Atrial fibrillation is the most common cardiac arrhythmia with its prevalence expected to increase to 12.1 million people in the United States by 2030. Chronic underlying conditions that affect the heart and lungs predispose patients to develop atrial fibrillation. Obstructive sleep apnea is strongly associated with atrial fibrillation. Several pathophysiological mechanisms have been proposed to elucidate this relationship which includes electrophysiological substrate modification and the contribution of the autonomic nervous system. In this comprehensive review, we highlight important relationships and plausible causality between obstructive sleep apnea and atrial fibrillation which will improve our understanding in the evaluation, management, and prevention of atrial fibrillation. This is the most updated comprehensive review of the relationship between obstructive sleep apnea and atrial fibrillation.

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Introduction: African American (AA) patients have a higher incidence of stroke but lower prevalence of atrial fibrillation (AF). Studies involving long term monitoring with implantable cardiac monitors (ICM) for AF after cryptogenic stroke are limited by the under-representation of the AA population. Objective: We sought to assess racial differences in the diagnosis of AF by implantable cardiac monitors in patients with cryptogenic stroke. Methods: We performed a retrospective chart review study at Methodist University Hospital, University of Tennessee Health Science Center, Memphis TN. We included patients with cryptogenic stroke who received an ICM from September 2014 to June 2019 to assess for AF. Race and additional demographic characteristics were obtained from the electronic medical records. Interrogation reports from the ICMs were obtained by remote monitoring as well as clinic visits. Fisher exact and student t test were used to compare demographic data as well as the incidence of AF in these patients. Results: A total of 219 patients with cryptogenic stroke who underwent ICM implantation were included, of which 129 (58.9%) were AA. In the AA cohort, the patients were significantly younger than (62.3 versus 65.8 years; p =0.04) and had a significantly higher prevalence of hypertension (92.2% versus 68.5%; p <0.01) and diabetes mellitus (40.3% versus 27.3%; p =0.04). Upon a mean follow up of 10.6 months, a total of 39 patients (17.8%) were diagnosed with AF on ICM monitoring. The mean time to the incidence of AF was 7.4 months. There was no significant difference in the incidence of AF in the AA population (17.8%) as compared to the rest of the population (17.8%) ( p =1.00). Conclusion: In this single center study of patients with cryptogenic stroke who underwent long term monitoring with ICM, there was no significant difference in the incidence of AF between AA and the rest of the population. We conclude that ICM’s have an equally important role in AF detection in AA patients as in the general population with cryptogenic stroke.

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