A nomogram for predicting post-hepatectomy liver failure in patients with hepatocellular carcinoma based on spleen-volume-to-platelet ratio

被引:4
|
作者
Meng, Xue-Qin [1 ]
Miao, Hui [2 ]
Xia, Yong [3 ]
Shen, Hao [3 ]
Qian, Yi [1 ]
Chen, Yan [1 ]
Shen, Feng [3 ]
Guo, Jia [1 ,4 ]
机构
[1] Second Mil Med Univ, Naval Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Ultrasound, Shanghai, Peoples R China
[2] Second Mil Med Univ, Coll Basic Med Sci, Dept Med Genet, Shanghai, Peoples R China
[3] Shanghai Eastern Hepatobiliary Surg Hosp, Dept Hepat Surg 4, Shanghai, Peoples R China
[4] Second Mil Med Univ, Shanghai Eastern Hepatobiliary Surg Hosp, Dept Ultrasound, 225 Changhai Rd, Shanghai 200438, Peoples R China
关键词
Post-hepatectomy liver failure; Spleen volume -to -platelet ratio; Liver resection; Hepatocellular carcinoma; HEPATIC RESECTION; PREALBUMIN; DISEASE; COUNT; DEFINITION; SURGERY; INDEX;
D O I
10.1016/j.asjsur.2022.05.001
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background and objectives: Post-hepatectomy liver failure (PHLF) is one of the most serious complica-tions after hepatectomy in patients with hepatocellular carcinoma (HCC), and has an association with high morbidity and mortality. This study aimed to explore the risk factors of PHLF and to establish and validate a nomogram to predict PHLF.Methods: We retrospectively analyzed 971 HCC patients undergoing major liver resection at the Eastern Hepatobiliary Surgery Hospital between 2011 and 2016, and established a nomogram based on multi-variate analyses for predicting PHLF. The predictive accuracy and discriminative ability of the nomogram were evaluated by concordance index (C-index) and calibration curve. The predictive ability of PHLF of this nomogram was compared with conventional models using receiver operating characteristic (ROC) curves.Results: The incidence of PHLF was 18.8%. Multivariate analysis identified age, BMI, preoperative ascites, preoperative prealbumin, spleen volume-to-platelet ratio, total bilirubin, and intraoperative blood loss as independent predictors of PHLF. The area under ROC curve (AUROC) of the predictive model was 0.668 and was higher than that of the albumin-bilirubin score (ALBI). The optimal cut-off value of the model was 124.Conclusions: We constructed a nomogram for predicting PHLF based on risk factors. The nomogram can assist clinicians in identifying patients with high-risk PHLF, eventually facilitating earlier interventions and improving clinical outcomes.& COPY; 2022 Asian Surgical Association and Taiwan Robotic Surgery Association. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:399 / 404
页数:6
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