Incidence of acute hepatitis C virus infection among men who have sex with men with and without HIV infection: a systematic review
Bibliographic record
Abstract
BACKGROUND: A recent increase in reports of acute hepatitis C virus infection (HCV) in HIV-infected and HIV-uninfected men who have sex with men (MSM), with the sole risk factor being sexual exposure, has led to routine screening and targeted prevention requests for this population; current evidence for this necessity is unclear. OBJECTIVE: A systematic review was conducted to assess the incidence of HCV infection among studies conducted in HIV-positive and/or HIV-negative MSM to explore the implications for routine HCV screening. DATA SOURCES: The MEDLINE, EMBASE and BIOSYS databases were searched for the period January 2000 to May 2012, yielding 21 studies. Six conferences were hand-searched for the same period yielding four abstracts. STUDY SELECTION: Only studies in English presenting incidence rates of HCV and specifying HIV status were included. DATA ABSTRACTION: Data were abstracted by two authors using predefined data fields. The STROBE checklist was used to assess study quality. DATA SYNTHESIS: Data were divided into HIV-negative MSM and HIV-positive MSM subgroups, and HCV incidence density measurements were pooled. Using a DerSimonian-Laird random effects model, pooled incidence was 1.48/1000 person-years (95% CI 0.75 to 2.21) for the HIV-negative MSM subgroup. The HIV-positive MSM subgroup was at 4.1 times higher risk of acquiring HCV at 6.08/1000 person-years (95% CI 5.18 to 6.99). Studies directly comparing subgroups estimated a pooled risk difference of 3.45/1000 person-years (95% CI 1.63 to 5.27). CONCLUSION: HIV-positive MSM were at higher risk for acute HCV infection than HIV-negative MSM, substantiating the need for routine screening initiatives. Insufficient evidence exists to warrant routine screening of HIV-negative MSM, except on a case-by-case basis, such as high-risk sexual behaviour.
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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 | 0.008 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".