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Background: Opioid-dependent patients undergoing opioid substitution therapy (OST) consume alcohol in a hazardous pattern which adversely affects their treatment outcome. This study aims to measure alcohol biomarkers to screen for secondary alcohol use in OST patients. Methods: A pilot study was planned to measure alcohol biomarkers (AST, ALT, GGT, and CDT) to assess alcohol use in OST patients from three community clinics. The biomarkers were categorized based on the reported frequency of alcohol use. The association of the biomarkers with the frequency of alcohol consumption was determined using the post hoc (Mann-Whitney) test. Results: Forty-five patients with a mean (SD) age of 37.04 (10.7) years were included in the study. Alcohol intake was reported in daily, weekly, and monthly patterns by 22, 63, and 16% of the patients, respectively. High levels of ALT, GGT, and CDT were measured in patients with daily use of alcohol. Serum CDT levels significantly differentiate daily and weekly use from monthly consumption of alcohol. Conclusions: Alcohol biomarkers significantly predict the pattern of alcohol use among OST patients. These results can be prudent in low-resource community clinics to improve the overall outcomes of OST in India.
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BACKGROUND: Alcohol dependence often cannot be diagnosed based on self-report alone. Various biochemical and haematological parameters have been used to screen alcohol use disorders. AIM: To develop discriminant equations based on lipid and liver measures independently for identifying alcohol dependent and non-dependent subjects. SETTINGS AND DESIGN: Case control study in a tertiary care hospital. METHODS AND MATERIALS: One hundred subjects fulfilling the criteria of alcohol dependence and seventy healthy controls were included. The socio-demographic details, caloric intake, height, weight and blood pressure were recorded. Samples were analysed for various lipid measures as well as liver function. STATISTICAL ANALYSIS USED: Diagnostic values such as sensitivity, specificity, positive predictive value (PV+), negative predictive value (PV-) and discriminant analysis. RESULTS: Using discriminant analysis, two equations were constructed based on liver and lipid measures independently. 84.7% of the subjects on the basis of total cholesterol (TC), apolipoprotein B (ApoB) and low density lipoprotein/high density lipoprotein-cholesterol (LDL/HDL-c and 89.1% on the basis of aspartate amino transferase (AST) and gamma glutamyl transferase (GGT) were correctly classified into their respective groups. CONCLUSIONS: This study demonstrates the ability of TC, ApoB and LDL/HDL-c (among lipid measures) and AST and GGT (among liver measures) in discriminating alcohol dependents from non-dependent subjects.