Understanding the Correlates of Attrition Associated with Antiretroviral Use and Viral Suppression Among Women Living with HIV in Canada
Bibliographic record
Abstract
Attrition along the cascade of HIV care compromises attainment of the UNAIDS 90-90-90 goals and achievement of desirable treatment outcomes for people living with HIV. Given known gender disparities in HIV care and outcomes, understanding the correlates of attrition at stages of the care cascade for women living with HIV (WLWH) is essential. Among the 1425 WLWH enrolled in the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS), we measured the proportion who reported not being currently on combination antiretroviral therapy (cART) and the proportion who reported a detectable viral load (VL; ≥40 copies/mL) despite cART use. Correlates of these cascade indicators were examined using univariate and multivariable logistic regression. Overall, 14.8% of women were not currently on cART. Of women who were on cART, 9.0% were not virally suppressed. In multivariable analyses, age between 26 and 34, unstable housing, food insecurity, current injection drug use, higher HIV-related stigma, and racial discrimination were associated with increased odds of not being on cART. Factors associated with increased odds of reporting a detectable VL among women on cART included age ≤34 years, less than a secondary education, unstable housing, and incarceration in the previous year. Programmatic efforts to support cART use and viral suppression for WLWH in Canada should focus on social determinants of health, including housing and food insecurity, social exclusion, and education.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".