Suicide mortality among people accessing highly active antiretroviral therapy for HIV/AIDS in British Columbia: a retrospective analysis
Bibliographic record
Abstract
BACKGROUND: Suicide rates have been reported at elevated levels among people living with HIV/AIDS. We sought to characterize longitudinal suicide rates among people living with HIV/AIDS who are accessing free highly active antiretroviral treatment (HAART) in British Columbia and evaluate the sociodemographic, clinical and behavioural factors associated with suicide in this population. METHODS: Retrospective analysis of all patients in the HAART Observational Medical Evaluation and Research (HOMER) cohort who were 19 years of age and older who started treatment between August 1996 and June 2012. The primary outcome variable was death due to suicide. Data on deaths were obtained monthly through a linkage with the British Columbia Ministry of Health Vital Statistics Agency. Logistic regression and Cox proportional hazards models were used to identify factors independently associated with suicide mortality. RESULTS: A total of 993 deaths among 5229 patients accessing treatment were recorded, of which 82 (8.2%) were caused by suicide. Death from suicide peaked at 961 deaths per 100 000 person-years in 1998 and declined to 2.81 deaths per 100 000 person-years in 2010. Cox regression analysis showed that a history of injection drug use (adjusted hazard ratio [AHR] = 3.95, 95% confidence interval [CI] 1.99-7.86) or having no experience with an AIDS-defining illness (AHR = 4.45, 95% CI 1.62-12.25) were factors independently associated with suicide. This model showed a 51% reduction (AHR = 0.49, 95% CI 0.45-0.54) in the suicide rate per calendar year. INTERPRETATION: Deaths from suicide declined substantially over time, and factors other than progression of HIV disease, such as injection drug use, may be important targets for intervention to reduce suicide risk.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".