Influence of M. tuberculosis Lineage Variability within a Clinical Trial for Pulmonary Tuberculosis
Bibliographic record
Abstract
Recent studies suggest that M. tuberculosis lineage and host genetics interact to impact how active tuberculosis presents clinically. We determined the phylogenetic lineages of M. tuberculosis isolates from participants enrolled in the Tuberculosis Trials Consortium Study 28, conducted in Brazil, Canada, South Africa, Spain, Uganda and the United States, and secondarily explored the relationship between lineage, clinical presentation and response to treatment. Large sequence polymorphisms and single nucleotide polymorphisms were analyzed to determine lineage and sublineage of isolates. Of 306 isolates genotyped, 246 (80.4%) belonged to the Euro-American lineage, with sublineage 724 predominating at African sites (99/192, 51.5%), and the Euro-American strains other than 724 predominating at non-African sites (89/114, 78.1%). Uneven distribution of lineages across regions limited our ability to discern significant associations, nonetheless, in univariate analyses, Euro-American sublineage 724 was associated with more severe disease at baseline, and along with the East Asian lineage was associated with lower bacteriologic conversion after 8 weeks of treatment. Disease presentation and response to drug treatment varied by lineage, but these associations were no longer statistically significant after adjustment for other variables associated with week-8 culture status.
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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 | 0.021 | 0.066 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".