Predictive value for progression to tuberculosis by IGRA and TST in immigrant contacts
Bibliographic record
Abstract
The authors determined the positive predictive value (PPV) for progression to tuberculosis (TB) of two interferon-gamma release assays (IGRAs), QuantiFERON-TB Gold In-tube (QFT-GIT) and T-SPOT.TB, and the tuberculin skin test (TST) in immigrants contacts. Immigrant close contacts of sputum smear-positive TB patients were included when aged > or =16 yrs and their TST result was > or =5 mm 0 or 3 months after diagnosis of the index patient. Contacts were followed for the next 2 yrs for development of TB disease. Of 339 immigrant contacts with TST > or =5 mm, 324 and 299 had valid results of QFT-GIT and T-SPOT.TB, respectively. Nine contacts developed active TB. One patient had not been tested with TST, while another patient had not been tested with QFT-GIT and T-SPOT.TB. The PPV for progression to TB during this period was 9/288 = 3.1% (95% CI 1.3-5.0%) for TST > or =10 mm, 7/184 = 3.8% (95% CI 1.7-5.9%) for TST > or =15 mm, 5/178 = 2.8% (95% CI 1.0-4.6%) for QFT-GIT and 6/181 = 3.3% (95% CI 1.3-5.3%) for T-SPOT.TB. Sensitivity was 100%, 88%, 63% and 75%, respectively. The predictive values of QFT-GIT, T-SPOT.TB and TST for progression to TB disease among immigrant close contacts were comparable.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".