Health-Related Quality of Life in HIV-Infected and At-Risk Women
Bibliographic record
Abstract
PURPOSE: To assess the impact of illicit drug use and chronic hepatitis C virus (HCV) on health-related quality of life (HRQoL) in women with HIV or at risk for HIV infection. METHODS: Cross-sectional analysis of data from the Women's Interagency Health Study (WIHS) of women with HIV (n = 2508) and at high risk of HIV infection (n = 889) in the US. A Short-Form-6D (SF-6D) HRQoL measure derived from the Medical Outcomes Study-HIV (MOS-HIV) questionnaire, HIV infection status, CD4 cell count (a measure of immune status), antiretroviral treatment, current illicit drug use (heroin and/or cocaine), and HCV status were assessed at a recent study visit. We developed multivariate linear regression models adjusting for age, race/ethnicity, education, and testing for interactions. RESULTS: HIV-infected women with ≤200 CD4 cells/µL had lower mean HRQoL scores (0.69) than either HIV-infected women with >200 CD4 cells/µL (0.78) or HIV-uninfected women (0.80) (P < 0.01). In multivariate analysis, illicit drug use, chronic HCV, and low CD4 count were independently associated with lower HRQoL. There was a differential effect of HCV and illicit drug use for HIV-infected women depending on CD4 cell count: HIV-infected women with >200 CD4 cells/µL had a significantly greater reduction in HRQoL associated with illicit drug use (-0.063) and chronic HCV (-0.036) than women with ≤200 CD4 cells/µL (-0.017, -0.005 respectively). CONCLUSIONS: Poorly controlled HIV, illicit drug use, and chronic HCV are associated with lower HRQoL. Illicit drug use and chronic HCV have greater HRQoL impacts for HIV-infected women with well-controlled HIV versus those with poorly controlled HIV, which may affect clinical and policy priorities.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".