Clinical characteristics and prognosis of non-APAP drug-induced acute liver failure: a large multicenter cohort study

Author:

Han LinORCID,Huang AngORCID,Chen Jinjun,Teng Guangju,Sun Ying,Chang Binxia,Liu Hong-Li,Xu Manman,Lan Xiaoqin,Liang Qingsheng,Zhao Jun,Tian Hui,Chen Songhai,Zhu Yun,Xie Huan,Dang Tong,Wang Jing,Li Ning,Wang Xiaoxia,Chen Yu,Yang Yong-Feng,Ji DongORCID,Zou ZhengshengORCID

Abstract

Abstract Background There is growing recognition of natural history, complications, and outcomes of patients who develop non-acetaminophen (APAP) drug-induced acute liver failure (ALF). To clarify high-risk factors and develop a nomogram model to predict transplant-free survival (TFS) in patients with non-APAP drug-induced ALF. Methods Patients with non-APAP drug-induced ALF from 5 participating centers were retrospectively analyzed. The primary endpoint was 21-day TFS. Total sample size was 482 patients. Results Regarding causative agents, the most common implicated drugs were herbal and dietary supplements (HDS) (57.0%). The hepatocellular type (R ≥ 5) was the main liver injury pattern (69.0%). International normalized ratio, hepatic encephalopathy grades, the use of vasopressor, N-acetylcysteine, or artificial liver support system were associated with TFS and incorporated to construct a nomogram model (drug-induced acute liver failure-5, DIALF-5). The AUROC of DIALF-5 for 7-day, 21-day, 60-day, and 90-day TFS in the internal cohort were 0.886, 0.915, 0.920, and 0.912, respectively. Moreover, the AUROC of DIALF-5 for 21-day TFS had the highest AUROC, which was significantly higher than 0.725 of MELD and 0.519 of KCC (p < 0.05), numerically higher than 0.905 of ALFSG-PI but without statistical difference (p > 0.05). These results were successfully validated in the external cohort (147 patients). Conclusions Based on easily identifiable clinical data, the novel DIALF-5 model was developed to predict transplant-free survival in non-APAP drug-induced ALF, which was superior to KCC, MELD and had a similar prediction performance to ALFSG-PI but is more convenient, which can directly calculate TFS at multiple time points.

Funder

302 Hospital Foundation

National Natural Science Foundation of China

Beijing Nova Program

Capital Characteristic Clinic Project by Beijing Municipal Science and Technology Commission

Publisher

Springer Science and Business Media LLC

Subject

Hepatology

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