Abstract
STUDY OBJECTIVES: We sought to evaluate sleep measures that better predict incident diabetes and prediabetes in a large cohort of veterans. METHODS: This secondary analysis included 650 patients without baseline diabetes from a multisite observational veterans' cohort. Participants underwent obstructive sleep apnea evaluation via laboratory-based polysomnography between 2000 and 2004 with follow-up through 2012. The primary outcomes were prediabetes and diabetes defined by fasting blood glucose, hemoglobin A1c, or use of glucose-lowering medication at study initiation. Exposure variables included respiratory event frequency, arousals, and oxygen desaturation. Cox models adjusted for body mass index, age, race, sex, change in body mass index, and continuous positive airway pressure device utilization. RESULTS: The adjusted analysis revealed that time spent with oxygen saturation less than 90 [hazards ratio (HR) 1.009], confidence interval (CI) 1.001-1.017, P = .02), respiratory arousals (HR 1.009, CI 1.003-1.015, P < 0.01) and total arousals (HR 1.006 CI 1.001-1.011 P = .02) were associated with an increased incidence of diabetes. Increases in mean nocturnal oxygen saturation were associated with decreased incidence of diabetes (HR 0.914 CI 0.857-0.975, P < .01) and prediabetes (HR 0.914 CI 0.857-0.975, P < .01). No significant relationships were demonstrated for apnea-hypopnea index (AHI), measures related to central apnea, Cheyne-Stokes respiration, periodic limb movements, or Epworth Sleepiness Scale score. CONCLUSIONS: There was no significant association of incident prediabetes or diabetes with AHI, the gold standard of sleep apnea severity. This study suggests that hypoxia may be a better predictor of glycemic outcomes than AHI in an obstructive sleep apnea population and may provide clues to the underlying mechanism(s) that link sleep-disordered breathing and its metabolic consequences. CITATION: Wojeck BS, Inzucchi SE, Qin L, Yaggi HK. Polysomnographic predictors of incident diabetes and pre-diabetes: an analysis of the DREAM study. J Clin Sleep Med. 2023;19(4):703-710.