Poor adherence to HIV monitoring and treatment guidelines for HIV‐infected injection drug users
Bibliographic record
Abstract
OBJECTIVES: There is growing concern about access to HIV/AIDS care among injection drug users (IDUs). We examined rates of CD4 cell count monitoring and correlates among HIV-infected IDUs. METHODS: This prospective observational cohort study of 460 community-recruited HIV-infected IDUs was situated in a Canadian city where all medical care is provided free of charge. Over a median follow-up period of 76 months, we evaluated factors associated with CD4 cell count monitoring through a linkage with a centralized CD4 registry. RESULTS: Overall, <5% of IDUs had CD4 monitoring consistent with local therapeutic guidelines. In multivariate analyses, after adjustment for being on antiretroviral therapy [odds ratio (OR) 2.21, 95% confidence interval (CI) 1.84-2.70, P<0.001] female gender (OR 0.71, 95% CI 0.57-0.89, P=0.003), non-White ethnicity (OR 0.75, 95% CI 0.60-0.94, P=0.014), use of methadone maintenance therapy (OR 1.66, 95% CI 1.42-1.94, P<0.001) and daily heroin use (OR 0.72, 95% CI 0.61-0.85, P<0.001) were independently associated with CD4 monitoring. CONCLUSIONS: Strategies to improve CD4 surveillance among IDUs are critically important, particularly for female and non-White IDUs. Expanded treatment for heroin dependence appears to have the greatest potential for improved care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".