Non-completion of latent tuberculous infection treatment among children in Rio de Janeiro State, Brazil
Bibliographic record
Abstract
BACKGROUND: Children with latent tuberculous infection (LTBI) are particularly vulnerable to progression to active tuberculosis (TB), and are thus a priority target for isoniazid preventive therapy (IPT). However, adherence to IPT is poor. We hypothesised that children from poorer families, with reduced access to health care and lack of understanding about the disease are more likely to default from IPT. METHODS: A questionnaire was administered to close child contacts or their parents at the time of prescribing IPT in three cities in Rio de Janeiro State. The children were followed prospectively. Treatment adherence was defined as taking 80% of prescribed doses. RESULTS: Among 1078 children screened for LTBI, 97 (8.9%) did not return for tuberculin skin test (TST) reading; 332 (30.8%) were TST-positive; 115/332 (34.6%) were prescribed IPT, 6 of whom did not initiate treatment and 11 did not adhere during the first 2 months; 25 additional children did not complete IPT. Overall non-completion was four times more frequent among those with lower income. Health care access and knowledge did not improve treatment completion. CONCLUSIONS: Substantial losses to follow-up occurred before IPT prescription; this should be further investigated. Among the children who started isoniazid, low income, but not difficult access or poor knowledge, increased the risk of treatment non-completion.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".