A Population-Based Cohort Study of Mycobacterium tuberculosis Beijing Strains: An Emerging Public Health Threat in an Immigrant-Receiving Country?
Bibliographic record
Abstract
INTRODUCTION: Mycobacterium tuberculosis Beijing strains are frequently associated with tuberculosis outbreaks and drug resistance. However, contradictory evidence and limited study generalizability make it difficult to foresee if the emergence of Beijing strains in high-income immigrant-receiving countries poses an increased public health threat. The purpose of this study was to determine if Beijing strains are associated with high risk disease presentations relative to other strains within Canada. METHODS: This was a retrospective population-based study of culture-confirmed active TB cases in a major immigrant-receiving province of Canada in 1991 through 2007. Of 1,852 eligible cases, 1,826 (99%) were successfully genotyped. Demographic, clinical, and mycobacteriologic surveillance data were combined with molecular diagnostic data. The main outcome measures were site of disease, lung cavitation, sputum smear positivity, bacillary load, and first-line antituberculosis drug resistance. RESULTS: A total of 350 (19%) patients had Beijing strains; 298 (85%) of these were born in the Western Pacific. Compared to non-Beijing strains, Beijing strains were significantly more likely to be associated with polyresistance (aOR 1.8; 95% CI 1.0-3.3; p = 0.046) and multidrug-resistance (aOR 3.4; 1.0-11.3; p = 0.049). Conversely, Beijing strains were no more likely than non-Beijing strains to be associated with respiratory disease (aOR 1.3; 1.0-1.8; p = 0.053), high bacillary load (aOR 1.2; 0.6-2.7), lung cavitation (aOR 1.0; 0.7-1.5), immediately life-threatening forms of tuberculosis (aOR 0.8; 0.5-1.6), and monoresistance (aOR 0.9; 0.6-1.3). In subgroup analyses, Beijing strains only had a significant association with multidrug-resistant tuberculosis (aOR 6.1; 1.2-30.4), and an association of borderline significance with polyresistant tuberculosis (aOR 1.8; 1.0-3.5; p = 0.062), among individuals born in the Western Pacific. CONCLUSION: Other than an increased risk of polyresistant or multidrug-resistant tuberculosis, Beijing strains appear to pose no more of a public health threat than non-Beijing strains within a high-income immigrant-receiving country.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".