Dynamics of overdose and non-overdose mortality among people living with HIV amidst the illicit drug toxicity crisis in British Columbia
Bibliographic record
Abstract
We sought to characterize overdose and non-overdose mortality among PLWH amidst the illicit drug toxicity crisis in British Columbia, Canada. A population-based analysis of PLWH (age ≥19) in British Columbia accessing healthcare from April 1996 to March 2017 was conducted using data from the Seek and Treat for Optimal Prevention of HIV/AIDS (STOP HIV/AIDS) cohort linkage. Underlying causes of deaths were stratified into overdose and non-overdose causes. We compared (bivariate analysis) health-related characteristics and prescription history between PLWH died of overdose and non-overdose causes between April 2009 and March 2017. Among 9,180 PLWH, we observed 962 deaths (142 [14.7%] overdoses; 820 [85.2%] other causes). Compared to those who died from other causes, those who died of overdose were significantly younger (median age [Q, Q3]: 46 years [42, 52] vs. 54 years [48, 63]); had an indication of chronic pain (35.9% vs. 27.1%) and hepatitis C virus (64.8% vs. 50.4%), but fewer experienced hospitalization in the year before death. PLWH who died were most likely to be prescribed with opioids (>50%) and least likely with opioid agonist therapy (<10%) in a year before death. These findings highlight the syndemic of substance use, HCV, and chronic pain, and how the crisis is unqiuely impacting females and younger people.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".