摘要
目的基于四变量评分和传统危险因素构建阻塞性睡眠呼吸暂停低通气综合征(OSAHS)合并冠心病(CHD)的列线图预测模型。方法招募2020年2月至2024年3月在新疆医科大学第一附属医院住院的OSAHS患者1224例。以7∶3的比例随机分为训练集(857例)和验证集(367例)。根据训练集患者CHD合并情况分为OSAHS+CHD组(277例)和OSAHS+非CHD组(580例)。通过LASSO回归筛选自变量,采用多因素logistic回归分析OSAHS合并CHD的影响因素,建立列线图预测模型。分别通过受试者工作特征(ROC)曲线、校准曲线、Hosmer-Lemeshow检验和决策曲线分析(DCA)评估模型的区分度、校准度、拟合度和临床有效性。结果LASSO回归分析筛选出8个自变量,分别为男性、年龄≥45岁、高血压史、体质量指数(BMI)≥25 kg/m2、高密度脂蛋白胆固醇(HDL-C)、呼吸暂停低通气指数(AHI)≥30次/h、平均血氧饱和度(MSaO2)≥90%、四变量评分≥10.5分。多因素logistic回归分析结果显示,男性、年龄≥45岁、高血压史、BMI≥25 kg/m2、AHI≥30次/h、四变量评分≥10.5分是OSAHS合并CHD的独立危险因素(P<0.05),较高的HDL-C水平是OSAHS合并CHD的独立保护因素(P<0.05)。基于7个影响因素构建OSAHS合并CHD的列线图预测模型。ROC曲线显示,模型在训练集的AUC(95%CI)为0.778(0.747~0.810),灵敏度为71.80%,特异度为71.20%;模型在验证集的AUC(95%CI)为0.797(0.752~0.842),灵敏度为78.80%,特异度为70.80%,具有较高的区分度。校准曲线显示,模型预测OSAHS合并CHD风险的预测概率与实际概率基本一致,具有良好的校准度。Hosmer-Lemeshow检验结果(训练集:χ^(2)=8.100,P=0.524;验证集:χ^(2)=16.880,P=0.051)证明模型具有较好的拟合度。决策曲线验证了模型的临床有效性。结论男性、年龄≥45岁、高血压史、BMI≥25 kg/m2、AHI≥30次/h、四变量评分≥10.5分是OSAHS合并CHD的独立危险因素,较高的HDL-C水平是OSAHS合并CHD的独立保护因素,基于以上7个影响因素构建的OSAHS合并CHD列线图预测模型具有较好的预测价值。
Objective To construct a Nomogram prediction model for obstructive sleep apnea hypopnea syndrome(OSAHS)complicated with coronary heart disease(CHD)based on four-variable screening tool and conventional risk factors.Methods A total of 1224 OSAHS patients who were admitted to the First Teaching Hospital of Xinjiang Medical University from February 2020 to March 2024 were enrolled.The patients were randomly divided into a training set(857 cases)and a validation set(367 cases)in a ratio of 7∶3.According to the complicating CHD of the patients in the training set,these patients were divided into OSAHS+CHD group(277 cases)and OSAHS+non-CHD group(580 cases).The independent variables were screened by LASSO regression,and the influencing factors of OSAHS complicated with CHD were analyzed by using multivariate logistic regression,and a Nomogram prediction model was established.Receiver operating characteristic(ROC)curve,calibration curve,Hosmer-Lemeshow test,and decision curve analysis(DCA)were used to evaluate the differentiation degree,calibration degree,fitting degree and clinical effectiveness of the model,respectively.Results Eight independent variables were screened out by using LASSO regression analysis,which were male,age≥45 years,a history of hypertension,body mass index(BMI)≥25 kg/m 2,high-density lipoprotein cholesterol(HDL-C),apnea-hypopnea index(AHI)≥30 times/hour,mean arterial oxygen saturation(MSaO 2)≥90%,and four-variable screening tool scores≥10.5 points.The results of multivariate logistic regression analysis showed that male,age≥45 years,a history of hypertension,BMI≥25 kg/m 2,AHI≥30 times/hour and four-variable screening tool scores≥10.5 points were independent risk factors for OSAHS complicated with CHD(P<0.05).Higher HDL-C level was an independent protective factor for OSAHS complicated with CHD(P<0.05).A Nomogram prediction model for OSAHS complicated with CHD was constructed based on the 7 influencing factors.The ROC curve showed that area under the curve(AUC)(95%CI)of the model in the training set was 0.778(0.747-0.810),with a sensitivity of 71.80%,and a specificity of 71.20%,and AUC(95%CI)of the model in the validation set was 0.797(0.752-0.842),with a sensitivity of 78.80%,and a specificity of 70.80%,showing a high differentiation degree.The calibration curve showed that the prediction probability risk of OSAHS complicated with CHD predicted by the model was basically consistent with the actual probability,with a good calibration degree.The results of Hosmer-Lemeshow test(training set:χ^(2)=8.100,P=0.524;validation set:χ^(2)=16.880,P=0.051)proved that the model had a good fitting degree.The decision curve verified the clinical effectiveness of the model.Conclusion Male,age≥45 years,a history of hypertension,BMI≥25 kg/m 2,AHI≥30 times/hour,and four-variable screening tool scores≥10.5 points are independent risk factors for OSAHS complicated with CHD.Higher HDL-C level was an independent protective factor for OSAHS complicated with CHD.The Nomogram prediction model constructed based on the 7 influencing factors has better predictive value for OSAHS complicated with CHD.
作者
姚艳丽
邱璇
陈玉岚
古丽米热·艾麦提
阿依古再丽·麦麦提敏
梁泽宇
YAO Yanli;QIU Xuan;CHEN Yulan;Gulimire Aimaiti;Ayiguzaili Maimaitimin;LIANG Zeyu(Department of Hypertension,Cardiovascular Disease Center,the First Teaching Hospital of Xinjiang Medical University,Urumqi 830011,China)
出处
《中国临床新医学》
2025年第2期176-183,共8页
CHINESE JOURNAL OF NEW CLINICAL MEDICINE
基金
国家自然科学基金资助项目(编号:82060058)。
关键词
四变量评分
危险因素
阻塞性睡眠呼吸暂停低通气综合征
冠心病
列线图预测模型
Four-variable screening tool
Risk factors
Obstructive sleep apnea hypopnea syndrome(OSAHS)
Coronary heart disease(CHD)
Nomogram model
作者简介
第一作者:姚艳丽,在读硕士研究生,研究方向:高血压及其相关研究。E-mail:y821023966@163.com;通信作者:陈玉岚,医学博士,主任医师,教授,博士、硕士研究生导师,研究方向:高血压及其相关研究。E-mail:sheliachen@sina.com。
