PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 3, 2026Scientific Reports0 citationsOpen Access

Aspartate aminotransferase and model for end-stage liver disease reliably predict mortality in drug-induced liver injury

SWS. A. WeberIMIzabel MirchevaRBRochell Balakumar

Key Points

  • The study aims to identify predictive biomarkers for mortality in patients with drug-induced liver injury.
  • Analyzed data from 268 patients with drug-induced liver injury (DILI)
  • Used multivariate logistic regression to assess mortality predictors
  • Employed receiver operating characteristic curves to evaluate predictive performance of biomarkers
  • 10.4% of DILI patients had a fatal outcome, associated with higher transaminases and MELD scores
  • MELD score and AST were independently linked to poor outcomes, with a high c-statistic of 0.93
  • At a cutoff of ≥ 20, MELD score showed 88% sensitivity and 81% specificity for predicting mortality
  • Combining MELD with AST further improved predictive values with 44% positive and 96% negative predictive values

Abstract

Abstract Drug-induced liver injury (DILI) is associated with high mortality risk. However, no biomarker can reliably predict outcome. In order to identify baseline parameters that are associated with mortality the data of 268 prospectively collected DILI patients were analyzed. Multivariate logistic regression and receiver operating characteristic curves were used to identify the parameters being most predictive for a fatal outcome, as defined by orthotopic liver transplantation (OLT) or death. 10.4% of patients had a fatal outcome, which was associated with higher levels of transaminases, total bilirubin, INR and model for end-stage liver disease (MELD) scores (25 vs. 12, p < 0.001). Multivariate analysis revealed that only MELD and aspartate aminotransferase (AST) were independently associated with a poor outcome, the MELD score in particular had an extraordinarily high c-statistic of 0.93 (95% CI: 0.87–0.97). At a cut-off of ≥ 20, MELD could predict a fatal outcome with a sensitivity and specificity of 88% and 81%. The predictive performance of the MELD score could even be enhanced by combing it with AST elevation: At a cut-off of ≥ 20 and ≥ 29.6xULN, respectively, positive and negative predictive values of 44% and 96% were observed, which were higher than for any other baseline parameter.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Weber et al. (2026) studied this question.

synapsesocial.com/papers/69cf5dc55a333a821460bc58https://doi.org/10.1038/s41598-026-44893-8
Ask AI
Helpful
Bookmark
Share
View Full Paper