Risk factors for suboptimal antiretroviral therapy adherence in HIV-infected adolescents in Gaborone, Botswana: a pilot cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: Little is known about factors associated with suboptimal antiretroviral treatment (ART) adherence among adolescents in Sub-Saharan Africa. Our objective was to determine the level of ART adherence and predictors of non-adherence among human immunodeficiency virus (HIV)-infected adolescents at the Botswana-Baylor Children's Clinical Centre of Excellence in Gaborone, Botswana. METHODS: In a cross-sectional study, 82 HIV-infected adolescents receiving ART and their caregivers were administered a structured questionnaire. The patient's clinical information was retrieved from medical records. Outcome measures included excellent pill count ART adherence (>95%) and virologic suppression (HIV viral load <400 copies/mL). Multivariate logistic regression analysis was performed to identify independent predictors of ART non-adherence. RESULTS: The overall median (interquartile range) ART adherence was 99% (96.5-100) (N = 82). Seventy-six percent of adolescents had excellent pill count ART adherence levels and 94% achieved virologic suppression. Male adolescents made up 65% of the non-adherent group (P = 0.02). Those who displayed suboptimal ART adherence were more likely to report having ever missed ART doses due to failure to pick up medication at the pharmacy (30.0% versus 9.7%, P = 0.03). In the multivariate logistic regression model, male sex (odds ratio [OR] 3.29, 95% confidence interval [CI] 1.13-9.54; P = 0.03) was the only factor which was independently associated with suboptimal ART adherence. CONCLUSIONS: A high proportion of HIV-infected adolescents studied had excellent ART adherence and virologic suppression, with male adolescents at higher risk of suboptimal adherence than females. Further research to investigate how sex relates to suboptimal adherence may aid in the design of targeted intervention strategies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".