Factors associated with the initiation of treatment for latent tuberculosis infection
Bibliographic record
Abstract
Background. Treating Latent Tuberculosis (TB) Infection (LTBI) decreases the risk of it progressing to active TB by 90%, yet only a fraction of those offered treatment initiate therapy. Objective. To determine if being a health care worker (HCW) is associated with the initiation of treatment for LTBI. Methods. Retrospective cohort study of patients with LTBI. Results. The overall LTBI treatment initiation rate of the clinic population was 58%. Fifty-five of 116 (47%) HCW versus 126/194 (65%) non-HCW initiated treatment for LTBI. (OR 0.49, 95% CI 0.30–0.78) Multivariate analysis controlling for age, sex, foreign-birth, contact with active TB, previous Bacillus Calmette-Guerin (BCG) vaccination, previous positive TB skin test, history of liver disease, abnormal liver enzymes, CXR abnormalities, comorbidities, and income produced similar results (adjusted OR 0.50, 95% CI 0.29–0.86). Conclusion. At a TB clinic in downtown Toronto, HCW were less likely than other patients to initiate treatment 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".