospectively analyzed. ResultsVariables positively associated with a diagnosis of clinically significant AF include age (P <.001), race (P = .022), diabetes status (P = .026), chronic obstructive pulmonary disease status (P = .012), presence of atrial runs (P = .003), number of atrial runs per 24 hours (P <.001), total number of atrial run beats per 24 hours (P <.001), number of beats in the longest atrial run (P <.001), left atrial enlargement (P = .007), and at least mild mitral regurgitation (P = .009). We created a risk stratification score for our population, termed the ACL score. The ACL score demonstrated superiority to the CHA2DS2-VASc score and comparability to the C2HEST score for predicting device-detected AF. ConclusionThe ACL score enables clinicians to better predict which patients are more likely to be diagnosed with device-detected AF after a cryptogenic stroke.