Intensive injection cocaine use as the primary risk factor in the Vancouver HIV-1 epidemic
Bibliographic record
Abstract
OBJECTIVES: The explosive and ongoing injecting drug use-related HIV-1 epidemic in Vancouver continues to receive international attention. This study was conducted to determine how patterns of cocaine use influence the risk of HIV infection. METHODS: The Vancouver Injection Drug Users Study is an open prospective cohort of injecting drug users that began in May 1996. At enrollment and at semi-annual follow-up visits an interviewer administers a detailed semi-structured questionnaire. Cox proportional hazards models were used to determine behavioral and drug use patterns reported in the 6 months prior to HIV seroconversion. RESULTS: One-hundred and nine incident HIV infections have been observed during a mean follow-up of 31 months, from 940 HIV-seronegative participants. During the 6 months prior to seroconversion, predictors of HIV infection were injecting cocaine use [adjusted hazards ratio (AHR), 3.72], incarceration (AHR, 2.74), unstable housing (AHR, 2.36), methadone maintenance treatment (AHR, 1.98), and Aboriginal ethnicity (AHR, 1.78). Injecting cocaine use was predictive of HIV infection in a dose-dependent fashion. Compared with infrequent cocaine users, participants who averaged more than three injections per day were seven times more likely to contract HIV. In addition, the time to HIV infection was accelerated among regular cocaine injectors independent of concurrent heroin use. CONCLUSIONS: Injecting cocaine use was a strong, dose-dependent predictor of HIV seroconversion in this poly-drug using population. Injection cocaine users remain particularly vulnerable to HIV infection and treatment options for cocaine dependency remain woefully inadequate.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".