Prevalence of tuberculosis infection and disease in children referred for tuberculosis medical surveillance in Ontario: a single-cohort study
Bibliographic record
Abstract
BACKGROUND: There are few data about the utility of the Canadian tuberculosis medical surveillance system for detecting tuberculosis in children and adolescents. We sought to assess the prevalence of tuberculosis infection and disease in children and adolescents referred by the tuberculosis medical surveillance program who were evaluated at The Hospital for Sick Children (SickKids) tuberculosis program. METHODS: We retrospectively studied clinical records, radiographic findings and results of interferon-γ release assays (IGRAs) of all children less than 18 years of age referred by the tuberculosis medical surveillance program and evaluated at SickKids between November 2012 and June 2016. RESULTS: The median age of the 216 children was 10.0 years. Most were born in the Philippines (157 [72.7%]) or India (39 [18.0%]). Of the 216, 166 (76.8%) had a history of prior treatment for tuberculosis, and 34 (15.7%) were federal-sponsored refugees from settings with a high tuberculosis burden. Negative IGRA results were found in 110/130 (84.6%) of those with prior tuberculosis treatment. Thirty-one children (14.4%) had any chest radiographic abnormality, of whom 4 had changes thought to be due to tuberculosis. No child received a diagnosis of active tuberculosis at assessment or during follow-up; 3 (1.4%) were treated for latent tuberculosis infection following IGRA testing at SickKids. A positive IGRA result was associated with contact with infectious tuberculosis (odds ratio [OR] 5.97, 95% confidence interval [CI] 2.06-17.52) and older age at first clinic visit (OR 2.98, 95% CI 1.24-8.30) but not with radiographic abnormalities or history of prior tuberculosis treatment. INTERPRETATION: Most children were referred because of a history of prior treatment for tuberculosis; few had clinical or laboratory evidence of infection or prior disease. The tuberculosis medical surveillance process did not identify any children who required treatment for active disease and requires improvement.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".