A dynamic prediction model for prognosis of acute-on-chronic liver failure based on the trend of clinical indicators

Zhenjun Yu,Tao Han,Shaojie Xin,Yingying Cao,Yu Zhang,Bing Zhu,Zhongping Duan,Manman Xu,Ming Kong,Shaoli You,Fangjiao Song,Yu Chen

doi:10.1038/s41598-021-81431-0

Abstract

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.

Highlights

Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately
Examples are the classic Child–Turcotte–Pugh (CTP) and Model of End-stage Liver Disease (MELD) s core[5,6], or the more recent Chronic Liver Failure Sequential Organ Failure Assessment (CLIF-SOFA) and Chronic Liver Failure Consortium Acute-on-Chronic Liver Failure (CLIFC ACLF) score proposed by the European Association for the Study of Chronic Liver F ailure[7,8]
The ACLF guidelines proposed by the Asian Pacific Association for the Study of the Liver (APASL)[10] recommend that ACLF patients should be assessed with the APASL ACLF Research Consortium (AARC)-ACLF score on admission and dynamically evaluated on the 4th and 7th day of treatment to predict progression

Summary

Introduction

Acute-on-chronic liver failure (ACLF) is a dynamic syndrome, and sequential assessments can reflect its prognosis more accurately. 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. Examples are the classic Child–Turcotte–Pugh (CTP) and Model of End-stage Liver Disease (MELD) s core[5,6], or the more recent Chronic Liver Failure Sequential Organ Failure Assessment (CLIF-SOFA) and Chronic Liver Failure Consortium Acute-on-Chronic Liver Failure (CLIFC ACLF) score proposed by the European Association for the Study of Chronic Liver F ailure[7,8]. The ACLF guidelines proposed by the Asian Pacific Association for the Study of the Liver (APASL)[10] recommend that ACLF patients should be assessed with the APASL ACLF Research Consortium (AARC)-ACLF score on admission and dynamically evaluated on the 4th and 7th day of treatment to predict progression. The cumulative mortality increases with rises in the AARC-ACLF score in the first w eek[10]

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