Nonadherence to Clinic Appointments Among HIV-Infected Children in an Ambulatory Care Program in Western Kenya
Bibliographic record
Abstract
BACKGROUND: Nonadherence to clinic appointments is associated with poor outcomes in HIV-infected adults. We describe the effect of cumulative clinic adherence (CCA) to clinic appointments on mortality and loss to follow-up (LTFU) among HIV-infected children in Kenya. METHODS: We analyzed retrospective clinical data from HIV-infected children in the United States Agency for International Development-Academic Model Providing Access to Healthcare Partnership in Kenya between 2001 and 2009. We defined CCA as the proportion of days adherent to clinic visits after enrollment. We examined the effects of CCA on both death and LTFU, controlling for demographic and clinical factors at enrollment and over time. Cox proportional hazards models with time-varying coefficients were used to calculate adjusted hazard ratios (AHR) associated with each 10% increase in CCA on mortality and LTFU. RESULTS: Among 3255 HIV-infected children, 1668 (51.2%) were male, median enrollment age of 5.2 years (interquartile range: 3.6-7.4). Of 2393 children with CD4 within 3 months after enrollment, 1125 (47.0%) were severely immune suppressed, 567 became LTFU, and 88 died. Children with higher CCA had a higher risk of both mortality and LTFU at 3 and 6 months. Higher CCA became protective at 24 months for mortality, AHR at 24 months: 0.7 (95% confidence interval: 0.6 to 0.9), and at 12 months for LTFU, AHR at 24 months: 0.7 (95% confidence interval: 0.7 to 0.7). CONCLUSIONS: Children adherence to clinic visits during the first 6 months of HIV care was associated with a higher risk of death and LTFU, but by 24 months, children with better CCA had a reduced risk of LTFU and mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".