Low alanine aminotransferase cut-off for predicting liver outcomes; A nationwide population-based longitudinal cohort study

Jin Hwa Park, Jun Choi, Dae Won Jun, Sung Won Han, Yee Hui Yeo, Mindie H. Nguyen

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Background and aim: Recent practice guidelines suggest healthy normal alanine aminotransferase (ALT) levels should be less than 30 U/L for males and 19 U/L for females. We tried to validate the prediction power of the “low cut off” for liver related outcomes in the general population. Methods: A total of 426,013 subjects were followed up for 10 years using the National Health Screening Cohort database. Prediction ability of long term mortality and liver related outcomes between conventional (<40 U/L in men and women) and low (<30 U/L in men and <19 U/L in women) ALT cut-off values were compared. Results: Both conventional and low ALT cut-offs predicted liver related unfavorable outcomes in Kaplan-Meier analysis. Following adjustment for age, body mass index, smoking, exercise, alcohol consumption, fasting blood glucose, and cholesterol via multivariate Cox regression, abnormal ALT using new ‘low ALT cut off’ was a significant independent predictor for liver-related mortality, HCC, and decompensated liver events. When the low cut-off criteria were added to the prediction model, the ability to predetect liverrelated hard outcomes significantly increased in both men and women (p-values < 0.0001). The Cindex values for predicting liver-related adverse events were the same in both ALT cut-offs, after adjusting confounding factors (C index value: 0.73~0.88). Conclusions: New low ALT cut-off showed good prediction power for liver related unfavorable outcomes.

Original languageEnglish
Article number1445
JournalJournal of Clinical Medicine
Volume8
Issue number9
DOIs
Publication statusPublished - 2019 Sep

Keywords

  • Alanine aminotransferase
  • Liver function tests
  • Mortality
  • Upper limit of normal

ASJC Scopus subject areas

  • Medicine(all)

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