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. 2022 Sep;53(5):758-763.
doi: 10.12182/20220960203.

[Assessment Value of Short-Term Prognosis of Six Predictive Models for Patients with Acute-on-Chronic Liver Failure Treated with Artificial Liver Support System]

[Article in Chinese]
Yuan-Ji Ma  1 , Ling-Yao Du  1 , Lang Bai  1 , Hong Tang  1
Affiliations

[Assessment Value of Short-Term Prognosis of Six Predictive Models for Patients with Acute-on-Chronic Liver Failure Treated with Artificial Liver Support System]

[Article in Chinese]
Yuan-Ji Ma et al. Sichuan Da Xue Xue Bao Yi Xue Ban. 2022 Sep.

Abstract
in English, Chinese

Objective: To apply 6 predictive models on acute-on-chronic liver failure (ACLF) patients treated with artificial liver support system (ALSS), and to compare their assessment values for the short-term prognosis of patients.

Methods: A total of 258 ACLF patients who underwent ALSS therapy between January 2018 and December 2019 were selected from the ALSS clinical database established by West China Hospital, Sichuan University, and their clinical data and 90-day prognosis information were collected. Cox proportional hazards model was used to estimate the association between the six predictive models, including Chinese Group on the Study of Severe Hepatitis B-ACLF (COSSH ACLF), European Association for the Study of the Liver--Chronic Liver Failure-Consortium (CLIF-C) ACLF, CLIF-C Organ Failure (OF), Asian Pacific Association for the Study of the Liver (APASL) ACLF Research Consortium (AARC) ACLF, Model for End-Stage Liver Disease (MELD) and Simplified MELD (sMELD), and 90-day mortality, which included death or receiving liver transplantation. The area under the receiver operating characteristic (ROC) curve ( AUC), Harrell's C-index and Brier scores were calculated and compared to evaluate the predictive power.

Results: A total of 258 ACLF patients were enrolled. Of these patients, who had a mean age of (46.2±11.7) years old, 37 (14.3%) patients were female, 202 (78.3%) patients had a diagnosis of liver cirrhosis, and 107 (41.5%) patients died during the 90-day follow-up period. The six predictive models all yielded higher scores for patients who died than those for patients who survived (all P<0.001). The six predictive models were all independent risk factors for the short-term prognosis of ACLF patients treated with ALSS (all adjusted hazard ratio [HR]>1, all P<0.001). The AUC (0.806, 95% confidence interval [CI]: 0.753-0.853) and Harrell's C-index (0.772, 95% CI: 0.727-0.816) of COSSH ACLF were much higher than those of the five other predictive models (all AUCs<0.750, P<0.01; all Harrell's C-indices<0.750, P<0.001). The Brier score of COSSH ACLF was 0.18 (95% CI: 0.15-0.20). The 90-day mortality of patients defined as having low risk, moderate risk, and high risk according to the risk stratification of COSSH ACLF were 22.2%, 56.3%, and 90.2%, respectively.

Conclusion: The COSSH ACLF could more accurately predict short-term prognosis in ACLF patients who received ALSS therapy, and could facilitate clinical decision-making.

目的: 对接受人工肝治疗的慢加急性肝衰竭（ACLF）患者应用6种预测模型，比较它们对患者短期预后的评估价值。

方法: 自四川大学华西医院建立的人工肝治疗临床数据库中筛选2018年1月–2019年12月期间接受人工肝治疗的ACLF患者258例，收集临床资料和90 d预后信息。运用Cox比例风险模型估计6种预测模型（COSSH ACLF评分、CLIF-C ACLF评分、CLIF-C OF评分、AARC ACLF评分、MELD评分和sMELD评分）与患者90 d病死（含死亡或接受肝移植）的关系。以受试者工作特征（ROC）曲线下面积（AUC）、Harrell's C指数和Brier分数等评价模型预测效能。

结果: 共纳入ACLF患者258例，年龄（46.2±11.7）岁，女性37例（14.3%），肝硬化202例（78.3%），随访90 d时病死107例（41.5%），存活151例（58.5%）。病死患者的6种预测模型评分均高于存活患者（全部P<0.001）。6种预测模型均是人工肝治疗的ACLF患者90 d病死的独立危险因素（校正的风险比>1，P<0.001）。COSSH ACLF评分的AUC〔0.806，95%可信区间（CI）：0.753～0.853〕和Harrell's C指数（0.772，95%CI：0.727～0.816）均高于其余5种预测模型的AUC（5种AUC均<0.750，P<0.01）和Harrell's C指数（5种Harrell's C指数均<0.750，P≤0.001）。COSSH ACLF评分的Brier分数为0.18（95%CI：0.15～0.20）。基于COSSH ACLF评分风险分层的低危、中危和高危组患者的90 d病死率分别为22.2%、56.3%和90.2%。

结论: COSSH ACLF评分可更准确地预测人工肝治疗的ACLF患者的短期预后，有助于临床决策。

Keywords: Acute-on-chronic liver failure; Artificial liver support system therapy; Predictive model; Prognosis.

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Conflict of interest statement

利益冲突 所有作者均声明不存在利益冲突

Figures

图 1
图 1
Receiver operating characteristic curves of predictive models for 90-day mortality of ACLF patients 预测模型预测慢加急性肝衰竭患者90 d病死的ROC曲线
图 2
图 2
Calibrating COSSH ACLF score for predicting 90-day mortality of ACLF patients COSSH ACLF评分预测慢加急性肝衰竭患者90 d病死的校准度
图 3
图 3
Survival curves of ACLF patients based on risk stratification of COSSH ACLF score 基于COSSH ACLF评分风险分层的慢加急性肝衰竭患者的生存曲线
See this image and copyright information in PMC

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