Literature DB >> 25555268

Circulating gamma glutamyltransferase and prediction of cardiovascular disease.

Setor K Kunutsor1, Stephan J L Bakker2, Jenny E Kootstra-Ros3, Ronald T Gansevoort4, Robin P F Dullaart5.   

Abstract

BACKGROUND: The value of measuring levels of gamma glutamyltransferase (GGT) for the prediction of first cardiovascular events is uncertain. We aimed to determine whether adding information on GGT values to conventional cardiovascular risk factors is associated with improvement in prediction of CVD risk.
METHODS: Circulating GGT levels were measured at baseline in the PREVEND prospective cohort study. We included 6969 participants without a prevalent history of CVD. Hazard ratios (95% confidence intervals [CI]) and measures of risk discrimination for CVD outcomes (e.g., C-index) and reclassification (i.e., net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5%to <7.5%), and high (≥7.5%) risk were assessed.
RESULTS: During a median follow-up of 10.5 years, 735 incident CVD events were recorded. Loge GGT was linearly associated with CVD risk. In analyses adjusted for conventional plus several potential cardiovascular risk factors, the hazard ratio (95% CI) for CVD per 1 standard deviation increase in loge GGT was 1.24 (1.12-1.37; P < 0.001), which was attenuated somewhat after further adjustment for C-reactive protein 1.18 (1.06-1.30; P = 0.002). Addition of information on GGT to a CVD risk prediction model containing conventional risk factors was associated with a C-index change of 0.0003 (-0.0015 to 0.0022; P = 0.73) and a net reclassification improvement of 1.19% (-0.11-2.49%; P = 0.07) for the categories of predicted 10-year CVD risk.
CONCLUSIONS: In the general population, adding GGT to conventional CVD risk factors is unlikely to improve prediction of first-ever cardiovascular events.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Cardiovascular disease; Gamma glutamyltransferase; Risk factor; Risk prediction

Mesh:

Substances:

Year:  2014        PMID: 25555268     DOI: 10.1016/j.atherosclerosis.2014.12.045

Source DB:  PubMed          Journal:  Atherosclerosis        ISSN: 0021-9150            Impact factor:   5.162


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