Role of precipitants in transition of acute decompensation to acute-on-chronic liver failure in patients with HBV-related cirrhosis

Tongyu Wang, Wenting Tan, Xianbo Wang, Xin Zheng, Yan Huang, Beiling Li, Zhongji Meng, Yanhang Gao, Zhiping Qian, Feng Liu, Xiaobo Lu, Huadong Yan, Yubao Zheng, Weituo Zhang, Shan Yin, Wenyi Gu, Yan Zhang, Fuchen Dong, Jianyi Wei, Guohong Deng, Xiaomei Xiang, Yi Zhou, Yixin Hou, Qun Zhang, Shue Xiong, Jing Liu, Liyuan Long, Ruochan Chen, Jinjun Chen, Xiuhua Jiang, Sen Luo, Yuanyuan Chen, Chang Jiang, Jinming Zhao, Liujuan Ji, Xue Mei, Jing Li, Tao Li, Rongjiong Zheng, Xinyi Zhou, Haotang Ren, Yu Shi, Hai Li, Chinese (Acute on) Chronic Liver Failure Consortium (Ch-CLIF.C), Tongyu Wang, Wenting Tan, Xianbo Wang, Xin Zheng, Yan Huang, Beiling Li, Zhongji Meng, Yanhang Gao, Zhiping Qian, Feng Liu, Xiaobo Lu, Huadong Yan, Yubao Zheng, Weituo Zhang, Shan Yin, Wenyi Gu, Yan Zhang, Fuchen Dong, Jianyi Wei, Guohong Deng, Xiaomei Xiang, Yi Zhou, Yixin Hou, Qun Zhang, Shue Xiong, Jing Liu, Liyuan Long, Ruochan Chen, Jinjun Chen, Xiuhua Jiang, Sen Luo, Yuanyuan Chen, Chang Jiang, Jinming Zhao, Liujuan Ji, Xue Mei, Jing Li, Tao Li, Rongjiong Zheng, Xinyi Zhou, Haotang Ren, Yu Shi, Hai Li, Chinese (Acute on) Chronic Liver Failure Consortium (Ch-CLIF.C)

Abstract

Background & aims: Pre-acute-on-chronic liver failure (ACLF) is a distinct intermediate stage between acute decompensation (AD) and ACLF. However, identifying patients with pre-ACLF and predicting progression from AD to ACLF is difficult. This study aimed to identify pre-ACLF within 28 days, and to develop and validate a prediction model for ACLF in patients with HBV-related decompensated cirrhosis.

Methods: In total, 1,736 patients with HBV-related cirrhosis and AD were enrolled from 2 large-scale, multicenter, prospective cohorts. ACLF occurrence within 28 days, readmission, and 3-month and 1-year outcomes were collected.

Results: Among 970 patients with AD without ACLF in the derivation cohort, the 94 (9.6%) patients with pre-ACLF had the highest 3-month and 1-year LT-free mortality (61.6% and 70.9%, respectively), which was comparable to those with ACLF at enrollment (57.1% and 67.1%); the 251 (25.9%) patients with unstable decompensated cirrhosis had mortality rates of 22.4% and 32.1%, respectively; while the 507 (57.9%) patients with stable decompensated cirrhosis had the best outcomes (1-year mortality rate of 2.6%). Through Cox proportional hazard regression, specific precipitants, including hepatitis B flare with HBV reactivation, spontaneous hepatitis B flare with high viral load, superimposed infection on HBV, and bacterial infection, were identified to be significantly associated with ACLF occurrence in the derivation cohort. A model that incorporated precipitants, indicators of systemic inflammation and organ injuries reached a high C-index of 0.90 and 0.86 in derivation and validation cohorts, respectively. The optimal cut-off value (0.22) differentiated high-risk and low-risk patients, with a negative predictive value of 0.95.

Conclusions: Three distinct clinical courses of patients with AD are validated in the HBV-etiology population. The precipitants significantly impact on AD-ACLF transition. A model developed by the precipitant-systemic inflammation-organ injury framework could be a useful tool for predicting ACLF occurrence.

Clinical trial number: NCT02457637 and NCT03641872.

Lay summary: It was previously shown that patients with decompensated cirrhosis could be stratified into 3 groups based on their short-term clinical prognoses. Herein, we showed that this stratification applies to patients who develop cirrhosis as a result of hepatitis B virus infection. We also developed a precipitant-based model (i.e. a model that incorporated information about the exact cause of decompensation) that could predict the likelihood of these patients developing a very severe liver disease called acute-on-chronic liver failure (or ACLF).

Keywords: ACLF, acute-on-chronic liver failure; AD, acute decompensation; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CATCH-LIFE study, Chinese AcuTe-On-Chronic LIver FailurE Study; CLIF, Chronic Liver Failure; CLIF-C AD, CLIF consortium acute decompensation score; CRP, C-reactive protein; EASL, European Association for the Study of the Liver; HR, hazard ratio; INR, international normalized ratio; LT, liver transplantation; MELD, model for end-stage liver disease; NL, neutrophil-lymphocyte ratio; NPV, negative predictive value; OFs, organ failures; PPV, positive predictive value; PVT, portal vein thrombosis; SDC, stable decompensated cirrhosis; UDC, unstable decompensated cirrhosis; WBC, white blood cell; acute-on-chronic liver failure; acutely decompensated cirrhosis; hepatitis B virus; iMELD, integrated MELD; precipitants; prediction model.

Conflict of interest statement

The authors declare no conflicts of interest that pertain to this work. Please refer to the accompanying ICMJE disclosure forms for further details.

© 2022 The Author(s).

Figures

Graphical abstract
Graphical abstract
Fig. 1
Fig. 1
Patient screening flow chart according to diagnosis of ACLF and 3-month readmission in the derivation and validation cohort. ACLF, acute-on-chronic liver failure; LT, liver transplantation.
Fig. 2
Fig. 2
The discrimination and calibration plot of the ACLF development prediction model. (A) ROC curve (solid line) and AUC (95%CI) (shadow area) of the model predicting ACLF development in derivation cohort; (B) ROC curve and AUC (95% CI) of the model predicting ACLF development in the validation cohort; (C) Calibration plot in the derivation cohort; (D) Calibration plot in the validation cohort. ACLF, acute-on-chronic liver failure.
Fig. 3
Fig. 3
Predictive ability comparison between ACLF development predicting model and other prognostic scores. (A) The ROC curves of the new model and CLIF-C AD, iMELD, MELD-sodium, and Child-Pugh score comparison in the derivation cohort. (B) The ROC curves of the new model and CLIF-C AD, iMELD, MELD-sodium, and Child-Pugh score comparison in the validation cohort. ACLF, acute-on-chronic liver failure; AD, acute decompensation; CLIF-C AD, CLIF consortium acute decompensation score; iMELD, integrated MELD; MELD, model for end-stage liver disease.
Fig. 4
Fig. 4
Differentiating patients at a high risk and low risk of ACLF development with the selected cut-off in the validation cohort. The cut-off value of 0.22 covers 12% of patients as the high-risk group and 88% as the low-risk group, with a sensitivity of 0.5 and specificity of 0.92. The risks of ACLF development in the high- and low-risk groups were 39.6% and 5.3%, respectively. ACLF, acute-on-chronic liver failure.

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