Use of the T-SPOT.<i>TB</i> Assay to Detect Latent Tuberculosis Infection Among Rheumatic Disease Patients on Immunosuppressive Therapy
Bibliographic record
Abstract
OBJECTIVE: We evaluated the T-SPOT.TB assay to identify latent tuberculosis infection (LTBI) in patients with rheumatic disease receiving immunosuppressive medication including tumor necrosis factor (TNF) antagonists. METHODS: A total of 200 patients seen in the Arthritis Center at Brigham and Women's Hospital were enrolled for study. Most patients were US-born women with rheumatoid arthritis. A medical history was obtained using a questionnaire, whole blood was drawn for the T-SPOT.TB assay, and tuberculin skin testing (TST) was performed. RESULTS: Both tests were performed on 179 subjects, who had no history of a positive TST. All subjects had a strong response to the T-SPOT.TB test positive control, and there were no indeterminate results. Among these 179 subjects, 2 had a positive TST and 10 had a positive T-SPOT.TB test. No subject was positive for both tests. Patients with a positive T-SPOT.TB test did not have typical risk factors for LTBI based on clinical evaluation. CONCLUSION: The lack of concordance between the TST and the T-SPOT.TB assay may indicate that the immunoassay is more sensitive, particularly in a patient population taking immunosuppressive medications. It is equally likely that the low prevalence of LTBI in this low-risk population led to an increase in the false-positive rate despite the high sensitivity and specificity of the T-SPOT.TB assay. In the context of our patient population, the T-SPOT.TB assay is likely to be most useful in evaluation of patients with a positive TST, since these patients have a higher pretest probability of having LTBI.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".