Zhang Yaoliang, Li Juan, Xie Wenjie, Yang Chao, Peng Guilin, Xu Xin, Lan Lan
Department of Anesthesiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
School of Nursing, Southern Medical University, Guangzhou, China.
J Thorac Dis. 2024 Jan 30;16(1):231-240. doi: 10.21037/jtd-23-452. Epub 2024 Jan 15.
Extracorporeal membrane oxygenation (ECMO) has been increasingly used as life support for lung transplantation. However, there are no clinical risk models to predict whether ECMO support is required for lung transplantation. This study developed a simple risk score to predict the need for intraoperative ECMO in patients undergoing lung transplantation, identify high-risk patients who need ECMO support, and guide clinical interventions.
Patients, who underwent lung transplantation between January 1, 2016 and July 31, 2021, were systematically reviewed. All enrolled patients were divided in a ratio of 7:3 to establish the development and validation datasets. A risk score model was established using stepwise logistic regression and verified using bootstrapping and the split-sample method.
A total of 248 patients who underwent lung transplants were enrolled. Multivariate analysis showed that the primary disease diagnosis, pulmonary artery systolic pressure, sex, surgical type, creatine kinase isoenzyme-MB, and pro-B-type natriuretic peptide were risk factors for intraoperative ECMO during lung transplantation. The risk score was established and calibrated according to these six factors, ranging from 0 to 41, with the associated prediction of intraoperative use of ECMO ranging from 1.5% to 99.7% (Hosmer-Lemeshow χ=5.624; P=0.689). Good discrimination was verified by developing and validating the datasets (C-statistics =0.850 and 0.842, respectively). Based on the distribution of the scores, the three levels were classified as low-risk (0-10], moderate-risk (10-20], and high-risk (20-41].
This simple risk score model effectively predicts the need for intraoperative ECMO and stratifies high-risk patients who require ECMO support.
体外膜肺氧合(ECMO)已越来越多地用作肺移植的生命支持手段。然而,目前尚无临床风险模型来预测肺移植是否需要ECMO支持。本研究开发了一种简单的风险评分,以预测肺移植患者术中对ECMO的需求,识别需要ECMO支持的高危患者,并指导临床干预。
对2016年1月1日至2021年7月31日期间接受肺移植的患者进行系统回顾。所有纳入患者按7:3的比例分为开发数据集和验证数据集。采用逐步逻辑回归建立风险评分模型,并通过自抽样法和拆分样本法进行验证。
共纳入248例接受肺移植的患者。多因素分析显示,原发性疾病诊断、肺动脉收缩压、性别、手术类型、肌酸激酶同工酶-MB和前B型利钠肽是肺移植术中使用ECMO的危险因素。根据这六个因素建立并校准了风险评分,范围为0至41,术中使用ECMO的相关预测范围为1.5%至99.7%(Hosmer-Lemeshowχ=5.624;P=0.689)。通过开发和验证数据集验证了良好的区分度(C统计量分别为0.850和0.842)。根据评分分布,将三个水平分为低风险(0-10]、中度风险(10-20]和高风险(20-41]。
这种简单的风险评分模型有效地预测了术中对ECMO的需求,并对需要ECMO支持的高危患者进行了分层。