Developing and validating a nomogram based on skeletal muscle index and clinical scoring system for prediction of liver failure after hepatectomy

列线图 医学 肝切除术 接收机工作特性 多元分析 曲线下面积 肝病 内科学 多元统计 阶段(地层学) 肝衰竭 外科 切除术 统计 数学 古生物学 生物
作者
Chenyue Ding,Jianye Jia,Han Liu,Wei Zhou,Ziyan Liu,Genji Bai,Qian Wang
出处
期刊:Frontiers in Oncology [Frontiers Media]
卷期号:13
标识
DOI:10.3389/fonc.2023.1036921
摘要

Hepatectomy is the preferred treatment for patients with liver tumors. Post-hepatectomy liver failure (PHLF) remains one of the most fatal postoperative complications. We aim to explore the risk factors of PHLF and create a nomogram for early prediction of PHLF.We retrospectively analyzed patients undergoing hepatectomy at the Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University between 2015 and 2022, and the patients were divided into training and internal validation cohorts at an 8:2 ratio randomly. The patients undergoing liver resection from the Affiliated Huaian Hospital of Xuzhou Medical University worked as external validation. Then, a nomogram was developed which was based on multivariate analyses to calculate the risk of PHLF. The area under the ROC curve (AUROC) and Hosmer -Lemeshow test was used to evaluate the prediction effect of the model.A total of 421 eligible patients were included in our study. Four preoperative variables were identified after multivariate analysis as follows, ASA (American Society of Anesthesiologists) score, Child-Pugh score, SMI (Skeletal muscle index), and MELD (Model for end-stage liver disease) score as independent predictors of PHLF. The area under the ROC curve of the predictive model in the training, internal, and external validation cohorts were 0.89, 0.82, and 0.89. Hosmer -Lemeshow P values in the training, internal, and external validation cohorts were 0.91, 0.22, and 0.15. The Calibration curve confirmed that our nomogram prediction results were in accurate agreement with the actual occurrence of PHLF.We construct a nomogram to predict the grade B/C PHLF of ISGLS (International Study Group of Liver Surgery) in patients who underwent hepatic resection based on risk factors. This tool can provide a visual and accurate preoperative prediction of the grade B/C PHLF and guide the next step of clinical decision-making.

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