Interferon-gamma release assays for diagnosis of latent tuberculosis infection: evidence in immune-mediated inflammatory disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide a narrative synthesis of evidence on interferon-gamma release assays (IGRAs) for the diagnosis of latent tuberculosis infection (LTBI) in individuals with immune-mediated inflammatory disorders (IMIDs). RECENT FINDINGS: Only a few studies have evaluated IGRAs in IMIDs, and most were small and varied considerably with respect to the use of immunosuppressive medications and types of IMIDs. Current evidence does not clearly suggest that IGRAs are better than tuberculin skin test (TST) in identifying individuals with IMID who could benefit from LTBI treatment. To date, no studies have been done on the predictive value of IGRAs in IMID patients. Important questions remain unanswered as to the impact of immunosuppressive medications and the impact of type of IMID on IGRA performance. SUMMARY: Despite the lack of clear evidence, there is an increasing tendency for guidelines to prefer IGRA over TST in IMIDs or to recommend both TST and IGRA to enhance sensitivity. We believe the use of either test is acceptable for LTBI screening. Clinicians could consider starting with IGRAs in individuals with a history of Bacille Calmette-Guérin (BCG) vaccination after infancy or with repeated BCG vaccinations. When the index of suspicion for LTBI is high, both IGRA and TST could be performed, especially prior to initiating TNF-α inhibitor therapy. Regardless of the test used, it is important to remember that in the face of immune-suppression, both IGRA and TST can be falsely negative and are thus only diagnostic aids - they will need to be interpreted with other clinical and risk factor data.
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How this classification was reachedexpand
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".