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find Keyword "Chronic Intermittent Hypoxia" 2 results
  • Research Progress on the Chronic Intermittent Hypoxia and Abnormal Sympathetic Activation

    睡眠过程中反复出现呼吸暂停造成的间歇低氧是阻塞性睡眠呼吸暂停低通气综合征( OSAHS) 的主要病理生理学特点, 它能够导致自主神经, 特别是交感神经兴奋性异常增高[1] , 后者可能是OSAHS合并心血管疾病包括高血压、充血性心力衰竭、心肌梗死以及心律失常的主要危险因素之一[2,3] 。现将慢性间歇低氧( chronic intermittent hypoxia,CIH) 所致交感神经异常兴奋的相关研究作一综述。

    Release date:2016-09-14 11:25 Export PDF Favorites Scan
  • Study on the Risk Factors for Renal Impairment in Obstructive Sleep Apnea

    ObjectiveTo investigate the renal impairment and the risk factors of renal impairment in patients with OSA. MethodsData from patients who underwent polysomnography (PSG) in our department from July 2022 to January 2023 were collected, totaling 178 cases. Based on the results of the polysomnography, the patients were divided into an OSA group (145 cases) and a non-OSA group (33 cases). According to the severity of the condition, the OSA group was further divided into mild OSA (21 cases), moderate OSA (28 cases), and severe OSA (96 cases). The Pearson correlation analysis was further conducted to analyze the relationships between serum urea nitrogen (BUN), serum cystatin C (Cys-C) concentrations, and estimated Glomerular Filtration Rate (eGFR) with various risk factors that may influence renal impairment. Moreover, multiple linear regression analysis was used to identify the risk factors affecting BUN, Cys-C, and eGFR. ResultsWhen comparing the two groups, there were statistically significant differences in age, weight, BMI, neck circumference, waist circumference, eGFR、Cys-C、BUN, LSaO2, CT90% (all P<0.05). Univariate analysis of variance was used to compare differences in BUN, Serum creatinine (SCr), Cys-C, and eGFR among patients with mild, moderate, and severe OSA, indicating that differences in eGFR and Cys-C among OSA patients of varying severities were statistically significant. Further analysis with Pearson correlation was conducted to explore the associations between eGFR, BUN, and Cys-C with potential risk factors that may affect renal function. Subsequently, multiple linear regression was utilized, taking these three indices as dependent variables to evaluate risk factors potentially influencing renal dysfunction. The results demonstrated that eGFR was negatively correlated with age, BMI, and CT90% (β=−0.95, P<0.001; β=−1.36, P=0.01; β=−32.64, P<0.001); BUN was positively correlated with CT90% (β=0.22, P=0.01); Cys-C was positively correlated with CT90% (β=0.58, P<0.001. Conclusion Chronic intermittent hypoxia, age, and obesity are risk factors for renal dysfunction in patients with OSA.

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