Table_1_Exploration of a nomogram prediction model of 30-day survival in adult ECMO patients.pdf

ObjectiveTo investigate the factors of 30-day survival in ECMO patients, establish a nomogram model, and evaluate the predictive value of the model.MethodsA 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.ResultsThe 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.ConclusionThe 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.

旨在探究体外膜肺氧合（ECMO）患者30天存活率的影响因素，构建Nomogram模型，并评估该模型的预测价值。方法：2018年1月至2021年3月，共有105例ECMO患者被收入安徽医科大学第一附属医院重症医学科。通过Cox回归分析筛选出风险因素。基于多因素分析结果，利用R软件构建Nomogram模型，并通过Bootstrap和校准验证模型的区分度。结果：结果显示，性别、急性生理和慢性健康评估（APACHE）II评分、ECMO启动前弥散性血管内凝血（DIC）评分及去甲肾上腺素平均日剂量为预后的独立风险因素。Bootstrap内部验证表明Nomogram模型得到验证，校正C-index为0.886，显示良好的区分度。校准曲线（校准）显示Nomogram模型具有良好的一致性。决策曲线分析（DCA）曲线显示，在两极端曲线之上具有良好的临床有效性。绘制Kaplan-Meier曲线，对三分位患者进行分组，并与第一、二组进行比较。第三组预测ECMO患者的最差30天预后。结论：基于性别、APACHE II评分、DIC评分及去甲肾上腺素平均日剂量构建的Nomogram预测模型，可有效筛选影响预后的因素，并为ECMO患者的个体化治疗提供参考。