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• W2910132592 abstract "Gamma glutamyl transferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) are commonly used liver function markers. We performed a dose-response meta-analysis to investigate the association between liver enzymes and cardiovascular disease (CVD) mortality in prospective cohort studies. We conducted a systematic search up to April 2018 in Medline/PubMed, Scopus, Cochrane, and Embase databases. Combined hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a random-effects model as described by DerSimonian and Laird. Dose-response analysis was also carried out. Twenty-three studies with 1 067 922 participants reported association between GGT and CVD mortality and were included in our analysis. Pooled results showed a significant association between GGT and risk of CVD mortality (HR: 1.62; 95% CI: 1.47-1.78, P=0.001, P-heterogeneity=0.001) and it was HR: 0.87; 95% CI: 0.73-1.07; P=0.221, P-heterogeneity=0.028, for ALT. There was a direct association between baseline levels of ALP and AST/ALT ratio with CVD mortality (HR: 1.45; 95% CI: 1.11-1.89; P=0.005, P-heterogeneity=0.026, and HR: 2.20; 95% CI: 1.60-3.04; P=0.001, P-heterogeneity=0.540, respectively). Pooled results did not show any significant association between AST and the risk of CVD mortality (HR: 1.20; 95% CI: 0.83-1.73; P=0.313, P-heterogeneity=0.024). Moreover, there was a significant nonlinear association between GGT and ALP levels and the risk of CVD mortality (P=0.008 and 0.016, respectively). Our dose-response meta-analysis revealed a direct relationship between GGT and ALP levels and the risk of CVD mortality. High levels of GGT, ALP and AST/ALT were associated with an increased CVD mortality rate." @default.
• W2910132592 created "2019-01-25" @default.
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• W2910132592 date "2019-05-01" @default.
• W2910132592 modified "2023-10-18" @default.
• W2910132592 title "Elevated liver enzymes and cardiovascular mortality: a systematic review and dose–response meta-analysis of more than one million participants" @default.
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• W2910132592 doi "https://doi.org/10.1097/meg.0000000000001353" @default.
• W2910132592 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30614883" @default.
• W2910132592 hasPublicationYear "2019" @default.
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