2026 年第 5 期 第 21 卷

单核细胞与高密度脂蛋白胆固醇比值与冠心病合并阻塞性睡眠呼吸暂停患者主要不良心血管事件风险的关系及预测模型构建

Relationship between monocyte to high-density lipoprotein cholesterol ratio and risk of major adverse cardiovascular events in patients with coronary atherosclerotic heart disease complicated by obstructive sleep apnea and construction of a predictive model

作者：赵丽凤1董旭1谭秀利1张立新1张喜维2王艳玲3葛长江1

英文作者：Zhao Lifeng1 Dong Xu1 Tan Xiuli1 Zhang Lixin1 Zhang Xiwei2 Wang Yanling3 Ge Changjiang1

单位：1首都医科大学附属北京安贞医院心内科北京市心肺血管疾病研究所，北京100029；2首都医科大学附属北京安贞医院护理部北京市心肺血管疾病研究所，北京100029；3首都医科大学护理学院，北京100069

英文单位：1Department of Cardiology Beijing Anzhen Hospital Capital Medical University Beijing Institute of Heart Lung and Blood Vessel Diseases Beijing 100029 China; 2Department of Nursing Beijing Anzhen Hospital Capital Medical University Beijing Institute of Heart Lung and Blood Vessel Diseases Beijing 100029 China; 3School of Nursing Capital Medical University Beijing 100069 China

关键词：冠心病（冠状动脉粥样硬化性心脏病）；阻塞性睡眠呼吸暂停；单核细胞与高密度脂蛋白胆固醇比值；主要不良心血管事件；预测模型

英文关键词：Coronaryatheroscleroticheartdisease;Obstructivesleepapnea;Monocytetohigh-densitylipoproteincholesterolratio;Majoradversecardiovascularevents;Predictionmodel

• 摘要：

• 目的 基于单核细胞与高密度脂蛋白胆固醇比值（MHR）分析冠心病（冠状动脉粥样硬化性心脏病，CHD）合并阻塞性睡眠呼吸暂停（OSA）患者发生主要不良心血管事件（MACE）风险的影响因素，并构建风险预测模型。方法 选取2021年9月至2024年9月在首都医科大学附属北京安贞医院诊治的289例CHD合并OSA患者，按照有无发生MACE分为MACE组（61例）和非MACE组（228例），采用二元Logistic回归方法分析CHD合并OSA患者发生MACE的危险因素，并根据二元Logistic回归结 构建预测模型。结果 经二元Logistic回归分析，吸烟史、睡眠呼吸暂停低通气指数≥15次/h、高敏C反应蛋白≥0.5 mg/L、高N末端B型脑钠肽前体、MHR是CHD合并OSA患者发生MACE的危险因素（均P＜0.05），高左心室射血分数是CHD合并OSA患者发生MACE的保护因素（P＜0.05）。使用上述因素构建模型，Hosmer-Lemeshow拟合度检验显示，χ2=6.223，P=0.622，Logistic回归模型预测CHD合并OSA患者发生MACE的曲线下面积（AUC）为0.948，敏感度、特异度分别为89.0%、100.0%，实际应用准确度为90.7%；验证组的AUC为0.960，敏感度、特异度分别为74.5%、100.0%。结论 MHR是CHD合并OSA患者发生MACE的危险因素，基于MHR等危险因素构建的风险预测模型具有较高的预测价值。

• Objective To analyze the influencing factors of major adverse cardiovascular events (MACE) in patients with coronary atherosclerotic heart disease (CHD) complicated by obstructive sleep apnea (OSA) based on monocyte to high-density lipoprotein cholesterol ratio (MHR), and to construct a risk prediction model. Methods A total of 289 patients with CHD complicated by OSA treated in Beijing Anzhen Hospital, Capital Medical University from September 2021 to September 2024 were enrolled and divided into MACE group (61 cases) and non-MACE group (228 cases) according to the occurrence of MACE. Binary Logistic regression was used to analyze the risk factors of MACE in patients with CHD complicated by OSA, and a prediction model was constructed based on the results. Results Binary Logistic regression analysis showed that smoking history, apnea-hypopnea index≥15 events/h, high-sensitivity C-reactive protein≥0.5 mg/L, N-terminal pro-B-type natriuretic peptide and MHR were risk factors for MACE in patients with CHD complicated by OSA (all P<0.05), while high left ventricular ejection fraction was a protective factor (P<0.05). The model was constructed using the above factors. Hosmer-Lemeshow goodness-of-fit test showed χ2=6.223, P=0.622. The area under the curve (AUC) of the Logistic regression model for predicting MACE was 0.948, with sensitivity of 89.0%, specificity of 100.0%, and actual accuracy of 90.7%. The AUC of the validation group was 0.960, with sensitivity of 74.5% and specificity of 100.0%. Conclusion MHR is a risk factor for MACE in patients with CHD complicated by OSA. The risk prediction model constructed based on MHR and other risk factors has high predictive value.