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Association of Serum Gamma-Glutamyltransferase and Premature Coronary Artery Disease Publisher



Sheikh M1 ; Tajdini M1 ; Shafiee A1, 2 ; Sotoudeh Anvari M1 ; Jalali A1 ; Poorhosseini H1 ; Amirzadegan A1
Authors
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Authors Affiliations
  1. 1. Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Community Medicine, Faculty of Medicine, Shahid Beheshti university of Medical sciences, Tehran, Iran

Source: Netherlands Heart Journal Published:2017


Abstract

Background Serum gamma-glutamyltransferase (GGT) has been introduced as a predictive factor for cardiovascular disease. In this study, we investigated the association of serum GGT and premature coronary artery disease (CAD) in candidates for coronary angiography. Methods In this cross-sectional study, we enrolled male subjects aged <45 years and female subjects <55 years who were candidates for elective coronary angiography due to typical chest pain or a positive non-invasive test. Baseline characteristics were recorded for all the participants and serum levels of blood glucose, lipid profile and GGT were measured. Patients were divided into CAD and non-CAD groups based on angiography for further comparisons. Results From a total of 367 patients (age 45.1 ± 6.1 years, 161 males [43.9%]), 176 (47.9%) patients had premature CAD. A high level of GGT was significantly associated with the presence of CAD (p < 0.001). A 10-unit increase in GGT could strongly predict the presence of premature coronary artery disease (OR: 13.34, 95% CI: 7.19–24.78; p < 0.001) after adjustment for confounders. The area under the receiver operating characteristic curve for GGT was 80.9% (range 76.5–85.3) and the sensitivity and specificity of GGT at a cut-point of 22.5 IU/l was 80.1% and 70.2%, respectively. Diagnostic accuracy of GGT was 74.9%. The positive predictive value and negative predictive value for GGT was 71.3 and 79.3, respectively. Conclusion We observed that GGT levels in patients with typical chest pain or positive non-invasive tests could predict the presence of premature CAD in young patients. © The Author(s) 2017.