Age- and sex-stratified prevalence of obstructive sleep apnea and stroke risk comorbidities: A large cross-sectional EHR study.

چکیده اصلی

OBJECTIVE: To characterize age- and sex-stratified prevalence patterns of obstructive sleep apnea and co-morbid conditions corresponding to [Formula: see text] components using a large, population-based electronic health record dataset. STUDY DESIGN: The study cohort included 556,474 unique de-identified OSA patients (ICD-9 code 327.23), mined from HIPAA-compliant Cerner [Formula: see text] database (1999-2016). The patient records were mined using Structured Query Language (SQL), stratified by age, gender, and stroke risk comorbidities per [Formula: see text], to conduct a population-based cross-sectional epidemiological study. METHODS: Clinical and epidemiological research informatics methodologies are applied to characterize OSA prevalence patterns across age (5-year intervals), gender, and stroke risk comorbidities per [Formula: see text] criteria. Body-level organ system involvement was examined according to the Major Diagnostic Category (MDC) classification. RESULTS: Age-stratified cross-sectional analyses showed that prevalence rates for OSA (m: 10.43%, f: 9.28%), hypertension (m: 7.37%, f: 7.11%), along with clinical encounters, peaked at age 55 for both genders, whereas the highest prevalence of cardiovascular comorbidities was observed in older age groups (ages 65-70). Hypertension was most prevalent (57.83%), followed by diabetes (34.7%), congestive heart failure (17.7%), atrial fibrillation (13.31%), vascular disease (12.3%), and prior stroke/TIA (4.78%). MDC analysis revealed that prevalence is pronounced in ENT, cardiovascular, and musculoskeletal body systems, consistent with the pathophysiology of chronic intermittent hypoxia in OSA patients. These patterns reflect population-level age-specific prevalence differences rather than longitudinal disease progression. CONCLUSION: This large cross-sectional study (556,474 patients) provides detailed age- and sex-specific prevalence estimates of OSA-associated stroke-risk comorbidities. While causal or temporal inferences cannot be drawn, the findings highlight population-level prevalence patterns that may inform hypothesis-driven longitudinal studies and future evaluation of stroke-risk models.

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