The adherence gap
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to observe the effect of sex on attaining optimal adherence to combination antiretroviral therapy (cART) longitudinally while controlling for known adherence confounders - IDU and ethnicity. DESIGN: Using the population-based HAART Observational Medical Evaluation and Research cohort, data were collected from HIV-positive adults, aged at least 19 years, receiving cART in British Columbia, Canada, with data collected between 2000 and 2014. cART adherence was assessed using pharmacy refill data. The proportion of participants reaching optimal (≥95%) adherence by sex was compared per 6-month period from initiation of therapy onward. Generalized linear mixed models with logistic regression examined the effect of sex on cART adherence. RESULTS: Among 4534 individuals followed for a median of 65.9 months (interquartile range: 37.0-103.2), 904 (19.9%) were women, 589 (13.0%) were Indigenous, and 1603 (35.4%) had a history of IDU. A significantly lower proportion of women relative to men were optimally adherent overall (57.0 vs. 77.1%; P < 0.001) and in covariate analyses. In adjusted analyses, female sex remained independently associated with suboptimal adherence overall (adjusted odds ratio: 0.55; 95% confidence interval: 0.48-0.63). CONCLUSION: Women living with HIV had significantly lower cART adherence rates then men across a 14-year period overall, and by subgroup. Targeted research is required to identify barriers to adherence among women living with HIV to tailor women-centered HIV care and treatment support services.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".