A Novel Predictive Method Incorporating Parameters of Main Pulmonary Artery Bifurcation for Short-Term Prognosis in Non-high-risk Acute Pulmonary Embolism Patients

Frontiers in Physiology

卷:11

Dong Jia¹  Xue-Lian Li²  Gang Hou³  Xiao-Ming Zhou⁴ 

[1] Department of Emergency, Shengjing Hospital of China Medical University, Shenyang, China;

[2] Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China;

[3] Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of China Medical University, Shenyang, China;

[4] Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China;

关键词: computed tomography angiography;    pulmonary embolism;    pulmonary artery;    pulmonary hypertension;    main pulmonary artery bifurcation;   

DOI  :  10.3389/fphys.2020.00420

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown