医学
内科学
肝性脑病
对乙酰氨基酚
列线图
药品
队列
临床终点
肝衰竭
肝病学
胃肠病学
临床试验
药理学
肝硬化
作者
Lin Han,Ang Huang,Jinjun Chen,Guangju Teng,Ying Sun,Binxia Chang,Hongli Liu,Manman Xu,Xiaoqin Lan,Qingsheng Liang,Jun Zhao,Hui Tian,Songhai Chen,Yun Zhu,Huan Xie,Tong Dang,Jing Wang,Ning Li,Xiaoxia Wang,Yú Chen
标识
DOI:10.1007/s12072-023-10541-w
摘要
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.
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