Socio-Demographic Profile and Hiv and Hepatitis C Prevalence Among Persons Who Died of a Drug Overdose
Bibliographic record
Abstract
To describe the sociodemographic characteristics and HIV and Hepatitis C prevalence among persons who died of a drug overdose in the Vancouver metropolis health region in 1998. Methods: A retrospective review was conducted on all overdose death files in the Vancouver/Richmond health region reported to the Office of the Chief Coroner. The files included, autopsy, toxicology, virology, and coroner reports. External linkages were done to determine the proportion of individuals on antiretro-viral treatment. Contingency analyses were conducted to determine factors associated with Hepatitis C and HIV seropositivity. Results: Data on a total of 199 deaths were obtained from the coroner's office. Of these 37 (18.6%) were female and 162 (81.4%) were male. A total of 25 (12.6%) deaths were among persons of First Nations descent and 134 (73.6%) were among chronic drug users. The median age at death was 38 years (Interquartile range [IQR]: 32–45 years). The drug most commonly responsible for overdose was heroin [89 (47.3%) deaths]. A total of 91 (45.7%) deaths were tested for HIV and 95 (47.7%) deaths were tested for HCV. Of those deaths, 28 (29.8%) were HIV-positive and 78(78.0%) were HCV-positive. Conclusion: Our analysis suggests that those dying of illicit drug overdose in Vancouver during 1998, are largely comprised of older, male, chronic injection drug users. Rates of HIV and HCV positivity are very high in this group.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".