Ongoing impact of <scp>HIV</scp> infection on mortality among people who inject drugs despite free antiretroviral therapy
Bibliographic record
Abstract
AIMS: To determine the impact of HIV infection on mortality over time among people who inject drugs (PWID) in settings with free HIV/AIDS care. DESIGN AND SETTING: Prospective cohort study of PWID in Vancouver, Canada, recruited between May 1996 and December 2011. We ascertained morality rates and causes of death through a confidential linkage with the provincial vital statistics registry. PARTICIPANTS: A total of 2283 individuals were followed for a median of 60.9 months (interquartile range: 34.4-113.1), among whom 622 (27.2%) individuals were HIV-positive at baseline, and 179 (7.8%) seroconverted during follow-up. MEASUREMENTS: The primary and secondary outcomes of interests were all-cause mortality and cause of death, respectively. The main independent variable of interest was HIV serostatus (positive versus negative). We used Cox proportional hazards regression to determine factors associated with mortality, including socio-demographic variables, drug use behaviors and other risk behaviors. FINDINGS: During the study period, 491 (21.5%) individuals died. In multivariate analyses, HIV infection remained associated independently with all-cause mortality (adjusted hazard ratio = 3.15; 95% CI: 2.59-3.82). While all-cause mortality rates declined markedly during the study period (P < 0.001), the independent effect of HIV infection on mortality remained unchanged over time (P = 0.640). Among HIV-positive individuals, significant changes in causes of death from infectious and AIDS-related causes to non-AIDS-related etiologies were observed. CONCLUSIONS: HIV infection continues to have a persistent impact on mortality rates among people who inject drugs in settings with free HIV/AIDS care, although causes of death have shifted markedly from infectious and AIDS-related causes to non-AIDS-related etiologies.
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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 | 0.001 | 0.001 |
| 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".