Analysis of influencing factors and construction of a risk prediction integral assessment system for hypertension associated with obstructive sleep apnea syndrome in elderly males
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(1. Graduate School, Yanchi 751500, Ningxia Hui Autonomous Region, China ;2. National Clinical Research Center for Geriatric Diseases, Yanchi 751500, Ningxia Hui Autonomous Region, China;5. Department of Cardiology, Second Medical Center, Yanchi 751500, Ningxia Hui Autonomous Region, China;6. Department of Respiratory and Critical Care Medicine, Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China;3. Department of Internal Medicine, Ningxia Yanchi County Traditional Chinese Medicine Hospital, Yanchi 751500, Ningxia Hui Autonomous Region, China;4. School of Nursing and Health, Medical College, Yan′an University, Yan′an 716000, Shaanxi Province, China)

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R544

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    Abstract:

    Objective To explore the influencing factors of hypertension associated with obstructive sleep apnea syndrome (OSAS) in the elderly males and to construct an integral assessment system to predict the risk of hypertension in the OSAS population. Methods We selected 798 elderly males OSAS patients as the research subjects from six tertiary hospitals (Beijing, Gansu Province, Shandong Province, etc.) from January 2015 to October 2017. According to the presence of hypertension, they were divided into hypertension group (n=538) and non-hypertension group (n=260). Their general information and biochemical indicators were collected. SPSS 25.0 was used for data analysis. Spearman correlation analysis was used to evaluate the correlation between various indicators and hypertension grading, and logistic regression analysis to analyze the factors affecting hypertension. A risk prediction model was constructed for hypertension in elderly male OSAS population. Receiver operating characteristic (ROC) curve was used to evaluate the rick prediction model.Results The body mass index (BMI), oxygen desaturation index (ODI), time with pulse oxygen saturation (SpO2)<90%, proportion of the cumulative sleep time with SpO2<90% in total sleep time (T90), creatinine, fasting blood glucose, proportion of patients with a drinking history, and prevalence of diabetes mellitus, coronary heart disease, carotid atherosclerosis and hyperlipidemia were significantly higher in the hypertensive patients than in non-hypertensive patients, and the differences were statistically significant (P<0.05). Correlation analysis showed that the age, BMI, apnea hypopnea index (AHI), ODI, time of SpO2<90%, T90, low-density lipoprotein cholesterol, fasting blood glucose and creatinine levels were significantly positively correlated with hypertension grading (r=0.107,0.160,0.072,0.079,0.089,0.087,0.080,0.112,0.154; P<0.05 for all), and that the lowest oxygen saturation and high-density lipoprotein cholesterol were negatively correlated with hypertension grading (r=-0.082, -0.087; P<0.05 for both). Multivariate logistic regression analysis showed that BMI (OR=1.098,95%CI 1.053-1.145), fasting blood glucose (OR=1.144,95%CI 1.028-1.274), creatinine (OR=1.008,95%CI 1.002-1.014) and hyperlipidemia (OR=1.543,95%CI 1.070-2.224) were risk factors, and the treatment with continuous positive airway pressure (CPAP) (OR=0.612,95%CI 0.387-0.967) was a protective factor of hypertension in elderly male OSAS patients. The calculation formula for the risk prediction model was logit (P)=-3.263+0.093×BMI+0.135×fasting blood glucose+0.008×creatinine+0.434× hyperlipidemia-0.491×CPAP, with an area under ROC curve of 0.654 (95%CI 0.614-0.694), a sensitivity of 0.701 and a specificity of 0.542. Theoretically, the integral range of the individual patients to be evaluated was from -2 to 11 after values were assigned to all the variables in the model. Using the formula, the corresponding probability of hypertension was P=1/[1+exp(0.2277-0.217S)], where S representod the corresponding integral. Conclusion The BMI, fasting blood glucose, creatinine, hyperlipidemia, and CPAP are influencing factors of hypertension in the elderly male OSAS patients. The risk prediction model established in this study has some ability to detect hypertension in the elderly male OSAS patients, and the designed integral assessment system can predict the risk of hypertension simply and intuitively.

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History
  • Received:December 13,2022
  • Revised:
  • Adopted:
  • Online: August 22,2023
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