Jia Dong, Li Xue-Lian, Hou Gang, Zhou Xiao-Ming
Department of Emergency, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China.
Front Physiol. 2020 Apr 30;11:420. doi: 10.3389/fphys.2020.00420. eCollection 2020.
The aim of this study was to build a formula to predict short-term prognosis using main pulmonary artery (MPA) parameters reconstructed from computed tomographic pulmonary angiography in non-high-risk acute pulmonary embolism (PE) patients. After reconstructing the MPA and its centerline, the MPA, the right and left pulmonary artery inlet, and the MPA outlet plane were differentiated to measure the cross-sectional area (CSA), the maximal diameter and the hydraulic diameter. The MPA bifurcation area, volume and angle were measured. MPA dilation was defined as >29 mm at the transverse section plane. The patients were randomly divided into a training set and a validation set. A least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was used to build a predictive formula. The performances of the predictive formula from LASSO were tested by the area under the receiver operating characteristic curve (AUC) and precision-recall (PR) curve with 10-fold cross-validation. The clinical utility was assessed by decision curve analysis (DCA). In total, 296 patients were enrolled and randomly divided (50:50) into a training set and a validation set. The LASSO predictive formula (lambda.1SE) was as follows: 0.92 × MPA bifurcation area + 0.50 × MPA outlet hydraulic diameter + 0.10 × MPA outlet CSA. The AUCs of the predictive formula were 0.860 (95% CI: 0.795-0.912) and 0.943 (95% CI: 0.892-0.975) in the training set and validation set, respectively. The LASSO predictive formula had a higher average area under the PR curve than MPA dilation (0.71 vs. 0.23 in the training set and 0.55 vs. 0.23 in the validation set) and added a net benefit in clinical utility by DCA. Integration of MPA outlet CSA, hydraulic diameter, and bifurcation area with the LASSO predictive formula as a novel weighting method facilitated the prediction of poor short-term prognosis within 30 days after hospital admission in non-high-risk acute PE patients.
本研究的目的是构建一个公式,用于使用从计算机断层扫描肺动脉造影重建的主肺动脉(MPA)参数预测非高危急性肺栓塞(PE)患者的短期预后。重建MPA及其中心线后,区分MPA、左右肺动脉入口和MPA出口平面,以测量横截面积(CSA)、最大直径和水力直径。测量MPA分叉面积、体积和角度。MPA扩张定义为在横断面上>29mm。将患者随机分为训练集和验证集。使用最小绝对收缩和选择算子(LASSO)逻辑回归算法构建预测公式。通过接受者操作特征曲线(AUC)下的面积和精确召回率(PR)曲线,采用10倍交叉验证对LASSO预测公式的性能进行测试。通过决策曲线分析(DCA)评估临床实用性。总共纳入296例患者,并将其随机(50:50)分为训练集和验证集。LASSO预测公式(lambda.1SE)如下:0.