Association of Chronic Covert Cerebral Infarctions and White Matter Hyperintensities With Atrial Fibrillation Detection on Post‐Stroke Cardiac Rhythm Monitoring: A Cohort Study

BACKGROUND: This study was conducted to explore the association of different phenotypes, count, and location of chronic covert brain infarctions (CBIs) with detection of atrial fibrillation (AF) on prolonged post‐stroke cardiac rhythm monitoring (PCM). METHODS AND RESULTS: We conducted a cohort single‐center study of consecutive first‐ever ischemic stroke or transient ischemic attack patients undergoing PCM between January 2015 and December 2017. We blindly rated CBI phenotypes according to established definitions and white matter hyperintensities (WMHs) according to the age‐related white matter changes rating scale. We used (multiple) regression models to assess the association of the imaging biomarkers and incident AF on PCM. A total of 795 patients (median [interquartile range]) aged 69 (57–78) years, 41% women, median National Institutes of Health Stroke Scale score 2 (0–5), median PCM duration 14 (7–14) days, and AF detection in 61 patients (7.7%) were included. On univariate analysis, WMHs (per point odds ratio, 1.35 [95% CI, 1.03–1.78]) but not CBIs (odds ratio, 0.90 [95% CI, 0.52–1.56]) were associated with AF detection. Neither CBI phenotype, count, nor location were associated with AF detection. After adjustment for age, hypertension, and stroke severity, neither increasing WMHs (per point adjusted odds ratio, 0.85 [95% CI, 0.60–1.20]) nor CBIs (adjusted odds ratio, 0.60 [95% CI, 0.33–1.09]) were independently associated with AF detection. CONCLUSIONS: Although WMHs and CBIs represent surrogate biomarkers of vascular risk factors, neither WMHs nor CBIs, including their phenotypes, count, and location, were independently associated with AF detection on PCM. In patients with manifest ischemic stroke or transient ischemic attack, the presence of imaging biomarkers of chronic ischemic injury does not seem promising to further refine prediction tools for AF detection on PCM.