Sexually transmitted and blood-borne infections by sex, methamphetamine use, and houselessness before, at, and after HIV diagnosis in Manitoba, Canada
Bibliographic record
Abstract
Objectives: Describe the proportion of people newly living with HIV with sexually transmitted and blood-borne infections (STBBIs) before, at, and after HIV diagnosis in Manitoba, Canada. Methods: A retrospective cohort study reviewed clinical charts of all 404 people ≥18 years old newly diagnosed with HIV in Manitoba, Canada between 2018 and 2021. Syphilis, hepatitis C and B, gonorrhea, and chlamydia infections before, at, and after HIV diagnosis were recorded and analyzed by sex at birth, injection drug use status, use of methamphetamines, and housing status. Results: A total of 53% of people were diagnosed with syphilis, 44.1% with gonorrhea, 42.8% with chlamydia, and 40.6% with hepatitis C at least once. Among females, 64.1% had at least one or more STBBIs diagnoses before HIV diagnosis compared with 44.8% of males. Over 70% of people experiencing houselessness had at least one STBBI diagnosis before their HIV diagnosis compared with 43.9% of people not houseless. Among people who used methamphetamines, 68.3% had one or more STBBIs before HIV diagnosis compared with 28.9% of people who do not use methamphetamines. In a multivariable analysis houselessness, methamphetamine use, and younger age were associated with increased risk of any STBBIs. Conclusions: In our Manitoba cohort of people living with HIV, disproportionately more females, people experiencing houselessness, and those who use methamphetamine were diagnosed with STBBIs. The proportion of new infections before HIV diagnoses highlights a missed opportunity to provide prevention modalities, including pre-exposure prophylaxis, and the proportion after HIV diagnosis emphasizes the importance of enhancing engagement, repeated testing, and educational strategies to ameliorate ongoing exposures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".