High HIV incidence among MSM prescribed postexposure prophylaxis, 2000–2009
Bibliographic record
Abstract
OBJECTIVE: To determine (trends in) HIV incidence among MSM\ who have recently had postexposure prophylaxis (PEP) prescribed in Amsterdam, compared with MSM participating in the Amsterdam Cohort Studies (ACS). DESIGN AND METHODS: We used data from MSM who were prescribed PEP in Amsterdam between 2000 and 2009, who were HIV-negative at the time of PEP prescription and had follow-up HIV testing 3 and/or 6 months after PEP prescription (n = 395). For comparison, cohort data from MSM participating in the ACS in the same period were used (n = 782). Poisson log-linear regression analyses were performed to model trends in HIV incidence and identify differences in HIV incidence between both cohorts at different time points. RESULTS: Between 2000 and 2009, among MSM who were prescribed PEP, an overall HIV incidence of 6.4 [95% confidence interval (CI) 3.4-11.2] per 100 person-years was found, compared with an HIV incidence of 1.6 (95% CI 1.3-2.1) per 100 person-years among MSM participating in the ACS (P < 0.01). In both cohorts, an increasing trend in HIV incidence over time was observed [incidence rate ratio (IRR(per calendar year)) 1.3 (95% CI 0.9-1.7) and 1.1 (95% CI 1.0-1.2) among MSM prescribed PEP and MSM of the ACS, respectively]. The difference in HIV incidence between both cohorts was most evident in more recent years [IRR(PEP versus ACS in 2009) 4.8 (95% CI 2.0-11.5)]. CONCLUSION: Particularly in more recent years, MSM recently prescribed PEP had a higher HIV incidence compared with MSM participating in the ACS, indicating ongoing sexual risk behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".