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Record W2994561572 · doi:10.1093/cid/ciz1138

Tuberculosis Disease in Children and Adolescents on Therapy With Antitumor Necrosis Factor-ɑ Agents: A Collaborative, Multicenter Paediatric Tuberculosis Network European Trials Group (ptbnet) Study

2019· article· en· W2994561572 on OpenAlexfundno aff
Antoni Noguera‐Julián, Joan Calzada‐Hernández, Folke Brinkmann, Robindra Basu Roy, Olga Bilogortseva, Michael Buettcher, Isabel Carvalho, Vira Chechenyeva, Lola Falcón-Neyra, Florian Göetzinger, Carmelo Guerrero-Laleona, Péter Hoffmann, Marija Jelušić, Tim Niehues, Iveta Ozere, Fiona Shackley, Elena Sučilienė, Steven Welch, Elisabeth H. Schölvinck, Nicole Ritz, Marc Tebruegge

Bibliographic record

VenueClinical Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersMedical Research CouncilSociedad Española de Reumatología PediátricaSociedad Española de ReumatologíaGeneralitat de CatalunyaNational Institute for Health and Care ResearchMcMaster University
KeywordsMedicineTuberculosisLatent tuberculosisMiliary tuberculosisAdalimumabInternal medicineDiseaseTuberculinPediatricsPopulationMycobacterium tuberculosisPathology

Abstract

fetched live from OpenAlex

BACKGROUND: In adults, anti-tumor necrosis factor-α (TNF-α) therapy is associated with progression of latent tuberculosis (TB) infection (LTBI) to TB disease, but pediatric data are limited. METHODS: Retrospective multicenter study within the Paediatric Tuberculosis Network European Trials Group, capturing patients <18 years who developed TB disease during anti-TNF-α therapy. RESULTS: Sixty-six tertiary healthcare institutions providing care for children with TB participated. Nineteen cases were identified: Crohn's disease (n = 8; 42%) and juvenile idiopathic arthritis (n = 6; 32%) were the commonest underlying conditions. Immune-based TB screening (tuberculin skin test and/or interferon-γ release assay) was performed in 15 patients before commencing anti-TNF-α therapy but only identified 1 LTBI case; 13 patients were already receiving immunosuppressants at the time of screening. The median interval between starting anti-TNF-α therapy and TB diagnosis was 13.1 (IQR, 7.1-20.3) months. All cases presented with severe disease, predominantly miliary TB (n = 14; 78%). One case was diagnosed postmortem. TB was microbiologically confirmed in 15 cases (79%). The median duration of anti-TB treatment was 50 (IQR, 46-66) weeks. Five of 15 (33%) cases who had completed TB treatment had long-term sequelae. CONCLUSIONS: LTBI screening is frequently false-negative in this patient population, likely due to immunosuppressants impairing test performance. Therefore, patients with immune-mediated diseases should be screened for LTBI at the point of diagnosis, before commencing immunosuppressive medication. Children on anti-TNF-α therapy are prone to severe TB disease and significant long-term morbidity. Those observations underscore the need for robust LTBI screening programs in this high-risk patient population, even in low-TB-prevalence settings.

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)0.009
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.037
GPT teacher head0.370
Teacher spread0.333 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2019
Admission routes1
Has abstractyes

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