Feasibility and Diagnostic Utility of Antigen-Specific Interferon-γ Responses for Rapid Immunodiagnosis of Tuberculosis Using Induced Sputum
Bibliographic record
Abstract
BACKGROUND: The diagnosis of smear-negative or sputum-scarce tuberculosis (TB) is problematic as culture takes several weeks and representative biological samples are difficult to obtain. RD-1 antigen-specific interferon-gamma release assays (IGRAs) are sensitive and specific blood-based tests for the diagnosis of M. tuberculosis infection. The feasibility and diagnostic utility of this rapid immunodiagnostic assay, using cells from induced sputum, is unknown. METHODOLOGY/PRINCIPAL FINDINGS: Cells isolated from induced sputum were co-cultured with ESAT-6 and CFP-10 antigens using a standardized enzyme-linked immunospot (ELISPOT) assay (T-SPOT.TB) in 101 consecutively recruited TB suspects or non-TB controls. An optimization phase using 28 samples was followed by a validation phase using samples from 73 participants (20 with definite or probable TB, and 48 with non-TB). Despite optimization of sputum processing 65/73 (89%) of the IGRAs in the validation phase were inconclusive. 44/73 (60%) tests failed due to sputum induction-related factors [sputum induction-related adverse events (n = 5), inadequate sputum volume (n = 8), non-homogenisable sputum (n = 7), and insufficient numbers of cells to perform the assay (n = 24)], whilst 20/73 (27%) tests failed due T-SPOT.TB assay-related factors [excessive debris precluding reading of spots in the ELISPOT well (n = 6), failure of the positive control (n = 11), or high spot count in the negative control (n = 3)]. Only 8/73 (11%) of the available samples could therefore be correctly categorized (7 definite or probable TB, and 1 non-TB patient). Thus, 13/20 (65%) of the definite or probable TB cases remained undiagnosed. CONCLUSIONS/SIGNIFICANCE: Rapid immunodiagnosis of pulmonary TB by antigen-specific IFN-gamma ELISPOT responses, using cells from induced sputum, is possible. However, the test, in its current ELISPOT format, is not clinically useful because the majority of the assays are inconclusive.
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.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".