The Lack of Association Between Bacille Calmette‐Guerin Vaccination and Clustering of Aboriginals with Tuberculosis in Western Canada
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) remains a major health problem for Aboriginal people in Canada, with high rates of clustering of active TB cases. Bacille Calmette-Guerin (BCG) vaccination has been used as a preventive measure against TB in this high-risk population. OBJECTIVES: The study was designed to determine if BCG vaccination in Aboriginal people influenced recent TB transmission through an analysis of the clustering of TB cases. METHODS: A retrospective analysis of all culture-positive Mycobacterium tuberculosis cases in Aboriginal people in western Canada (1995 to 1997) was performed. Isolates were analyzed using standard methodology for restriction fragment length polymorphism and spoligotyping. RESULTS: Of 256 culture-positive Aboriginal TB cases, BCG status was confirmed in 216 (84%) cases; 34% had been vaccinated with BCG, 57% were male and 56% were living on-reserve. Patients who had been vaccinated with BCG were younger than unvaccinated individuals (mean age 32.4+/-1.65 years versus 45.0+/-1.8 years, P<0.0001). Clustering was found in 62% of cases: 59% of non-BCG vaccinated cases were clustered versus 68% of those vaccinated with BCG (P=0.16). Younger patients (younger than 60 years of age) were more likely to be clustered in the univariate analysis (P<0.01). When age, sex, province, and HIV and reserve status were controlled for, BCG vaccination was not associated with clustering (OR 1.3, 95% CI 0.7 to 2.6). CONCLUSIONS: BCG vaccinated Aboriginal people were no less likely to have active TB from recently transmitted disease. BCG vaccination appears to have limited value in preventing clustering of TB cases within this high-risk community.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".