Health-Related Quality of Life in a Randomized Trial of Antiretroviral Therapy for Advanced HIV Disease
Bibliographic record
Abstract
OBJECTIVE: To assess and compare alternative approaches of measuring preference-based health-related quality of life (HRQoL) in treatment-experienced HIV patients and evaluate their association with health status and clinical variables. DESIGN: Cross-sectional study. SETTING: Twenty-eight Veterans Affairs hospitals in the United States, 13 hospitals in Canada, and 8 hospitals in the United Kingdom. PATIENTS: Three hundred sixty-eight treatment-experienced HIV-infected patients enrolled in the Options in Management with Antiretrovirals randomized trial. MEASUREMENTS: Baseline sociodemographic and clinical indicators and baseline HRQoL using the Medical Outcome Study HIV Health Survey (MOS-HIV), the EQ-5D, the EQ-5D visual analog scale (EQ-5D VAS), the Health Utilities Index Mark 3 (HUI3), and standard gamble (SG) and time trade-off (TTO) techniques. RESULTS: The mean (SD) baseline HRQoL scores were as follows: MOS-HIV physical health summary score 41.70 (11.16), MOS-HIV mental health summary score 44.76 (11.38), EQ-5D 0.77 (0.19), HUI3 0.59 (0.32), EQ-5D VAS 65.94 (21.71), SG 0.75 (0.29), and TTO 0.80 (0.31). Correlations between MOS-HIV summary scores and EQ-5D, EQ-5D VAS, and HUI3 ranged from 0.60 to 0.70; the correlation between EQ-5D and HUI3 was 0.73; and the correlation between SG and TTO was 0.43. Preference-based HRQoL scores were related to physical, mental, social, and overall health as measured by MOS-HIV. Concomitant medication use, CD4 cell count, and HIV viral load were related to some instruments' scores. CONCLUSIONS: On average, preference-based HRQoL for treatment-experienced HIV patients was decreased relative to national norms but also highly variable. Health status and clinical variables were related to 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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".