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Serum Gamma-Glutamyl Transferase as a risk biomarker in predicting cardiovascular disease among diabetics: A cross-sectional descriptive study in Ghana
Christian Obirikorang, Emmanuel Acheampong*, Samuel Amoah, Daniel Gyamfi,Emmanuel Toboh, Enoch Odame, Bright Amankwaa & Emmanuella Nsenbah BatuAim: This study evaluated the use of serum Gamma-Glutamyl Transferase (GGT) as a risk biomarker in the development of cardiovascular diseases among Type 2 Diabetes Mellitus (T2DM) individuals. Method: This was a cross-sectional study one conducted among 185 diabetics at Effia-Nkwanta Regional Hospital. Questionnaires were administered regarding socio-demographic characteristics and exclusion of individuals with confounding conditions. Measurement of anthropometric indices, blood sample collection and estimation serum GGT and lipid profile was done for qualified participants. Data was entered and analysed using Grpahpad Prism version 6. Results: A total of 185 participants were enrolled in the study. The mean age of the participants was 57.9 ± 9.9 years with majority of them between 50- 60 years (36%). There were more females (77%) than males (23%). A significant difference in GGT levels was observed for duration of diabetes among the participants (p=0.0286). Indicators of central obesity were higher as stratified by the indices, Weight-to Height Ratio (WHtR) (81%), and Weight-to-Hip (WHR) (75%). Positive association between GGT levels and body mass index (BMI), waist circumference (WC), WHR, Body Adiposity (BAI), coronary risk (CR), conicity (CI), total cholesterol (TC), Triglyceride, very low density lipoprotein (VLDL) and Glucose concentrations were observed. Total cholesterol (aOR=2.35, p<0.0001), TG (aOR=3.01, p=0.004), and LDL-C (aOR=2.05, p<0.001) were significant associated with increased risk of developing CVD, however, significantly reduced risk was observed for HDL-C after controlling for cofounders. Receiver operating characteristics (ROC) curve analysis of GGT in predicting its accuracy in diagnosing risk of coronary events showed that area under curve AUC was 75.81% for a 37.90U/L serum GGT cut-off value with 60% sensitivity and 90% specificity. Conclusion: GGT demonstrated a high accuracy, good sensitivity and a high specificity in predicting coronary risk among the participants, together with showing good relationship with established risk markers.