Nomogram Prediction for Postoperative Mortality of Orthotopic Liver Transplantation

被引:2
|
作者
Liu, Jialin [1 ,2 ]
Li, Jiacen [3 ,4 ]
Su, Wenjie [3 ,4 ]
Yang, Xi [3 ,4 ]
机构
[1] Sichuan Univ, West China Hosp, Informat Ctr, Chengdu, Sichuan, Peoples R China
[2] West China Med Sch, Dept Med Informat, Chengdu, Sichuan, Peoples R China
[3] Univ Elect Sci & Technol China, Sichuan Prov Peoples Hosp, Dept Anesthesiol, Chengdu, Peoples R China
[4] Chinese Acad Sci, Sichuan Translat Med Res Hosp, Chengdu, Peoples R China
关键词
Hepatic; Prediction model; Risk factors; Transplant; RISK-FACTORS; MORBID-OBESITY; TRACHEAL EXTUBATION; DONOR AGE; OUTCOMES; IMPACT; DISEASE; ANESTHESIA; PROGNOSIS; INFECTION;
D O I
10.6002/ect.2021.0431
中图分类号
R3 [基础医学]; R4 [临床医学];
学科分类号
1001 ; 1002 ; 100602 ;
摘要
Objectives: The purpose of this study was to assess and predict risk factors for death within 30 days after orthotopic liver transplant and to develop a nomogram to predict mortality after liver transplant. Materials and Methods: We retrospectively studied 185 patients who underwent orthotopic liver transplant at Sichuan Provincial People's Hospital from January 1, 2010, to December 31, 2018. Multivariable logistic regression analyses were used to identify independent risk factors. A nomogram model was developed to predict mortality after liver transplant. The performance of the prediction model was assessed and validated by receiver operating characteristic curve and bootstrap methods (1000 replications). Results: Multivariable logistic regression analyses revealed that tracheal extubation time, postoperative infection, and intraperitoneal hemorrhage posttransplant were independent risk factors for mortality after liver transplant. The receiver operating characteristic curve of the nomogram prediction model was 0.896 (96% CI, 0.803-0.989), and the mean absolute error of internal validation by bootstrap (1000 replications) was 0.019 (n = 184). These results showed that the nomogram model had an excellent prediction accuracy. Conclusions: A nomogram model can provide clinicians with an individualized risk assessment of perioperative mortality in liver transplant recipients.
引用
收藏
页码:1099 / 1104
页数:6
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