Prevalence of Abnormal Radiological Findings in Health Care Workers with Latent Tuberculosis Infection and Correlations with T Cell Immune Response
Bibliographic record
Abstract
BACKGROUND: More than half of all health care workers (HCWs) in high TB-incidence, low and middle income countries are latently infected with tuberculosis (TB). We determined radiological lesions in a cohort of HCWs with latent TB infection (LTBI) in India, and determined their association with demographic, occupational and T-cell immune response variables. METHODOLOGY: We obtained chest radiographs of HCWs who had undergone tuberculin skin test (TST) and QuantiFERON-TB Gold In Tube (QFT), an interferon-gamma release assay, in a previous cross-sectional study, and were diagnosed to have LTBI because they were positive by either TST or QFT, but had no evidence of clinical disease. Two observers independently interpreted these radiographs using a standardized data form and any discordance between them resolved by a third observer. The radiological diagnostic categories (normal, suggestive of inactive TB, and suggestive of active TB) were compared with results of TST, QFT assay, demographic, and occupational covariates. RESULTS: A total of 330 HCWs with positive TST or QFT underwent standard chest radiography. Of these 330, 113 radiographs (34.2%) were finally classified as normal, 206 (62.4%) had lesions suggestive of inactive TB, and 11 (3.4%) had features suggestive of active TB. The mean TST indurations and interferon-gamma levels in the HCWs in these three categories were not significantly different. None of the demographic or occupational covariates was associated with prevalence of inactive TB lesions on chest radiography. CONCLUSION/SIGNIFICANCE: In a high TB incidence setting, nearly two-thirds of HCWs with latent TB infection had abnormal radiographic findings, and these findings had no clear correlation with T cell immune responses. Further studies are needed to verify these findings and to identify the causes and prognosis of radiologic abnormalities in health care workers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".