机构：[1]Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, 87 Dingjiaqiao Road, Nanjing, 210009, China.[2]Department of Minimally Invasive Interventional Radiology, Yunnan Tumor Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650106, China.[3]Department of Radiology, Lishui Central Hospital, Wenzhou Medical University, Lishui, 323000, China.[4]Department of Interventional Radiology, Anhui Provincial Hospital, The First Affiliated Hospital of University of Science and Technology of China (USTC), Hefei, 230001, China.[5]Department of Interventional Medicine, The Second Hospital of Shandong University, Jinan, 250033, China.[6]Department of Interventional Radiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, China
To develop, validate, and compare early warning models of the 30-day mortality risk for patients with malignant biliary obstruction (MBO) undergoing percutaneous transhepatic biliary stent placement (PTBS).
Between January 2013 and October 2018, this multicenter retrospective study included 299 patients with MBOs who underwent PTBS. The training set consisted of 166 patients from four cohorts, and another two independent cohorts were allocated as external validation sets A and B with 75 patients and 58 patients, respectively. A logistic model and an artificial neural network (ANN) model were developed to predict the risk of 30-day mortality after PTBS. The predictive performance of these two models was validated internally and externally.
The ANN model had higher values of area under the curve than the logistic model in the training set (0.819 vs 0.797), especially in the validation sets A (0.802 vs 0.714) and B (0.732 vs 0.568). Both models had high accuracy in the three sets (75.9-83.1%). Along with a high specificity, the ANN model improved the sensitivity. The net reclassification improvement and integrated discrimination improvement also demonstrated that the ANN model led to improvements in predictive ability compared with the logistic model.
Early warning models were proposed to predict the risk of 30-day mortality after PTBS in patients with MBO. The ANN model has higher accuracy and better generalizability than the logistic model.
基金：
the National Key Scientific
Instrument and Equipment Development Projects of China
(81827805), Innovation Platform of Jiangsu Provincial Medical
Center (YXZXA2016005), and National Natural Science Foundation
of China (81520108015, 81671796).
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2019]版：
大类|4 区医学
小类|4 区心脏和心血管系统4 区核医学
最新[2023]版：
大类|3 区医学
小类|3 区心脏和心血管系统3 区核医学
第一作者：
第一作者机构：[1]Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, 87 Dingjiaqiao Road, Nanjing, 210009, China.
共同第一作者：
通讯作者：
推荐引用方式(GB/T 7714)：
Zhou Hai-Feng,Lu Jian,Zhu Hai-Dong,et al.Early Warning Models to Estimate the 30-Day Mortality Risk After Stent Placement for Patients with Malignant Biliary Obstruction.[J].Cardiovascular and interventional radiology.2019,42(12):1751-1759.doi:10.1007/s00270-019-02331-5.
APA：
Zhou Hai-Feng,Lu Jian,Zhu Hai-Dong,Guo Jin-He,Huang Ming...&Teng Gao-Jun.(2019).Early Warning Models to Estimate the 30-Day Mortality Risk After Stent Placement for Patients with Malignant Biliary Obstruction..Cardiovascular and interventional radiology,42,(12)
MLA：
Zhou Hai-Feng,et al."Early Warning Models to Estimate the 30-Day Mortality Risk After Stent Placement for Patients with Malignant Biliary Obstruction.".Cardiovascular and interventional radiology 42..12(2019):1751-1759
