Piotrowski Damian, Sączewska-Piotrowska Anna, Jaroszewicz Jerzy, Boroń-Kaczmarska Anna
Medical University of Silesia in Katowice, Poland.
University of Economics in Katowice, Poland.
Clin Exp Hepatol. 2018 Dec;4(4):240-246. doi: 10.5114/ceh.2018.80125. Epub 2018 Dec 3.
To assess the performance of Child-Turcotte-Pugh (CTP) and Model for End-Stage Liver Disease (MELD) scores' kinetics during hospitalization in predicting in-hospital mortality in patients with liver cirrhosis.
One hundred and seventy-four cases of hospitalized liver cirrhosis patients were selected. The diagnosis of cirrhosis was made based on clinical, biochemical, ultrasonic, histological, and endoscopic findings and results. CTP and MELD scores at admission and ΔCTP and ΔMELD were calculated. Univariate and multivariate logistic regression and receiver-operating characteristic (ROC) curve analysis were performed. In the models, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. The area under the ROC curve (AUC) was used to measure the accuracy. For the optimal cutoff point, sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were calculated. The Kaplan-Meier method was used to construct survival curves, and the log-rank test was used to compare time to death, with respect to MELD and CTP categories.
Among the assessed scores, the highest area under the ROC curve (AUC) in univariate logistic regression analysis was calculated for ΔMELD ≥ 1, followed by ΔCTP ≥ 1, CTP > 8, and MELD > 17. Based on the selected criteria, multivariate models were created that were characterized by an outstanding ability to predict the in-hospital mortality.
In-hospital mortality is relatively high in patients with liver cirrhosis. The combination of CTP and MELD scoring methods, combined with their kinetics, allows for the prediction of short-term mortality.
评估Child-Turcotte-Pugh(CTP)评分和终末期肝病模型(MELD)评分在肝硬化患者住院期间的变化情况对预测院内死亡率的性能。
选取174例住院肝硬化患者。肝硬化的诊断基于临床、生化、超声、组织学及内镜检查结果。计算入院时的CTP和MELD评分以及ΔCTP和ΔMELD。进行单因素和多因素逻辑回归分析以及受试者工作特征(ROC)曲线分析。在模型中,计算比值比(OR)和95%置信区间(CI)。ROC曲线下面积(AUC)用于衡量准确性。对于最佳截断点,计算敏感度(SE)、特异度(SP)、阳性预测值(PPV)和阴性预测值(NPV)。采用Kaplan-Meier法构建生存曲线,并用对数秩检验比较MELD和CTP分类下的死亡时间。
在评估的评分中,单因素逻辑回归分析中ROC曲线下面积(AUC)最高的是ΔMELD≥1,其次是ΔCTP≥1、CTP>8和MELD>17。基于选定标准创建了多因素模型,其预测院内死亡率的能力突出。
肝硬化患者院内死亡率相对较高。CTP和MELD评分方法及其变化情况相结合,可用于预测短期死亡率。