Predicting post-hepatectomy liver failure using a nomogram based on portal vein width, inflammatory indices, and the albumin-bilirubin score

被引:0
作者
Sun, Ke [1 ]
Li, Jiang-Bin [2 ]
Chen, Ya-Feng [2 ]
Zhai, Zhong-Jie [3 ]
Chen, Lang [2 ]
Dong, Rui [2 ]
机构
[1] Xian Med Coll, Xian 710000, Shaanxi, Peoples R China
[2] Air Force Med Univ, Dept Gen Surg, Affiliated Hosp 2, 569 Xinsi Rd, Xian 710000, Shaanxi, Peoples R China
[3] Air Force Med Univ, Stat Teaching & Res Off, Xian 710038, Shaanxi, Peoples R China
关键词
Nomogram; Hepatocellular carcinoma; Post-hepatectomy liver failure; Albumin-bilirubin score; Portal vein width; HEPATOCELLULAR-CARCINOMA; LYMPHOCYTE RATIO; RESECTION; NEUTROPHIL; RECURRENCE; PREVENTION; SURVIVAL; CANCER; MODEL;
D O I
10.4240/wjgs.v17.i2.99529
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
BACKGROUND Post-hepatectomy liver failure (PHLF) after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma (HCC). It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation. AIM To identify risk factors for PHLF and develop a prediction model. METHODS This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023; these patients were divided into a training group (n = 164) and a validation group (n = 84) via random sampling. The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms. Ultimately, comparisons were made with traditional models via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS In this study, portal vein width [odds ratio (OR) = 1.603, 95%CI: 1.288-1.994, P <= 0.001], the preoperative neutrophil-to-lymphocyte ratio (NLR) (OR = 1.495, 95%CI: 1.126-1.984, P = 0.005), and the albumin-bilirubin (ALBI) score (OR = 8.868, 95%CI: 2.144-36.678, P = 0.003) were independent risk factors for PHLF. A nomogram prediction model was developed using these factors. ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models. CONCLUSION A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width, the NLR, and the ALBI score, which outperforms the traditional model.
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页数:11
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