摘要
目的:探讨肝癌肝脏切除手术后肝脏功能恢复影响因素,并建立风险预测模型。方法:回顾性分析2015年2月—2016年9月间行半肝切除手术的50例肝癌患者术的相关临床资料,通过单变量与多变量分析对筛选出可能影响肝癌患者术后肝脏功能恢复的因素,用所得各因素及其统计值建立风险预测模型。结果:患者手术前吲哚菁绿15分钟滞留率(ICGR15)、清除指数(HH15)、残余肝脏体积/标准肝脏体积(RLV/SLV)均为半肝切除手术后肝脏功能恢复的独立危险因素(P=0.002、P<0.001、P=0.007);所得到的风险预测模型为:风险系数(R)=31.871×(RLV/SLV)-1.689×(ICG R15)-19.663×HH15;R的临界值为0.90时,其预测术后出现肝功能不全的ROC曲线下面积为0.96,敏感度和特异度为97.5%和90%。结论:较低的RLV/SLV以及较高的ICGl5R和HH15是肝癌患者行肝脏切除术后肝功能不全的危险因素,所建立的预测模型有一定的风险评估价值。
Objective： To investigate the influential factors for recovery and then to establish a risk prediction model. of liver function from hepatectomy for liver cancer Methods： The relevant clinical data of 50 patients with liver cancer undergoing hemihepatectomy from February 2015 to September 2016 were retrospectively analyzed. ＂lhe factors affecting postoperative liver function recovery of liver cancer patients were identified by univariate and multivariate analyses, and then, all the obtained factors and their statistical values were used to create the risk prediction model.Results： The preoperative 15-minute retention of indocyanine green （ICG R15）, residual liver volume/standard remnant liver volume （RLV/SLV） and clearance index （HH15） are independent risk factors for recovery of liver function from hemihepatectomy （P=0.002. P〈0.001 and P=0.007）. The obtained risk prediction model was presented as follows： risk coefficient （R）=31.871x（RLV/SLV）-l.689x（ICG R15）-19.663xHH15. At the cut off value of R=0.90, the area under the ROC curve of this model for predicting postoperative liver dysfunction was 0.96, with the sensitivity and specificity of 97.5% and 90%, respectively. Conclusion： Lower RLV/SLV or higher ICG15R and HH15 are risk factors for postoperative liver dysfunction in patients after hepatectomy for liver cancer, and the established prediction model may have certain value for risk assessment.
出处
《中国普通外科杂志》
CAS
CSCD
北大核心
2017年第7期825-830,共6页
China Journal of General Surgery
基金
国家自然科学基金资助项目(81272398)
关键词
肝肿瘤
肝切除术
肝功能不全
危险因素
预测
Liver Neoplasms
Hepatectomy
Hepatic Insufficiency
Risk Factors
Forecasting
