Cui Liangwen, Zha Yutao, Zhang Cheng, Zhang Hui, Yu Chao, Rui Huang, Shao Min, Liu Nian
Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Department of Anhui Provincial Cancer Institute, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Front Med (Lausanne). 2023 Feb 28;10:1062918. doi: 10.3389/fmed.2023.1062918. eCollection 2023.
To investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model.
A total of 105 patients with extracorporeal membrane oxygenation (ECMO) were admitted to the Department of Critical Care Medicine, The First Affiliated Hospital of Anhui Medical University, from January 2018 to March 2021. Cox regression analysis screened out the risk factors. Based on the results of multivariate analysis, the nomogram model was established by using R software, and the discrimination of the model was verified by bootstrap and calibration.
The results showed that sex, acute physiology and chronic health evaluation (APACHE) II score, disseminated intravascular coagulation (DIC) score before ECMO initiation and average daily dose of norepinephrine were independent risk factors for prognosis. Verify that the nomogram model is verified by bootstrap internally, and the corrected C-index is C-index: 0.886, showing a good degree of discrimination. The calibration curve (calibration) showed that the nomogram model had good agreement. The decision curve analysis(DCA) curve shows good clinical validity above the two extreme curves. Kaplan-Meier curves were drawn for patients in the tertile and compared with the first and second groups. The third group predicted the worst 30-day prognosis for ECMO patients.
The nomogram prediction model constructed based on the sex, APACHE II and DIC score, average daily dose of norepinephrine can effectively screen out the factors affecting the prognosis and provide a reference for individualized treatment of ECMO patients.
探讨体外膜肺氧合（ECMO）患者30天生存的影响因素，建立列线图模型，并评估该模型的预测价值。
2018年1月至2021年3月，安徽医科大学第一附属医院重症医学科共收治105例接受体外膜肺氧合治疗的患者。采用Cox回归分析筛选危险因素。基于多因素分析结果，使用R软件建立列线图模型，并通过自抽样法和校准对模型的辨别力进行验证。
结果显示，性别、急性生理与慢性健康状况评分系统（APACHE）Ⅱ评分、启动ECMO前的弥散性血管内凝血（DIC）评分以及去甲肾上腺素日均剂量是预后的独立危险因素。内部自抽样法验证列线图模型，校正后的C指数为0.886，显示出良好的辨别度。校准曲线表明列线图模型具有良好的一致性。决策曲线分析（DCA）曲线显示在两条极端曲线之上具有良好的临床有效性。绘制三分位数患者的Kaplan-Meier曲线，并与第一组和第二组进行比较。第三组预测ECMO患者30天预后最差。
基于性别、APACHEⅡ评分、DIC评分、去甲肾上腺素日均剂量构建的列线图预测模型可有效筛选出影响预后的因素，为ECMO患者的个体化治疗提供参考。
