Serial Testing of Health Care Workers for Tuberculosis Using Interferon-γ Assay
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
RATIONALE: Although interferon-gamma (IFN-gamma) assays are promising alternatives to the tuberculin skin test (TST), their serial testing performance is unknown. OBJECTIVE: To compare TST and IFN-gamma conversions and reversions in healthcare workers. METHODS: We prospectively followed-up 216 medical and nursing students in India who underwent baseline and repeat testing (after 18 mo) with TST and QuantiFERON-TB Gold In-Tube (QFT). TST conversions were defined as reactions greater than or equal to 10 mm, with increments of 6 or 10 mm over baseline. QFT conversions were defined as baseline IFN-gamma less than 0.35 and follow-up IFN-gamma greater than or equal to 0.35 or 0.70 IU/ml. QFT reversions were defined as baseline IFN-gamma greater than or equal to 0.35 and follow-up IFN-gamma less than 0.35 IU/ml. RESULTS: Of the 216 participants, 48 (22%) were TST-positive, and 38 (18%) were QFT-positive at baseline. Among 147 participants with concordant baseline negative results, TST conversions occurred in 14 (9.5%; 95% confidence interval [CI] = 5.3-15.5) using the 6 mm increment definition, and 6 (4.1%; 95% CI = 1.5-8.7) using the 10 mm increment definition. QFT conversions occurred in 17/147 participants (11.6%; 95% CI = 6.9-17.9) using the definition of IFN-gamma greater than or equal to 0.35 IU/ml, and 11/147 participants (7.5%; 95% CI = 3.8-13.0) using IFN-gamma greater than or equal to 0.70 IU/ml. Agreement between TST (10 mm increment) and QFT conversions (>or= 0.70 IU/ml) was 96% (kappa = 0.70). QFT reversions occurred in 2/28 participants (7%) with baseline concordant positive results, as compared with 7/10 participants (70%) with baseline discordant results (p < 0.001). CONCLUSIONS: IFN-gamma assay shows promise for serial testing, but repeat results need to be interpreted carefully. To meaningfully interpret serial results, the optimal thresholds to distinguish new infections from nonspecific variations must be determined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it