摘要
目的:Charlson共病指数可反映全身共病负担,其在心血管领域已有应用,但在急性心肌梗死(acute myocardial infarction,AMI)合并室性心律失常(ventricular arrhythmias,VA)患者院内死亡预测中的作用尚未明确。本研究旨在评估Charlson共病指数预测AMI合并VA患者院内死亡的价值并构建预测模型,以期早期识别并制订个体化管理策略,改善患者预后。方法:本研究基于重症医学领域的开源数据库MIMIC-IV(Medical Information Mart for Intensive Care IV),纳入符合AMI合并VA诊断标准的ICU患者为研究对象,并根据院内死亡情况进行分组。分析Charlson共病指数及其他临床指标预测AMI合并VA患者院内死亡的效能。采用最小绝对收缩和选择算子(the least absolute shrinkage and selection operator,LASSO)回归筛选预测因子,并纳入多因素Logistic回归模型进行分析。基于多因素Logistic回归结果构建列线图预测模型,绘制受试者操作特征(receiver operating characteristic,ROC)曲线和校准曲线评估模型的预测效能。结果:本研究共纳入AMI合并VA患者1492例,其中发生院内死亡者340例,未发生院内死亡者1152例。发生院内死亡者与未发生院内死亡者在性别分布、生命体征、共病负担、器官功能及实验室指标方面比较,差异均有统计学意义(均P<0.05)。Charlson共病指数预测院内死亡的曲线下面积(area under the curve,AUC)为0.712(95%CI 0.681~0.742),高于白蛋白、国际标准化比值(international normalized ratio,INR)、血红蛋白、体温、血小板等指标的预测效能,差异均有统计学意义(均P<0.001),但与序贯器官衰竭评估(Sequential Organ Failure Assessment,SOFA)预测效能的差异无统计学意义(P>0.05)。LASSO回归筛选出7个关键预测因子,即Charlson共病指数(依据四分位数值分组;T1:Charlson共病指数<6分;T2:Charlson共病指数≥6~<7分;T3:Charlson共病指数≥7~<9分;T4:Charlson共病指数≥9分)、心室颤动、年龄、收缩压、呼吸频率、体温及SOFA评分。多因素Logistic回归分析显示:与Charlson共病指数T1组患者相比,T2组(OR=1.996,95%CI 1.135~3.486,P=0.016)、T3组(OR=3.386,95%CI 2.192~5.302,P<0.001)和T4组(OR=5.679,95%CI 3.711~8.842,P<0.001)患者的院内死亡风险显著增高;年龄(OR=1.056,P<0.001)、呼吸频率(OR=1.069,P<0.001)、SOFA评分(OR=1.223,P<0.001)和心室颤动(OR=2.174,P<0.001)均是院内死亡的危险因素,收缩压(OR=0.984,P<0.001)和体温(OR=0.648,P<0.001)则是院内死亡的保护因素。基于上述预测因子构建列线图预测模型,ROC曲线分析显示该模型的AUC为0.849(95%CI 0.826~0.871),具有较高的区分能力;校准曲线分析显示预测曲线与理想曲线较为接近,平均绝对误差为0.014,具有良好的校准度。结论:Charlson共病指数是AMI合并VA患者院内死亡的独立预测因子,与SOFA评分的预测效能相近。基于Charlson共病指数和其他临床变量构建的列线图预测模型可有效评估AMI合并VA患者的院内死亡风险,为临床决策提供参考。
Objective:The Charlson comorbidity index reflects overall comorbidity burden and has been applied in cardiovascular medicine.However,its role in predicting in-hospital mortality in patients with acute myocardial infarction(AMI)complicated by ventricular arrhythmias(VA)remains unclear.This study aims to evaluate the predictive value of the Charlson comorbidity index in this setting and to construct a nomogram model for early risk identification and individualized management to improve outcomes.Methods:Using the open-access critical care database MIMIC-IV(Medical Information Mart for Intensive Care IV),we identified intensive care unit(ICU)patients diagnosed with AMI complicated by VA.Patients were grouped according to in-hospital survival.The predictive performance of the Charlson comorbidity index and other clinical variables for in-hospital mortality was analyzed.Key predictors were selected using the least absolute shrinkage and selection operator(LASSO)regression,followed by multivariable Logistic regression.A nomogram model was constructed based on the regression results.Model performance was assessed using receiver operating characteristic(ROC)curves and calibration plots.Results:A total of 1492 patients with AMI and VA were included,of whom 340 died and 1152 survived during hospitalization.Significant differences were observed between survivors and non-survivors in sex distribution,vital signs,comorbidity burden,organ function,and laboratory parameters(all P<0.05).The area under the curve(AUC)of the Charlson comorbidity index for predicting in-hospital mortality was 0.712(95%CI 0.681 to 0.742),significantly higher than albumin,international normalized ratio(INR),hemoglobin,body temperature,and platelet count(all P<0.001),but comparable to Sequential Organ Failure Assessment(SOFA)score(P>0.05).LASSO regression identified seven key predictors:the Charlson comorbidity index(quartile groups:T1,<6;T2,≥6−<7;T3,≥7−<9;T4,≥9),ventricular fibrillation,age,systolic blood pressure,respiratory rate,body temperature,and SOFA score.Multivariate Logistic regression showed that compared with T1,mortality risk increased significantly in T2(OR=1.996,95%CI 1.135 to 3.486,P=0.016),T3(OR=3.386,95%CI 2.192 to 5.302,P<0.001),and T4(OR=5.679,95%CI 3.711 to 8.842,P<0.001).Age(OR=1.056,P<0.001),respiratory rate(OR=1.069,P<0.001),SOFA score(OR=1.223,P<0.001),and ventricular fibrillation(OR=2.174,P<0.001)were independent risk factors,while systolic blood pressure(OR=0.984,P<0.001)and body temperature(OR=0.648,P<0.001)were protective factors.The nomogram incorporating these predictors achieved an AUC of 0.849(95%CI 0.826 to 0.871)with high discrimination and good calibration(mean absolute error=0.014).Conclusion:The Charlson comorbidity index is an independent predictor of in-hospital mortality in AMI patients complicated by VA,with performance comparable to the SOFA score.The nomogram model based on the Charlson comorbidity index and additional clinical variables effectively estimates mortality risk and provides a valuable reference for clinical decision-making.
作者
谢楠
刘伟伟
杨鹏翥
姚翔
郭宇轩
苑聪
XIE Nan;LIU Weiwei;YANG Pengzhu;YAO Xiang;GUO Yuxuan;YUAN Cong(Department of Cardiovascular Medicine,Affiliated Changsha Hospital of Xiangya School of Medicine,Central South University,Changsha 410005;Department of Cardiovascular Medicine,Hunan Chest Hospital,Changsha 410013,China)
出处
《中南大学学报(医学版)》
北大核心
2025年第5期793-804,共12页
Journal of Central South University (Medical Science)
基金
湖南省自然科学基金(2023JJ60395)
长沙市自然科学基金(kq2208450)。
作者简介
第一作者:谢楠,Email:xienan0731@163.com,ORCID:0009-0007-1965-3043;通信作者:苑聪,副主任医师,Email:yuancong2023@vip.163.com,ORCID:0009-0009-7151-7641。
