A shorter treatment regimen for latent tuberculosis infection holds promise for at-risk Canadians
Bibliographic record
Abstract
Despite recent success in reducing its incidence, tuberculosis remains a considerable challenge in Canada, particularly among foreign-born and Indigenous populations. A key component of the strategy for controlling the disease is the treatment of latent tuberculosis infection. The standard treatment consists of isoniazid (INH) daily for nine months. In recent years, shorter regimens have been developed in the hope of increasing rates of treatment acceptance and completion. Of these, the shortest and most recently developed is a combination of INH and rifapentine taken once weekly for 12 doses (3HP), typically using directly observed therapy (DOT). This regimen has been approved by the Food and Drug Administration in the United States but is not yet authorized in Canada. Based on a rapidly expanding number of observational studies and randomized controlled trials, 12 weeks of 3HP appears to have similar efficacy to nine months of INH, a favourable adverse event profile and potentially improved rates of treatment completion. Although rates of treatment acceptance, the role of self-administered therapy and the regimen's cost-effectiveness within the Canadian context remain uncertain, 3HP is a promising alternative to existing treatments for LTBI.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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".