Sonja G Schütz1, Lynda D Lisabeth2, Fatema Shafie-Khorassani3, Erin Case2, Brisa N Sanchez4, Ronald D Chervin5, Devin L Brown6. 1. Sleep Disorders Center, Department of Neurology, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, USA. Electronic address: schuetzs@med.umich.edu. 2. Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. 3. Department of Biostatistics, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, USA. 4. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, 3215 Market St, Philadelphia, PA 19104, USA. 5. Sleep Disorders Center, Department of Neurology, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, USA. 6. Stroke Program, Department of Neurology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA.
Abstract
BACKGROUND: Obstructive sleep apnea (OSA) is highly prevalent in patients with ischemic stroke. Untreated OSA is associated with an increased risk of cardiovascular morbidity and OSA treatment may improve neurological recovery in stroke survivors, yet OSA in stroke patients remains poorly characterized. The goal of this study is to identify clinical phenotypes of ischemic stroke patients with OSA. METHODS: Participants (n = 451) with ischemic strokes and OSA (respiratory-event-index, (REI) ≥ 10/hour based on home sleep apnea testing) were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) project. Latent class analysis was performed based on the following variables: age, sex, race/ethnicity, REI, pre-stroke snoring, pre-stroke tiredness/fatigue, pre-stroke sleep duration, prior stroke history, NIHSS at presentation, body mass index (BMI), hypertension, diabetes, atrial fibrillation, coronary artery disease, and chronic heart failure. RESULTS: A model with three phenotype clusters provided the best fit. Cluster 1 (n = 55, 12%) was defined by higher NIHSS scores. Participants in cluster 2 (n = 253, 56%) were younger and had relatively low NIHSS scores. Cluster 3 (n = 143, 32%) included participants with severe OSA and higher prevalence of medical comorbidities. CONCLUSION: Ischemic stroke survivors with OSA can be categorized into three clinical phenotype clusters characterized by differences in stroke severity, OSA severity, age and medical comorbidities. This highlights the heterogeneity of post-stroke OSA. Awareness of the different faces of OSA in patients with ischemic stroke may help clinicians identify OSA in their patients, and inform research concerning the pathophysiology, treatment and prognostic impact of post-stroke OSA.
BACKGROUND:Obstructive sleep apnea (OSA) is highly prevalent in patients with ischemic stroke. Untreated OSA is associated with an increased risk of cardiovascular morbidity and OSA treatment may improve neurological recovery in stroke survivors, yet OSA in strokepatients remains poorly characterized. The goal of this study is to identify clinical phenotypes of ischemic strokepatients with OSA. METHODS:Participants (n = 451) with ischemic strokes and OSA (respiratory-event-index, (REI) ≥ 10/hour based on home sleep apnea testing) were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) project. Latent class analysis was performed based on the following variables: age, sex, race/ethnicity, REI, pre-stroke snoring, pre-stroketiredness/fatigue, pre-stroke sleep duration, prior stroke history, NIHSS at presentation, body mass index (BMI), hypertension, diabetes, atrial fibrillation, coronary artery disease, and chronic heart failure. RESULTS: A model with three phenotype clusters provided the best fit. Cluster 1 (n = 55, 12%) was defined by higher NIHSS scores. Participants in cluster 2 (n = 253, 56%) were younger and had relatively low NIHSS scores. Cluster 3 (n = 143, 32%) included participants with severe OSA and higher prevalence of medical comorbidities. CONCLUSION:Ischemic stroke survivors with OSA can be categorized into three clinical phenotype clusters characterized by differences in stroke severity, OSA severity, age and medical comorbidities. This highlights the heterogeneity of post-stroke OSA. Awareness of the different faces of OSA in patients with ischemic stroke may help clinicians identify OSA in their patients, and inform research concerning the pathophysiology, treatment and prognostic impact of post-stroke OSA.
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