Guan Jian, Yi Hongliang, Zou Jianyin, Meng Lili, Tang Xulan, Zhu Huaming, Yu Dongzhen, Zhou Huiqun, Su Kaiming, Yang Mingpo, Chen Haoyan, Shi Yongyong, Wang Yue, Wang Jian, Yin Shankai
Department of Otolaryngology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China Department of Otolaryngology, Therapy Center for Obstructive Sleep Apnea, Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai China.
Department of Otolaryngology, Therapy Center for Obstructive Sleep Apnea, Otolaryngology Institute of Shanghai Jiao Tong University, Shanghai China.
Thorax. 2016 Apr;71(4):347-55. doi: 10.1136/thoraxjnl-2015-207403. Epub 2016 Feb 16.
Dyslipidaemia is an intermediary exacerbation factor for various diseases but the impact of obstructive sleep apnoea (OSA) on dyslipidaemia remains unclear.
A total of 3582 subjects with suspected OSA consecutively admitted to our hospital sleep centre were screened and 2983 (2422 with OSA) were included in the Shanghai Sleep Health Study. OSA severity was quantified using the apnoea-hypopnea index (AHI), the oxygen desaturation index and the arousal index. Biochemical indicators and anthropometric data were also collected. The relationship between OSA severity and the risk of dyslipidaemia was evaluated via ordinal logistic regression, restricted cubic spline (RCS) analysis and multivariate linear regressions.
The RCS mapped a nonlinear dose-effect relationship between the risk of dyslipidaemia and OSA severity, and yielded knots of the AHI (9.4, 28.2, 54.4 and 80.2). After integrating the clinical definition and RCS-selected knots, all subjects were regrouped into four AHI severity stages. Following segmented multivariate linear modelling of each stage, distinguishable sets of OSA risk factors were quantified: low-density lipoprotein cholesterol (LDL-C), apolipoprotein E and high-density lipoprotein cholesterol (HDL-C); body mass index and/or waist to hip ratio; and HDL-C, LDL-C and triglycerides were specifically associated with stage I, stages II and III, and stages II-IV with different OSA indices.
Our study revealed the multistage and non-monotonic relationships between OSA and dyslipidaemia and quantified the relationships between OSA severity indexes and distinct risk factors for specific OSA severity stages. Our study suggests that a new interpretive and predictive strategy for dynamic assessment of the risk progression over the clinical course of OSA should be adopted.
血脂异常是多种疾病的中间加重因素,但阻塞性睡眠呼吸暂停(OSA)对血脂异常的影响仍不明确。
对我院睡眠中心连续收治的3582例疑似OSA患者进行筛查,2983例(其中2422例患有OSA)纳入上海睡眠健康研究。采用呼吸暂停低通气指数(AHI)、氧饱和度下降指数和觉醒指数对OSA严重程度进行量化。同时收集生化指标和人体测量数据。通过有序逻辑回归、受限立方样条(RCS)分析和多元线性回归评估OSA严重程度与血脂异常风险之间的关系。
RCS描绘了血脂异常风险与OSA严重程度之间的非线性剂量效应关系,并得出AHI的节点(9.4、28.2、54.4和80.2)。结合临床定义和RCS选择的节点后,所有受试者被重新分组为四个AHI严重程度阶段。对每个阶段进行分段多元线性建模后,量化了不同的OSA风险因素集:低密度脂蛋白胆固醇(LDL-C)、载脂蛋白E和高密度脂蛋白胆固醇(HDL-C);体重指数和/或腰臀比;HDL-C、LDL-C和甘油三酯分别与I期、II期和III期以及II-IV期的不同OSA指标相关。
我们的研究揭示了OSA与血脂异常之间的多阶段和非单调关系,并量化了OSA严重程度指标与特定OSA严重程度阶段不同风险因素之间的关系。我们的研究表明,应采用一种新的解释性和预测性策略,对OSA临床过程中的风险进展进行动态评估。