Culture-positive Pediatric Tuberculosis in Toronto, Ontario
Bibliographic record
Abstract
BACKGROUND: Few data relate Mycobacterium tuberculosis (Mtb) lineage and disease phenotype in the pediatric population or examine the contribution of travel to the tuberculosis (TB)-endemic country in North America. We examined clinical, demographic and Mtb genotype data from patients with TB who were treated in Toronto between 2002 and 2012. METHODS: Consecutive Mtb culture-positive, pediatric patients were included. Clinical data were collected from a prospectively populated clinical database. Mtb case isolate genotypes were identified using Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeat (MIRU-VNTR) and spoligotyping and were categorized into phylogeographic lineages for analysis. RESULTS: The 77 patients included 30.4% of all culture-positive pediatric TB cases in Ontario from 2002 to 2012. Seventy-six (99%) patients were first or second generation Canadians. Foreign-born patients were more likely to have extrathoracic disease [odds ratios (OR) = 3.0; 95% confidence interval (CI): 1.04-8.71; P < 0.05] and less likely to have a genotype match in the Public Health Ontario Laboratories database [OR = 0.32 (95% CI: 0.11-0.90); P < 0.05] than Canadian-born patients. For those without a known TB contact, Canadian-born patients were more likely to have travelled to a TB-endemic country [OR = 13.0 (95% CI: 2.5-78.5); P < 0.001]. Extrathoracic disease was less likely in patients infected with the East Asian Mtb lineage [OR = 0.1 (95% CI: 0.01-0.9); P < 0.05] and more likely in those infected with the Indo-Oceanic Mtb lineage [OR = 5.4 (95% CI: 1.5-19.2); P < 0.05]. CONCLUSIONS: Travel to TB-endemic countries likely plays an important part in the etiology of pediatric TB infection and disease, especially in Canadian-born children. Mtb lineage seems to contribute to disease phenotype in children as it has been described in adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".