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Association of type 2 diabetes and hepatitis C virus infection in Pakistani population: A meta-analysis
Association of type 2 diabetes and hepatitis C virus infection in Pakistani population: A meta-analysis
- Source :
- Songklanakarin Journal of Science and Technology (SJST), Vol 44, Iss 5, Pp 1193-1200 (2022)
- Publication Year :
- 2022
- Publisher :
- Prince of Songkla University, 2022.
-
Abstract
- In Pakistan and other developing countries, the available data on the association of T2DM and HCV is limited. We therefore made an attempt to report the association of HCV and diabetes in Pakistani population through this meta-analysis. HCV and diabetes related studies were identified using various key words, from a number of databases including CINAHL, PubMed, Web of Science and Embase. Using RevMan5, the main outcome was regarded as type 2 diabetes associations with hepatitis c virus infection in Pakistan. Independent analyses were made for “HCV in diabetic patients” and “diabetes cases in hepatitis C virus patients”. Using random effect model, odds ratios were calculated with 95% CIs (dichotomous data). I2 statistics were used to calculate heterogeneity. From a total of 53 studies, we finally selected 6 studies for the meta-analysis. Using random effects model, hepatitis c virus patients in 3 studies (n = 1,902) demonstrated that HCV is a risk factor in developing diabetes, contrary to patients with no HCV infection (OR 0.01, 95% CI: 0.00-0.06, I2 = 0%; RR 0.01, 95% CI: 0.00-0.07, I2 = 0%). The remaining 3 studies (n = 13,710) had reported HCV infections in type 2 diabetic patients and patients with no diabetes. Similarly, our meta-analysis revealed higher prevalence of HCV infections in patients with type 2 diabetes (OR 0.7, 95% CI: 0.17-0.42, I2 = 32%; RR 0.30, 95% CI: 0.20-0.46, I2 = 32%) as compared to patients with no type 2 diabetes mellitus. Our meta-analysis demonstrates a significant link between HCV and T2DM. Further studies are recommended with adequate sample sizes.
Details
- Language :
- English
- ISSN :
- 01253395
- Volume :
- 44
- Issue :
- 5
- Database :
- Directory of Open Access Journals
- Journal :
- Songklanakarin Journal of Science and Technology (SJST)
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5478a9b6e274432c917f51e7a87ba2b6
- Document Type :
- article
- Full Text :
- https://doi.org/10.14456/sjst-psu.2022.155