Hua Ting1,2,3, Cher-Ming Liou3,4, Tung-Sheng Shih5,6, Chih-Huan Wang2,7, Shu-Yun Chang2,3, Ai-Hui Chung2, Jia-Fei Lee2, Lee Wang8, Ren-Jing Huang2,9, Shin-Da Lee10,11,12. 1. Department of Physical Medicine and Rehabilitation, Chung-Shan Medical University Hospital, Chung-Shan Medical University, Taichung, Taiwan. 2. Center of Sleep Medicine, Chung-Shan Medical University Hospital, Chung-Shan Medical University, Taichung, Taiwan. 3. Institute of Medicine, Chung-Shan Medical University, Taichung, Taiwan. 4. Department of Anesthesiology, Chung-Shan Medical University Hospital, Taichung, Taiwan. 5. Institute of Occupational Safety and Health Council of Labor Affairs, Executive Yuan, Taipei, Taiwan. 6. Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan. 7. Department of Psychology, National Chengchi University, Taipei, Taiwan. 8. Department of Public Health, Chung-Shan Medical University, Taichung, Taiwan. 9. Department of Medical Image and Radiological Sciences, Chung-Shan Medical University, Taichung, Taiwan. 10. Department of Physical Therapy and Graduate Institute of Rehabilitation Science, China Medical University, 91 Hsueh-Shih Road, Taichung, 40202, Taiwan. shinda@mail.cmu.edu.tw. 11. Department of Healthcare Administration, Asia University, Taichung, Taiwan. shinda@mail.cmu.edu.tw. 12. School of Rehabilitation Medicine, Shanghai University of TCM, Shanghai, China. shinda@mail.cmu.edu.tw.
Abstract
BACKGROUND: Both proteinuria and obstructive sleep apnea (OSA) are associated with cardiovascular events and consequent mortality. To examine whether age, OSA, diabetes, and obesity are potential predictors of proteinuria, a data-driven analysis was performed to delineate a potential categorical classification algorithm. METHODS: In this cross-sectional community-based cohort study, demographic data, blood pressure, serum biochemical analyses, proteinuria via single dipstick urinalysis, and overnight polysomnographies were measured in 300 males with sedentary work styles. RESULTS: Sixty-one (20.3 %) of all these participants had proteinuria. Logistic regression analysis showed that glycated hemoglobin (HbA1c), duration of arterial oxygen saturation <90 %, age, and log high-sensitivity C-reactive protein, but not apnea-hypopnea index (AHI), were responsible for 16.7 % of the variance of proteinuria's presence. A decision tree analysis showed that subjects over 49 years old had a higher risk for proteinuria than those subjects of 49 years old, or less. In the over 49-year-old group, subjects with an AHI >21 events/h had a higher risk for proteinuria; whereas in the 49-year-old and less group, subjects with HbA1c >7 %, or with HbA1c ≤7, and body mass index (BMI) >27.4 kg/m(2) had a higher risk for proteinuria than their counterparts. CONCLUSIONS: AHI was the major determinant responsible for the presence of proteinuria in late mid-aged male workers, while HbA1c and BMI were found in the junior subgroup. By algorithmic analysis, this study provides a comprehensive hierarchical model for better understanding of the correlates of proteinuria and sleep apnea.
BACKGROUND: Both proteinuria and obstructive sleep apnea (OSA) are associated with cardiovascular events and consequent mortality. To examine whether age, OSA, diabetes, and obesity are potential predictors of proteinuria, a data-driven analysis was performed to delineate a potential categorical classification algorithm. METHODS: In this cross-sectional community-based cohort study, demographic data, blood pressure, serum biochemical analyses, proteinuria via single dipstick urinalysis, and overnight polysomnographies were measured in 300 males with sedentary work styles. RESULTS: Sixty-one (20.3 %) of all these participants had proteinuria. Logistic regression analysis showed that glycated hemoglobin (HbA1c), duration of arterial oxygen saturation <90 %, age, and log high-sensitivity C-reactive protein, but not apnea-hypopnea index (AHI), were responsible for 16.7 % of the variance of proteinuria's presence. A decision tree analysis showed that subjects over 49 years old had a higher risk for proteinuria than those subjects of 49 years old, or less. In the over 49-year-old group, subjects with an AHI >21 events/h had a higher risk for proteinuria; whereas in the 49-year-old and less group, subjects with HbA1c >7 %, or with HbA1c ≤7, and body mass index (BMI) >27.4 kg/m(2) had a higher risk for proteinuria than their counterparts. CONCLUSIONS: AHI was the major determinant responsible for the presence of proteinuria in late mid-aged male workers, while HbA1c and BMI were found in the junior subgroup. By algorithmic analysis, this study provides a comprehensive hierarchical model for better understanding of the correlates of proteinuria and sleep apnea.
Authors: Michael D Faulx; Amy Storfer-Isser; H Lester Kirchner; Nancy S Jenny; Russell P Tracy; Susan Redline Journal: Sleep Date: 2007-07 Impact factor: 5.849