急性爆发性心肌炎风险预测模型的开发与验证  

Development and validation of a risk prediction model for acute fulminant myocarditis

作　　者：周文科 漆靖 Zhou Wenke;Qi Jing(Department of Emergency,The Fourth Hospital of Changsha;Department of Emergency,The Third Xiangya Hospital of Central South University,Changsha,China)

机构地区：[1]长沙市第四医院急诊科 [2]中南大学湘雅三医院急诊科

出　　处：《实用休克杂志（中英文）》2024年第3期166-169,174,共5页Journal of Practical Shock

基　　金：湖南省急危重症急救能力提升与突发公共卫生应急救治关键技术协同创新工程(项目编号:2020SK1010)

摘　　要：目的急性心肌炎是一种临床表现多样的急性炎症性疾病,部分患者可迅速进展为高死亡率的急性爆发性心肌炎,早期识别并改善预后。方法回顾性收集2020年1月至2023年12月湘雅三医院急诊科确诊的204例急性心肌炎患者的临床数据,并将其按3:1比例随机分为训练集和验证集。多因素Logistic回归分析筛选独立预测因子并构建列线图模型,并通过ROC曲线评估其预测性能。结果在204例患者中,50例(24.51%)进展为AFM。血清B型脑钠肽升高、左室射血分数下降及C反应蛋白升高为独立预测因子。列线图模型在验证集中的曲线下面积为0.949,预测性能较高。结论本研究构建的列线图模型可有效预测急性心肌炎患者进展为AFM的风险,具有临床应用潜力。Objective Acute myocarditis is an acute inflammatory disease with diverse clinical manifestations.Some patients can rapidly progress to acute fulminant myocarditis,which has a high mortality rate.Therefore,early identification is critical for improving patient outcomes.Methods Clinical data from 204 patients diagnosed with acute myocarditis in the Emergency Department of Xiangya Third Hospital between January 2020 and December 2023 were retrospectively collected and randomly divided into training and validation sets in a 3:1 ratio.Independent predictors were identified using multivariate logistic regression,and a nomogram model was constructed.The model's predictive performance was evaluated using the ROC curve.Results Among the 204 patients,50(24.51%)progressed to AFM.Elevated serum BNP,reduced LVEF,and elevated CRP were identified as independent predictors.The nomogram model demonstrated good predictive performance with an AUC of 0.949 in the validation set.Conclusions The nomogram model developed in this study effectively predicts the risk of progression to AFM in patients with acute myocarditis and shows potential for clinical application.

关 键 词：急性心肌炎 爆发性心肌炎 列线图 预后预测 

分 类 号：R542.21[医药卫生—心血管疾病]