Use of the QuantiFERON-TB Gold test to confirm latent tuberculosis infection in a Canadian tuberculosis clinic.
Bibliographic record
Abstract
SETTING: Capital Health Tuberculosis (TB) Clinic, Edmonton, Alberta, Canada. OBJECTIVE: To analyze the QuantiFERON-TB Gold In-Tube test (QFT) results after implementation as a routine test for tuberculin skin test (TST) positive patients. DESIGN: From November 2004 until January 2007, patients who were TST-positive and were eligible for preventive treatment based on Canadian guidelines, were offered a QFT. RESULTS: Of 1446 TST-positive patients, only 566 (39.6%) were QFT-positive. Categorized by reason for TST testing, 43.1% of 304 contacts, 32.8% of 348 employment screens and 24.2% of 298 post secondary school screens were QFT-positive. In contrast, 59.7% of 290 immigration screens were QFT-positive. A multivariate analysis found that QFT positivity was associated with older age, larger TST size, high-incidence TB region of birth, history of TB and chest X-ray findings suggestive of previous TB. CONCLUSION: Implementation of the QFT as a secondary test for latent TB infection (LTBI) can significantly reduce the number of patients given LTBI treatment in a low-incidence country such as Canada.
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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".