Department of Hepatology and Gastroenterology, The Third Central Clinical College of Tianjin Medical University, No. 83, Jintang Road, Hedong District, Tianjin, 300170, China.
Liver Disease Center (Difficult & Complicated Liver Diseases and Artificial Liver Center), Beijing You'an Hospital Affiliated to Capital Medical University, Beijing, China.
Sci Rep. 2021 Jan 19;11(1):1810. doi: 10.1038/s41598-021-81431-0.
Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately. Our aim was to build and validate a new scoring system to predict short-term prognosis using baseline and dynamic data in ACLF. We conducted a retrospective cohort analysis of patients with ACLF from three different hospitals in China. To construct the model, we analyzed a training set of 541 patients from two hospitals. The model's performance was evaluated in a validation set of 130 patients from another center. In the training set, multivariate Cox regression analysis revealed that age, WGO type, basic etiology, total bilirubin, creatinine, prothrombin activity, and hepatic encephalopathy stage were all independent prognostic factors in ACLF. We designed a dynamic trend score table based on the changing trends of these indicators. Furthermore, a logistic prediction model (DP-ACLF) was constructed by combining the sum of dynamic trend scores and baseline prognostic parameters. All prognostic scores were calculated based on the clinical data of patients at the third day, first week, and second week after admission, respectively, and were correlated with the 90-day prognosis by ROC analysis. Comparative analysis showed that the AUC value for DP-ACLF was higher than for other prognostic scores, including Child-Turcotte-Pugh, MELD, MELD-Na, CLIF-SOFA, CLIF-C ACLF, and COSSH-ACLF. The new scoring model, which combined baseline characteristics and dynamic changes in clinical indicators to predict the course of ACLF, showed a better prognostic ability than current scoring systems. Prospective studies are needed to validate these results.
慢加急性肝衰竭（ACLF）是一个动态的综合征，连续评估可以更准确地反映其预后。我们的目的是建立和验证一个新的评分系统，使用 ACLF 的基线和动态数据来预测短期预后。我们对来自中国三家不同医院的 ACLF 患者进行了回顾性队列分析。为了构建模型，我们分析了来自两家医院的 541 例患者的训练集。该模型在另一个中心的 130 例患者验证集中进行了评估。在训练集中，多变量 Cox 回归分析显示，年龄、WGO 类型、基础病因、总胆红素、肌酐、凝血酶原活动度和肝性脑病分期均为 ACLF 的独立预后因素。我们根据这些指标的变化趋势设计了一个动态趋势评分表。此外，通过结合动态趋势评分和基线预后参数，构建了一个逻辑预测模型（DP-ACLF）。所有预后评分均基于入院后第 3 天、第 1 周和第 2 周患者的临床数据计算，并通过 ROC 分析与 90 天预后相关。比较分析表明，DP-ACLF 的 AUC 值高于其他预后评分，包括 Child-Turcotte-Pugh、MELD、MELD-Na、CLIF-SOFA、CLIF-C ACLF 和 COSSH-ACLF。该新评分模型结合了基线特征和临床指标的动态变化来预测 ACLF 的病程，其预后能力优于目前的评分系统。需要前瞻性研究来验证这些结果。
