HIV incidence among men who have sex with men in Beijing: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: (1) To assess the HIV incidence rate among men who have sex with men (MSM) in a large cohort study in Beijing, China and (2) to identify sociodemographic and behavioural risk factors of HIV seroconversion among MSM in Beijing, China. DESIGN: A prospective cohort study. SETTING: Baseline and follow-up visits were conducted among MSM in Beijing, China. PARTICIPANTS: A cohort of 797 HIV-seronegative MSM was recruited from August to December 2009, with follow-up occurring after 6 and 12 months. PRIMARY AND SECONDARY OUTCOME MEASURES: At baseline and follow-up visits, participants reported sociodemographic and sexual behaviour information, and were tested for HIV, herpes simplex virus-2 (HSV-2) and syphilis with whole blood specimens. Cox regression analysis was used to identify factors associated with HIV seroconversion. RESULTS: Most study participants (86.8%) were retained by the 12-month follow-up. The HIV, HSV-2 and syphilis incidence rates were 8.09 (95% CI 6.92 to 9.26), 5.92 (95% CI 5.44 to 6.40) and 8.06 (95% CI 7.56 to 8.56) cases per 100 person-years, respectively. HIV seroconversion was significantly associated with being <25 years old, having <12 years of education, having >1 male sex partner in the past 6 months, and being syphilis positive or HSV-2 positive. CONCLUSIONS: The HIV incidence among MSM in Beijing is serious. Interventions and treatment of sexually transmitted diseases (STD) should be combined with HIV control and prevention measures among MSM.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".