Highly active antiretroviral treatment and health related quality of life in South African adults with human immunodeficiency virus infection: A cross-sectional analytical study
Bibliographic record
Abstract
BACKGROUND: Health Related Quality of Life (HRQoL) is an important outcome in times of Highly Active Antiretroviral Treatment (HAART). We compared the HRQoL of HIV positive patients receiving HAART with those awaiting treatment in public sector facilities in the Free State province in South Africa. METHODS: A stratified random sample of 371 patients receiving or awaiting HAART were interviewed and the EuroQol-profile, EuroQol-index and Visual Analogue Scale (VAS) were compared. Independent associations between these outcomes and HAART, socio-demographic, clinical and health service variables were estimated using linear and ordinal logistic regression, adjusted for intra-clinic clustering of outcomes. RESULTS: Patients receiving HAART reported better HRQoL for 3 of the 5 EuroQol-dimensions, for the VAS score and for the EuroQol index in bivariable analysis. They had a higher mean EuroQol index (0.11 difference, 95% confidence interval [CI] 0.04; 0.23), and were more likely to have a higher index (odds ratio 1.9, 95% CI 1.1; 1.3), compared to those awaiting HAART, in multivariate analysis. Higher mean VAS scores were reported for patients who were receiving HAART (6.5 difference, 95% CI 1.3; 11.7), were employed (9.1, 95% CI 4.3; 13.7) or were female (4.7, 95% CI 0.79; 8.5). CONCLUSION: HAART was associated with improved HRQoL in patients enrolled in a public sector treatment program in South Africa. Our finding that the EuroQol instrument was sensitive to HAART supports its use in future evaluation of HIV/AIDS care in South Africa. Longitudinal studies are needed to evaluate changes in individuals' HRQoL.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".