使用基于门静脉宽度、炎症指数和白蛋白-胆红素评分的nomogram预测肝切除术后肝功能衰竭。

IF 1.8 4区 医学 Q3 GASTROENTEROLOGY & HEPATOLOGY
Ke Sun, Jiang-Bin Li, Ya-Feng Chen, Zhong-Jie Zhai, Lang Chen, Rui Dong
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引用次数: 0

摘要

背景:肝切除术后肝衰竭(PHLF)是导致肝细胞癌(HCC)患者术后死亡的主要并发症之一。通过术前评估,帮助临床医生尽早识别潜在的高危PHLF患者至关重要。目的:探讨前列腺肥大的危险因素并建立预测模型。方法:本研究纳入2014年1月至2023年12月空军医科大学第二附属医院收治的248例肝癌患者;随机抽样将患者分为训练组(n = 164)和验证组(n = 84)。通过单变量和多变量分析确定PHLF发生的自变量,并将其可视化为模态图。最后,通过受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)与传统模型进行比较。结果:本研究中,门静脉宽度[比值比(OR) = 1.603, 95%CI: 1.288 ~ 1.994, P≤0.001]、术前中性粒细胞与淋巴细胞比值(NLR) (OR = 1.495, 95%CI: 1.126 ~ 1.984, P = 0.005)、白蛋白-胆红素(ALBI)评分(OR = 8.868, 95%CI: 2.144 ~ 36.678, P = 0.003)为PHLF的独立危险因素。利用这些因素建立了一个nomogram预测模型。ROC和DCA分析显示,该模型的预测效果和临床价值优于传统模型。结论:成功建立了基于门静脉宽度、NLR和ALBI评分预测HCC患者PHLF的Nomogram新模型,优于传统模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting post-hepatectomy liver failure using a nomogram based on portal vein width, inflammatory indices, and the albumin-bilirubin score.

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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