Parasitic infection may be associated with discordant responses to QuantiFERON and tuberculin skin test in apparently healthy children and adolescents in a tuberculosis endemic setting, Ethiopia
Bibliographic record
Abstract
BACKGROUND: M. tuberculosis remains one of the world's deadliest pathogens in part because of its ability to establish persistent, latent infections, which can later reactivate to cause disease. In regions of the globe where disease is endemic, as much as 50% of the population is thought to be latently infected, complicating diagnosis and tuberculosis control. The tools most commonly used for diagnosis of latent M. tuberculosis infection are the tuberculin skin test and the newer interferon-gamma release assays, both of which rely on an antigen-specific memory response as an indicator of infection. It is clear that the two tests, do not always give concordant results, but the factors leading to this are only partially understood. METHODS: In this study we examined 245 healthy school children aged from 12 to 20 years from Addis Ababa, a tuberculosis-endemic region, characterised them with regard to response in the tuberculin skin test and QuantIFERON™ test and assessed factors that might contribute to discordant responses. RESULTS: Although concordance between the tests was generally fair (90% concordance), there was a subset of children who had a positive QuantIFERON™ result but a negative tuberculin skin test. After analysis of multiple parameters the data suggest that discordance was most strongly associated with the presence of parasites in the stool. CONCLUSIONS: Parasitic gut infections are frequent in most regions where M. tuberculosis is endemic. This study, while preliminary, suggests that the tuberculin skin test should be interpreted with caution where this may be the case.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".