Title of article :
Forward stepwise logistic regression approach for determinants of hepatitis B & C among Hiv/Aids patients
Author/Authors :
Shahzad, Faryal Department of Information System - Dr. Hasan Murad School of Management - University of Management and Technology - Lahore, Pakistan , Obaid, Ahmed J Faculty of Computer Science and Mathematics - University of Kufa, Iraq , Kumar Rai, Bipin Department of Information Technology - ABES Institute of Technology - Ghaziabad, India , Ashraf, Mohsin Department of Computer Science - University of Central Punjab - Lahore, Pakistan , Shawkat Abdulbaqi, Azmi Department of Computer Science - College of Computer Science and Information Technology - University of Anbar - Ramadi, Iraq , Abid, Fazeel Department of Information System - Dr. Hasan Murad School of Management - University of Management and Technology - Lahore, Pakistan
Pages :
30
From page :
1367
To page :
1396
Abstract :
Hepatitis-related liver diseases are a leading cause of mortality and morbidity among people with HIV/ AIDS taking highly active antiretroviral therapy due to shared transmission routes. An estimated 2–4 million HIV-infected persons have chronic HBV co-infection, and 4–5 million have HCV co-infection worldwide and 14,000 new infections each day. The purpose of this study was to determine the prevalence and associated factors of HBV and HCV co-infection in HIV-positive patients. A cross-sectional study was conducted among 235 HIV/ AIDS patients seeking medical care at special clinics of two public hospitals in Lahore, Pakistan, from February 2018 to May 2018. A structured questionnaire was used to collect information on socio-demographic and clinical characteristics of HIV/ AIDS patients after obtaining their written informed consent. Chi-square, Fisher’s exact, and two independent sample t-tests as appropriate were used to find the association between risk factors and HBV, HCV co-infection with HIV. Further, a forward stepwise logistic regression model was used to evaluate the predictors of HBV and HCV co-infection with HIV. P-value ¡ 0.05 was regarded as significant. Of 235 HIV-positive patients, 9% were co-infected with HBV, 41 were HCV co-infected, and 6% had HBV-HCV triple infection. The highest prevalence of HBV (55%), HCV co-infection (70%), and HBV-HCV triple infection (85%) were observed in intravenous drug users followed by heterosexual routes. Male, hypertensive, alcohol consumers, and smokers were statistically significantly associated with HBV co-infection (P −value < 0.05). The factors include being male, never married, having < 1 year of HIV diagnosis, having < 200 CD4 counts (cell/mm3), presence of physical disability, having been infected through sexual routes, injecting drug user, alcohol consumer, and smoker were statistically significantly associated with HCV co-infection (P −value < 0.05). Whereas the factors; heterosexual transmission, intravenous drug use, alcohol use, smoking, and presence of physical disability were statistically significantly associated with HBV, HCV triple infection (P < 0.05). The adjusted odds ratio obtained by fitted logistic regression model showed that HIV transmission routes (both hetero and homo) and never married had lesser odds of HCV co-infection whereas the person with HIV transmission through intravenous drug use, who smoke and aged more than 30 years, had greater odds of HCV co-infection. Co-infection with hepatitis B and C virus is common among this studied sample of HIV-infected patients. The study’s finding reaffirms the need for routine baseline screening for this marker and as there is more chance of co-infection with these hepatitis viruses due to enhanced immunodeficiency by HIV and shared routes of transmission. It highlights the need for timely initiation of HAART. Furthermore, those found to be negative should be immunized with HBV and HCV vaccines to improve.
Keywords :
HBV , HCV , HIV , logistic regression
Journal title :
International Journal of Nonlinear Analysis and Applications
Serial Year :
2021
Record number :
2703070
Link To Document :
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