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Record W2911326280 · doi:10.1111/jpc.14338

Interpretation and management of discordant tuberculin skin test and interferon‐gamma release assays results in children

2019· letter· en· W2911326280 on OpenAlexaff
Thomas Volkman, Hamish Graham, Ingrid Laemmle‐Ruff, Shidan Tosif, Marc Tebruegge, Sarath Ranganathan, Nigel Curtis

Bibliographic record

VenueJournal of Paediatrics and Child Health · 2019
Typeletter
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineTuberculinVaccinationInterferon gamma release assayTuberculosisQuantiFERONBCG vaccineImmunologyTuberculosis diagnosisPediatricsMycobacterium tuberculosisLatent tuberculosisPathology

Abstract

fetched live from OpenAlex

We read with interest the retrospective analysis by Elliot et al.1 comparing the results of tuberculin skin test (TST) and QuantiFERON Gold In-Tube assays in children of a refugee background. Interpretation of TST and interferon-gamma release assays (IGRA) is a perpetual challenge for those working in child tuberculosis (TB) and immigrant health services, and we commend the authors' attempt to provide guidance. However, we have a different interpretation of the study findings and the implications for practice and policy. As highlighted by the authors, discordant results are common and problematic. This study suggests that clinicians in the Illawarra-Shoalhaven region place greater weight on the result of IGRA than TST results. The majority (87.2% (41/47)) of TST+/IGRA− discordant children were not offered preventive therapy, compared with 12.5% (2/16) of TST−/IGRA+ patients. This indicates an assumption that TST+/IGRA discordance reflects false-positive TST results (due to prior Bacille Calmette Guerin (BCG) vaccination or non-tuberculous mycobacterial exposure) rather than false-negative IGRA (due to imperfect sensitivity). We recognise that the decision to treat was primarily based on clinician perception of risk in this observational study. However, false-positive TSTs related to BCG vaccination are uncommon. A meta-analysis of more than 240 000 subjects vaccinated with BCG in infancy (as is common for immigrant children in Australia) found that only 8.5% had a positive TST result attributable to BCG vaccination and that the effect of BCG on TST results waned quickly over time.2 Furthermore, immunological studies provide strong evidence that a significant proportion of TST+/IGRA− discordant patients are, in fact, infected with Mycobacterium tuberculosis.3 As the authors note, there is no gold standard for TB infection. Therefore, using IGRA as a standard against which to assess TST sensitivity is inappropriate. TST and IGRA are both imperfect screening tests for TB infection, and there is compelling evidence for the limited sensitivity of IGRA in both active TB disease and latent TB infection (LTBI).4 The limitations of IGRA are particularly relevant for infants and young children,5 and national and international guidelines therefore continue to advise the use of TST in preference to IGRA for screening children under 5 years of age.6 Discordant results in this age group, especially those children who have received BCG at birth, is especially problematic given that they will potentially benefit the most from preventive therapy as they have the highest risk to progress to active TB disease. Missing LTBI and thereby the opportunity to provide preventive therapy has far greater implications in children than adults as they are more likely to develop TB disease, especially severe disease. Based on the current evidence, the safest option for managing children with a positive IGRA or TST, including those with discordant results, is to offer preventive therapy.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.012
GPT teacher head0.300
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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