Acceptance of screening and completion of treatment for latent tuberculosis infection among refugee claimants in Canada.
Bibliographic record
Abstract
SETTING: Primary care clinic for refugee claimants, Montreal, Canada. OBJECTIVES: To identify factors linked to the acceptance of the tuberculin skin test (TST), and assess completion of treatment for latent tuberculosis infection (LTBI). DESIGN: Asylum seekers consulting for a medical complaint or medical immigration examination between February and October 1999 were assessed for eligibility. Personal and clinical information was gathered prospectively by questionnaire. Hospital files were reviewed to assess completion of LTBI treatment. RESULTS: In our study, 296 subjects (72.4% of 409 eligible) were offered TST, of whom 227 accepted (76.7%). Of these, 49 (24.9%) had a TST > or = 10 mm and 24 (49%) completed 6 months of LTBI treatment. Logistic regression models showed that patients who had never had a TST (OR 3.2, 95%CI 1.34-7.6) or had no temporary exclusion criteria (OR 4.0, 95%CI 1.6-9.9) were more likely to accept TST. Perceiving tuberculosis as a severe disease (OR 0.29, 95%CI 0.09-0.91) and consulting for an immigration examination (OR 0.42, 95%CI 0.18-0.98) was associated with refusal of TST. Increasing age was found to be independently associated with a positive TST (OR 1.06, 95%CI 1.01-1.12). Variability in the proportion of positive results was found between TST readers. CONCLUSION: This study supports the feasibility of screening refugee claimants for LTBI during medical consultation and of developing organizational links to ensure completion of LTBI treatment.
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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".