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Record W2123748656 · doi:10.1016/j.jegh.2013.03.003

Trajectories of tuberculosis-specific interferon-gamma release assay responses among medical and nursing students in rural India

2013· article· en· W2123748656 on OpenAlexafffund
Alice Zwerling, Rajnish Joshi, Shriprakash Kalantri, Gajalakshmi Dakshinamoorthy, Maryada Venkatarami Reddy, Andrea Benedetti, Kevin Schwartzman, Dick Menzies, Madhukar Pai

Bibliographic record

VenueJournal of Epidemiology and Global Health · 2013
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMontreal Heart InstituteMcGill University
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMedicineTuberculosisIncidence (geometry)Health careInterferon γInterferon gammaTuberculinInternal medicineImmunologyPathologyImmune system

Abstract

fetched live from OpenAlex

BACKGROUND: Interferon gamma release assays (IGRAs) have been shown to be highly dynamic tests when used in serial testing for TB infection. However, there is little information demonstrating a clear association between TB exposure and IGRA responses over time, particularly in high TB incidence settings. OBJECTIVES: To assess whether QuantiFERON-TB Gold In-Tube (QFT) responses are associated with occupational TB exposures in a cohort of young health care trainees in India. METHODS: All medical and nursing students at Mahatma Gandhi Institute of Medical Sciences were approached. Participants were followed up for 18 months; QFT was performed 4 times, once every 6 months. Various modeling approaches were used to define IFN-gamma trajectories and correlations with TB exposure. RESULTS: Among 270 medical and nursing trainees, high rates of conversions (6.3-20.9%) and reversions (20.0-26.2%) were found depending on the definitions used. Stable converters were more likely to have had TB exposure in hospital pre-study. Recent occupational exposures were not consistently associated with QFT responses over time. CONCLUSION: IFN-gamma responses and rates of change could not be explained by occupational exposure investigated. High conversion and subsequent reversion rates suggest many health care workers (HCWs) would revert in the absence of treatment, either by clearing the infection naturally or due to fluctuations in the underlying immunological response and/or poor assay reproducibility. QFT may not be an ideal diagnostic test for repeated screening of HCWs in a high TB incidence setting.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.418
Teacher spread0.385 · 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 teacher head, not a consensus.

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

Citations21
Published2013
Admission routes2
Has abstractyes

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