Obstructive sleep apnea (OSA) has a high prevalence, and it has been shown to be an independent risk factor for various diseases. Therefore, it is important to strengthen screening for population at highrisk of OSA. OSA patients are prone to combine with lipid metabolism disorders, but it remains unclear whether the atherogenic index of plasma (AIP), visceral adiposity index (VAI), lipid accumulation product (LAP), cardiometabolic index (CMI), and Chinese visceral adiposity index (CVAI), which are used asmetabolic indexes, can be used to predict OSA.

To analyze the correlation between metabolic indexes and OSA, and evaluate the predictive efficacy of each metabolic index through a case-control study.

A total of 2 968 inpatients with suspected OSA and aged ≥18 years who completed polysomnography (PSG) in the First Affiliated Hospital of Xinjiang Medical University from March 2017 to June 2022 were selected, with 2 850 patients finally included based on the inclusion and exclusion criteria and divided into the OSA group 〔apnea-hypopnea index (AHI) ≥5 times/h, n=2 193〕 and non-OSA group (AHI<5 times/h, n=657) according to the AHI. The clinical data and laboratory test results of these patients were collected through the electronic medical record system. Univariate and multivariate Logistic regression analyses were used to investigate the correlation of AIP, VAI, LAP, CMI, and CVAI with OSA. The receiver operating characteristic (ROC) curve was plotted to analyze the efficacy of metabolic indexes in predicting OSA. A gender-stratified analysis was performed to explore the relationship between metabolic indexes and OSA in different populations.

Age, gender (male proportion), neck circumference, height, total cholesterol, triacylglycerol, AHI, AIP, VAI, LAP, CMI, and CVAI were significantly higher in the OSA group than the non-OSA group, high-density lipoprotein cholesterol (HDL-C), mean oxygen saturation and minimum oxygen saturation were significantly lower than the non-OSA group (P<0.05). After dividing the five metabolic indexes into quartiles (Q1 to Q4), them ultivariate Logistic regression analysis showed that AIP〔OR=2.241, 95%CI (1.689, 2.972), P<0.001〕, VAI〔OR=2.517, 95%CI (1.919, 3.301), P<0.001〕, LAP〔OR=2.313, 95%CI (1.761, 3.038), P<0.001〕, CMI〔OR=2.732, 95%CI (2.054, 3.633), P<0.001〕, and CVAI〔OR=6.060, 95%CI (4.411, 8.324), P<0.001〕 were associated with the risk of OSA (P<0.05). Further analysis stratified by gender showed that in female patients, AIP, VAI, LAP, CMI, and CVAI were associated with the risk of OSA (P<0.05) ; in male patients, CMI, LAP, and VAI were not associated with OSA (P>0.05), but AIP and CVAI were associated with OSA (P<0.05). The areas under the ROC curves (AUCs) of AIP, VAI, LAP, CMI, and CVAI for predicting OSA were〔0.593, 95%CI (0.568, 0.618) 〕〔0.607, 95%CI (0.583, 0.632) 〕〔0.594, 95%CI (0.569, 0.619) 〕〔0.616, 95%CI (0.591, 0.640) 〕, and〔0.728, 95%CI (0.706, 0.751) 〕, respectively.Further analysis stratified by gender for the clarification of the predictive efficacy of five metabolic indexes for OSA showed that the AUCs of the five metabolic indices for predicting OSA were higher in the female population than the total population, and the AUCs of the five metabolic indexes were lower in the male population than the total population. The AUC of CVAI was higher than other indexes in the total population, male and female populations (AUC=0.728 for the overall population, AUC=0.764 for the female population, AUC=0.681 for the male population) .

As the quartiles of AIP, VAI, LAP, CMI, and CVAI increase, the risk of OSA rises. CVAI has a better predictive efficacy for OSA than other indexes, therefore, CVAI may be used as a predictor for screening of population at high risk of OSA.

阻塞性睡眠呼吸暂停（OSA）的患病率很高，目前OSA已被证实是多种疾病的独立危险因素，因此要加强对OSA高危人群的筛查。OSA患者易合并脂代谢异常，而作为能评估代谢异常的指标——血浆致动脉粥样硬化指数（AIP）、内脏肥胖指数（VAI）、脂类积聚产物（LAP）、心脏代谢指数（CMI）以及中国人内脏肥胖指数（CVAI）是否能用于预测OSA，目前尚不清楚。

通过病例对照研究分析代谢指数与OSA的相关性，并评估各代谢指数对OSA的预测效能。

选取2017年3月—2022年6月在新疆医科大学第一附属医院已完善多导睡眠监测（PSG）的疑似OSA且年龄≥18岁的住院患者共2 968例。根据纳入、排除标准最终纳入2 850例患者，根据呼吸暂停低通气指数（AHI）将患者分为OSA组（AHI≥5次/h）2 193例和非OSA组（AHI<5次/h）657例。通过电子病历系统收集患者的临床资料和实验室检查指标。采用单因素及多因素Logistic回归分析探究AIP、VAI、LAP、CMI、CVAI与OSA的相关性。采用受试者工作特征（ROC）曲线分析代谢指数预测患者发生OSA的效能。对人群进行性别分层分析以探究代谢指数在不同人群中与OSA的关系。

OSA组患者年龄、性别（男性占比）、颈围、身高、总胆固醇、三酰甘油、AHI、AIP、VAI、LAP、CMI、CVAI均高于非OSA组，HDL-C、平均血氧饱和度、最低血氧饱和度低于非OSA组（P<0.05）。将5个代谢指数按四分位数进行分组（Q1~Q4），多因素Logistic回归分析显示，AIP〔OR=2.241，95%CI（1.689，2.972），P<0.001〕、VAI〔OR=2.517，95%CI（1.919，3.301），P<0.001〕、LAP〔OR=2.313，95%CI（1.761，3.038），P<0.001〕、CMI〔OR=2.732，95%CI（2.054，3.633），P<0.001〕、CVAI〔OR=6.060，95%CI（4.411，8.324），P<0.001〕与OSA发生风险相关（P<0.05）；进一步将患者按性别进行分层分析结果显示：在女性患者中AIP、VAI、LAP、CMI、CVAI与OSA发生风险相关（P<0.05），男性患者中CMI、LAP、VAI与OSA发生风险无相关性（P>0.05），AIP、CVAI与OSA发生风险相关（P<0.05）。AIP、VAI、LAP、CMI、CVAI预测发生OSA的ROC曲线下面积（AUC）分别为〔0.593，95%CI（0.568，0.618）〕〔0.607，95%CI（0.583，0.632）〕〔0.594，95%CI（0.569，0.619）〕〔0.616，95%CI（0.591，0.640）〕〔0.728，95%CI（0.706，0.751）〕。为明确5个代谢指数预测OSA的效能，进一步将患者按性别进行分层分析：在女性人群中5个代谢指数预测OSA的AUC均较总人群增加，男性人群中5个代谢指数的AUC均低于总人群。无论在总人群还是在男女亚组人群中，CVAI指数的AUC均高于其他指数（总人群AUC=0.728，女性AUC=0.764，男性AUC=0.681）。

随着AIP、VAI、LAP、CMI、CVAI的四分位数分组增高，发生OSA的风险增加。CVAI对OSA的预测效能优于其他指数，因此CVAI或可成为OSA高危人群筛查的预测指标。