Impact of HAART and injection drug use on life expectancy of two HIV-positive cohorts in British Columbia
Bibliographic record
Abstract
BACKGROUND: The introduction of HAART has led to consistent improvements in survival among HIV-infected individuals. However, there is evidence that not all populations have benefited equally from HAART and that mortality rates are higher in HIV-infected injection drug users than in non-users. OBJECTIVE: To model life expectancies for HIV-positive individuals subdivided according to history of injection drug use and treatment with HAART. DESIGN: Population-based study of HIV-positive persons in British Columbia's HIV/AIDS treatment program. METHODS: The primary outcome measures in this study were life expectancy at exact age 20 and potential years of life lost. RESULTS: The highest life expectancy (38.9 years) and lowest potential years of life lost were measured for individuals taking HAART and without a history of injection drug use. The lowest life expectancy (19.1 years) and highest potential years of life lost were measured in HIV-positive injection drug users who were not taking HAART. CONCLUSIONS: There are substantial disparities in life expectancy for persons living with HIV in British Columbia. Members of the injection drug community, particularly those who are not taking HAART, experience elevated mortality in comparison with those without a history of drug use.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".