TB Screening in Canadian Health Care Workers Using Interferon-Gamma Release Assays
Bibliographic record
Abstract
BACKGROUND: While many North American healthcare institutions are switching from Tuberculin Skin Test (TST) to Interferon-gamma release assays (IGRAs), there is relatively limited data on association between occupational tuberculosis (TB) risk factors and test positivity and/or patterns of test discordance. METHODS: We recruited a cohort of Canadian health care workers (HCWs) in Montreal, and performed both TST and QuantiFERON-TB Gold In Tube (QFT) tests, and assessed risk factors and occupational exposure. RESULTS: In a cross-sectional analysis of baseline results, the prevalence of TST positivity using the 10 mm cut-off was 5.7% (22/388, 95%CI: 3.6-8.5%), while QFT positivity was 6.2% (24/388, 95%CI: 4-9.1%). Overall agreement between the tests was poor (kappa=0.26), and 8.3% of HCWs had discordant test results, most frequently TST-/QFT+ (17/388, 4.4%). TST positivity was associated with total years worked in health care, non-occupational exposure to TB and BCG vaccination received after infancy or on multiple occasions. QFT positivity was associated with having worked as a HCW in a foreign country. CONCLUSIONS: Our results suggest that LTBI prevalence as measured by either the TST or the QFT is low in this HCW population. Of concern is the high frequency of unexplainable test discordance, namely: TST-/QFT+ subjects, and the lack of any association between QFT positivity and clear-cut recent TB exposure. If these discordant results are indeed false positives, the use of QFT in lieu of TST in low TB incidence settings could result in overtreatment of uninfected individuals.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".