Sikawat Thanaviratananich1, Hao Cheng2, Naricha Chirakalwasan3,4, Sirimon Reutrakul5,6. 1. Department of Neurology, Carver College of Medicine, University of Iowa, 200 Hawkins Dr, Iowa City, IA, 52242, USA. Sikawat-thanaviratananich@uiowa.edu. 2. Miami VA Healthcare System, Miami, FL, USA. 3. Division of Pulmonary and Critical Care Medicine, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. 4. Excellence Center for Sleep Disorders, King Chulalongkorn Memorial Hospital/Thai Red Cross Society, Bangkok, Thailand. 5. Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Illinois At Chicago, Chicago, IL, USA. 6. Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Abstract
PURPOSE: To evaluate the association between a novel integrated event-based and hypoxemia-based parameter of polysomnography (PSG), hypoxemic load or HL100, and fasting blood glucose (FBG) and hemoglobin A1c (HbA1c) levels. METHODS: Adult patients, who underwent an in-lab PSG at the University of Iowa Hospitals and Clinics with FBG or HbA1c levels, were included. Event-based parameter and hypoxemia-based parameter data were derived. HL100, defined as the integrated area of desaturation between the 100% oxygen saturation and the measured saturation levels during sleep divided by the total sleep time, was calculated by Python software. Demographic data and glycemic parameters within 1 year prior to PSG (FBG and HbA1c) were retrieved from chart review. Spearman correlation analysis and stepwise backward regression analysis were performed to determine independent predictors of FBG and HbA1c levels. RESULTS: Of the 467 patients who underwent an in-lab PSG, 218 had FBG levels, 84 had HbA1c levels, and 118 had both values. All event-based and hypoxemia-based parameters, including HL100, were significantly correlated to FBG and HbA1c levels. Stepwise backward regression analyses, adjusted for age, sex, body mass index, and diabetes status, revealed that log HL100 was significantly related to FBG (B = 23.9, p = 0.010), but none of log event-based or hypoxemia-based parameters were found to be significantly related HbA1c levels. CONCLUSIONS: HL100 was shown to be an independent predictor of FBG in this cohort, implying that any degree of desaturation below 100% could adversely affect glucose metabolism. HL100 may be useful for interpretation of sleep studies, risk stratification, and patient management purposes in the future.
PURPOSE: To evaluate the association between a novel integrated event-based and hypoxemia-based parameter of polysomnography (PSG), hypoxemic load or HL100, and fasting blood glucose (FBG) and hemoglobin A1c (HbA1c) levels. METHODS: Adult patients, who underwent an in-lab PSG at the University of Iowa Hospitals and Clinics with FBG or HbA1c levels, were included. Event-based parameter and hypoxemia-based parameter data were derived. HL100, defined as the integrated area of desaturation between the 100% oxygen saturation and the measured saturation levels during sleep divided by the total sleep time, was calculated by Python software. Demographic data and glycemic parameters within 1 year prior to PSG (FBG and HbA1c) were retrieved from chart review. Spearman correlation analysis and stepwise backward regression analysis were performed to determine independent predictors of FBG and HbA1c levels. RESULTS: Of the 467 patients who underwent an in-lab PSG, 218 had FBG levels, 84 had HbA1c levels, and 118 had both values. All event-based and hypoxemia-based parameters, including HL100, were significantly correlated to FBG and HbA1c levels. Stepwise backward regression analyses, adjusted for age, sex, body mass index, and diabetes status, revealed that log HL100 was significantly related to FBG (B = 23.9, p = 0.010), but none of log event-based or hypoxemia-based parameters were found to be significantly related HbA1c levels. CONCLUSIONS: HL100 was shown to be an independent predictor of FBG in this cohort, implying that any degree of desaturation below 100% could adversely affect glucose metabolism. HL100 may be useful for interpretation of sleep studies, risk stratification, and patient management purposes in the future.
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