Prevalence of hepatitis B and C infections among HIV‐positive men who have sex with men: A systematic review and meta‐analysis
Bibliographic record
Abstract
Background: Human immunodeficiency virus (HIV) infection is highly prevalent and often coexists with other infectious diseases, especially Hepatitis B virus (HBV) and Hepatitis C virus (HCV). Men who have sex with men (MSM) represent a vulnerable population in terms of HIV infection. We aimed to determine the prevalence of HCV, HBV among HIV-infected MSM. Methods: along with prediction interval for heterogeneity. Subgroup analysis based on continent and meta-regression for study size, average age and year of publication were used to explore heterogeneity. Modified Newcastle-Ottawa Scale was used to evaluate the quality of studies according to the protocol (PROSPERO: CRD42023428764). Results: Fifty-six of 5948 studies are included. In 53 studies with 3,07,589 participants, a pooled prevalence of 7% (95% confidence interval [CI]: 5-10) was found for HCV among MSM PLHIV, while a 9% (95% CI: 4-18) prevalence was found for HBV infection from five studies which included 5641 MSM PLHIV. Asia reported the lowest pooled prevalence at 5.84% (95% CI: 2.98-11.13) for HCV while Europe reported the highest pooled prevalence at 7.76% (95% CI: 4.35-13.45). Baujat plot and influence diagnostic identified contributors to influence and between-study heterogeneity. Sensitivity analyses omitting these studies result in considerably more precise estimates. Another sensitivity analysis as leave-one-out meta-analysis did not change any pooled estimate significantly. Conclusion: There is a significant burden of HCV and HBV among MSM PLHIV worldwide, with varying prevalence rates. Future studies should focus on these multimorbidity clusters and investigate factors influencing disease burden, long-term outcomes, optimal testing strategies, and tailored interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.041 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".