Development of a Predictive Model for Hepatitis B Virus (HBV) Status Using Gender and Serum Biomarkers
Year: 2025
Type: article
Study design: Observational Study
Abstract: Early screening for the Hepatitis B Virus (HBV) is crucial for effective management and treatment, especially in resource-limited areas like Enugu State, Nigeria. This study aims to develop and validate a predictive model for HBV status. By integrating several factors, this research seeks to improve diagnostic accuracy and contribute to more effective HBV management, particularly in resource-limited settings. The study is focused on the following gender and serum biomarkers: alpha glutathione S-transferase (α-GST), aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP) among patients at Enugu State University Teaching Hospital. Binary logistic regression was employed to analyze the predictive power of these variables. The results indicate that AST is a statistically significant predictor of HBV status. In contrast, gender, alpha GST, ALP, and ALT were not statistically significant predictors in the model.
Source: Precision Nanomedicine
DOI: 10.33218/001c.137474
Authors: Stanley Obinna Ezeadichie, Joy E. Ikekpeazu, Amechi Uchenna Katchy, Mima Wariso, Chioma Cordelia Ugwu, Osah Martins Onwuka
Institutions: Godfrey Okoye University, University of Nigeria
Language: English
Topic: Hepatitis B Virus Studies
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409914039