Human immunodeficiency virus case detection and antiretroviral therapy enrollment among children below and above 18 months old
Bibliographic record
Abstract
ABSTRACT: While pediatric human immunodeficiency virus (HIV) testing has been more focused on children below 18 months through prevention of mother to child transmission of HIV (PMTCT), the yield of this approach remains unclear comparatively to testing children above 18 months through routine provider-initiated testing and counselling (PITC). This study aimed at assessing and comparing the HIV case detection and antiretroviral therapy (ART) enrolment among children below and above 18 months of age in Cameroon. This information is required to guide the investments in HIV testing among children and adolescents.We conducted a cross-sectional study where we invited parents visiting or receiving HIV care in 3 hospitals to have their children tested for HIV. HIV testing was done using polymerase chain reaction (PCR) and antibody rapid tests for children <18 months and those ≥18 months, respectively. We compared HIV case detection and ART initiation between the 2 subgroups of children and this using Chi-square test at 5% significant level.A total of 4079 children aged 6 weeks to 15 years were included in the analysis. Compared with children <18 months, children group ≥18 months was 4-fold higher among those who enrolled in the study (80.3% vs 19.7%, P < .001); 3.5-fold higher among those who tested for HIV (77.6% vs 22.4%, P < .001); 6-fold higher among those who tested HIV+ (85.7% vs 14.3%, P = .24), and 11-fold higher among those who enrolled on ART (91.7% vs 8.3%, P = .02).Our results show that 4 out of 5 children who tested HIV+ and over 90% of ART enrolled cases were children ≥18 months. Thus, while rolling out PCR HIV testing technology for neonates and infants, committing adequate and proportionate resources in antibody rapid testing for older children is a sine quo none condition to achieve an acquired immunodeficiency syndrome (AIDS)-free generation.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".