Barriers to the care of HIV-infected children in rural Zambia: a cross-sectional analysis
Bibliographic record
Abstract
BACKGROUND: Successful antiretroviral treatment programs in rural sub-Saharan Africa may face different challenges than programs in urban areas. The objective of this study was to identify patient characteristics, barriers to care, and treatment responses of HIV-infected children seeking care in rural Zambia. METHODS: Cross-sectional analysis of HIV-infected children seeking care at Macha Hospital in rural southern Zambia. Information was collected from caretakers and medical records. RESULTS: 192 HIV-infected children were enrolled from September 2007 through September 2008, 28% of whom were receiving antiretroviral therapy (ART) at enrollment. The median age was 3.3 years for children not receiving ART (IQR 1.8, 6.7) and 4.5 years for children receiving ART (IQR 2.7, 8.6). 91% travelled more than one hour to the clinic and 26% travelled more than 5 hours. Most participants (73%) reported difficulties accessing the clinic, including insufficient money (60%), lack of transportation (54%) and roads in poor condition (32%). The 54 children who were receiving ART at study enrollment had been on ART a median of 8.6 months (IQR: 2.7, 19.5). The median percentage of CD4+ T cells was 12.4 (IQR: 9.2, 18.6) at the start of ART, and increased to 28.6 (IQR: 23.5, 36.1) at the initial study visit. However, the proportion of children who were underweight decreased only slightly, from 70% at initiation of ART to 61% at the initial study visit. CONCLUSION: HIV-infected children in rural southern Zambia have long travel times to access care and may have poorer weight gain on ART than children in urban areas. Despite these barriers, these children had a substantial rise in CD4+ T cell counts in the first year of ART although longer follow-up may indicate these gains are not sustained.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".