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脾脏硬度和体积有助于预测肝细胞癌患者肝切除术后的肝衰竭。

Spleen stiffness and volume help to predict posthepatectomy liver failure in patients with hepatocellular carcinoma.

作者信息

Peng Wei, Zhang Xiao-Yun, Li Chuan, Wen Tian-Fu, Yan Lv-Nan, Yang Jia-Yin

机构信息

Department of Liver Surgery & Liver Transplantation Center, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.

出版信息

Medicine (Baltimore). 2019 May;98(18):e15458. doi: 10.1097/MD.0000000000015458.

DOI:10.1097/MD.0000000000015458
PMID:31045820
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6504243/
Abstract

Posthepatectomy liver failure (PHLF) is the main cause of perioperative death, and liver cirrhosis is one of the most important risk factors for PHLF. Spleen stiffness (SS) is a novel ultrasonic indicator for liver cirrhosis and portal hypertension, however, it is not clear that whether it has a significant influence on PHLF. Future remnant liver volume (FRLV) is a significant factor for liver regeneration after hepatectomy, spleen volume (SV) could also predict the degree of liver cirrhosis, and recent literatures reported that SV to FRLV ratio (SV/FRLV) could predict small for size syndrome (SFSS) in liver transplantation, however, the relationship between SV/FRLV and PHLF in patients receiving hepatectomy is not known. Systemic inflammatory response (SIR) plays a significant role in the pathogenesis and progression of liver cirrhosis, however, it is not very clear about the exact relationship between SIR and PHLF.We prospectively collected the medical data of consecutive patients diagnosed with hepatocellular carcinoma (HCC) who underwent hepatectomy from August 2015 to February 2016. Preoperative measurements of SS, liver stiffness (LS), SV, FRLV, and SIR were performed on all patients. A univariate analysis was performed to find the risk factors of PHLF and a multivariate analysis was used to identify independent risk factors. The predictive efficiency of the risk factors was evaluated by receiver operating characteristic (ROC) curve.Twenty three (23) (14.6%) patients developed PHLF. Univariate analysis found several variables significantly related to PHLF, they were as follows: tumor diameter (P = .01), cirrhosis (P = .001), neutrophil to lymphocyte ratio (NLR) (P = .018), LS (P = .001), SS (P = .001), SV/FRLV (P < .001), operation duration (P = .003), transfusion (P = .009), hepatic inflow occlusion (HIO) (P = .001). Finally, SV/FRLV (P < .001, hazard ratio (HR) = 26.356, 95% confidence interval (CI) 1.627-425.21), SS (P = .009, HR = 1.077, 95%CI 1.017-1.141), and HIO time (P = .002, HR = 1.043, 95%CI 1.014-1.072) were determined as the independent risk factors of PHLF by multivariate analysis.SS and SV/FRLV help to predict the development of PHLF in patients with hepatocellular carcinoma.

摘要

肝切除术后肝衰竭(PHLF)是围手术期死亡的主要原因,而肝硬化是PHLF最重要的危险因素之一。脾硬度(SS)是一种用于评估肝硬化和门静脉高压的新型超声指标,然而,其对PHLF是否有显著影响尚不清楚。未来残余肝体积(FRLV)是肝切除术后肝脏再生的重要因素,脾体积(SV)也可预测肝硬化程度,最近的文献报道SV与FRLV的比值(SV/FRLV)可预测肝移植中的小肝综合征(SFSS),然而,接受肝切除术患者的SV/FRLV与PHLF之间的关系尚不清楚。全身炎症反应(SIR)在肝硬化的发病机制和进展中起重要作用,然而,SIR与PHLF的确切关系尚不完全清楚。我们前瞻性收集了2015年8月至2016年2月期间连续诊断为肝细胞癌(HCC)并接受肝切除术患者的医疗数据。对所有患者进行术前SS、肝硬度(LS)、SV、FRLV和SIR测量。进行单因素分析以寻找PHLF的危险因素,并使用多因素分析确定独立危险因素。通过受试者工作特征(ROC)曲线评估危险因素的预测效率。23例(14.6%)患者发生PHLF。单因素分析发现几个与PHLF显著相关的变量,如下所示:肿瘤直径(P = 0.01)、肝硬化(P = 0.001)、中性粒细胞与淋巴细胞比值(NLR)(P = 0.018)、LS(P = 0.001)、SS(P = 0.001)、SV/FRLV(P < 0.001)、手术时间(P = 0.003)、输血(P = 0.009)、肝血流阻断(HIO)(P = 0.001)。最后,多因素分析确定SV/FRLV(P < 0.001,风险比(HR)= 26.356,95%置信区间(CI)1.627 - 425.21)、SS(P = 0.009,HR = 1.077,95%CI 1.017 - 1.141)和HIO时间(P = 0.002,HR = 1.043,95%CI 1.014 - 1.072)为PHLF的独立危险因素。SS和SV/FRLV有助于预测肝细胞癌患者PHLF的发生。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/dc9b962fe93f/medi-98-e15458-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/57e812321bd0/medi-98-e15458-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/493b4904d8a5/medi-98-e15458-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/dc9b962fe93f/medi-98-e15458-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/57e812321bd0/medi-98-e15458-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/493b4904d8a5/medi-98-e15458-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f70/6504243/dc9b962fe93f/medi-98-e15458-g006.jpg

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