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Impact of Liver Injury on the Severity of COVID-19: a Systematic Review with Meta-analysis

Overview
Specialty Gastroenterology
Date 2020 Dec 3
PMID 33267597
Citations 8
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Abstract

Background And Aims: SARS-CoV-2 is mainly a respiratory virus that has relevant systemic effects. We assessed the impact of baseline liver function (aspartate aminotransferase [AST], alanine aminotransferase [ALT], bilirubin) on COVID-19-related outcomes, including mortality, intensive care unit (ICU) admissions, and non-fatal severe complications.

Methods: after a systematic review of the relevant studies the odds ratio (OR), mean difference, sensitivity, specificity, and both positive and negative likelihood ratios were calculated for the prediction of relevant COVID-19 outcomes by performing a meta-analysis using fixed and random effects models. A Fagan nomogram was used to assess clinical usefulness. Heterogeneity was explored by sensitivity analysis and univariate meta-regression.

Results: twenty-six studies were included (22 studies and 5,271 patients for AST, 20 studies and 5,440 subjects for ALT, and nine studies and 3,542 patients for bilirubin). The outcomes assessed by these studies were: survival (n = 8), ICU admission (n = 4), and non-fatal severe complications (n = 16). AST > upper limit of normal (ULN) (OR: 3.10 [95 % CI, 2.61-3.68]), ALT > ULN (OR: 2.15 [95 % CI, 1.43-3.23]), and bilirubin > ULN (OR: 2.78 [95 % CI, 1.88-4.13]) were associated with an increased prevalence of severe complications with a specificity of 78 %, 77 %, and 94 %, respectively. The mean difference between mild and severe COVID-19 was 10.7 U/l (95 % CI, 5.8-15.6) for AST, 8 U/l (95 % CI, 1.0-15) for ALT, and 0.3 mg/dl (95 % CI, 0.16-0.45) for bilirubin.

Conclusions: patients showing liver injury had a significantly higher risk of developing severe COVID-19 as compared to those with normal liver function tests at admission. We should include the assessment of AST, ALT, and total bilirubin (TB) routinely in the workup of patients affected by SARS-CoV-2 in order to predict those at risk of developing COVID-19-related outcomes.

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