Socioeconomic status, access to triple therapy, and survival from HIV-disease since 1996
Bibliographic record
Abstract
BACKGROUND: In the era before highly active antiretroviral therapy (HAART), socioeconomic status was associated with survival from HIV disease. We have explored socioeconomic status, access to triple therapy (HAART), and mortality in the context of a universal healthcare system. METHODS: We evaluated 1408 individuals who initiated double or triple therapy between 1 August 1996 and 31 December 1999, and were followed until 31 March 2000. Cumulative HIV-related mortality rates were estimated using Kaplan-Meier methods and Cox proportional hazards regression. RESULTS: In the overall Cox model, we found that adherence [risk ratio (RR) 0.83; per 10% increase], CD4 cell count (RR 1.53; per 100 cell decrease), and lower socioeconomic status (RR 2.19; high versus low), were associated with HIV-related mortality. However, socioeconomic status was not significant among patients prescribed triple therapy in a stratified analysis, or in a sub-analysis restricted to patients prescribed HAART in the initial regimen. When we investigated if inequitable access to HAART by socio-economic status could explain the discrepancy, we found that persons in the lower socio-economic strata were less likely to be prescribed triple therapy even after adjustment for clinical characteristics. CONCLUSION: In a universal healthcare system, socioeconomic status was strongly associated with HIV-related mortality. When we investigated possible explanations for this association, we found that individuals of lower socioeconomic status were less likely to receive triple therapy after adjustment for clinical characteristics. Our findings highlight the need for the monitoring of therapeutic guidelines to ensure equitable access, as treatment strategies are updated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".