Risk of tuberculosis in children from smear-negative source cases.
Bibliographic record
Abstract
SETTING: British Columbia, Canada. OBJECTIVE: To determine the frequency of smear-negative tuberculosis (TB) transmission events from adults to children in epidemiologically linked pairs and to determine the predictors for identifying the source case. DESIGN: We extracted demographic, clinical and mycobacteriology information of 190 children with TB and their 83 source cases reported from 1990 to 2001 in the province of British Columbia. Smear-negative transmission events from adults to children were determined by identifying the smear results of epidemiologically linked source cases. We compared the sex, age, ethnicity, contact history, site of disease and tuberculin skin test (TST) results of children who had a source case identified with those who had not. RESULTS: Smear-negative source cases transmitted the disease to 10% of children (95%CI 5-17). Aboriginals (OR 4.9, 95%CI 1.5-13.4), those with primary TB (OR 7.3, 95%CI 3.3-16.0) and those with a positive TST (OR 2.9, 95%CI 1.2-7.0) were independent predictors for source case identification. CONCLUSION: This study suggests lower rates of transmission of disease to children from smear-negative sources compared to other studies involving all ages. Ethnicity of children, site of disease and a positive TST predict source case identification.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".