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Record W2178016626

Factors associated with humoral response to ESAT-6, 38 kDa and 14 kDa in patients with a spectrum of tuberculosis.

2003· article· en· W2178016626 on OpenAlexaffabout
V M C Silva, Ganga V. Kanaujia, Maria Laura Gennaro, Dick Menzies

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMedicineTuberculosisAntigenImmunologyMycobacterium tuberculosisDiseaseESAT-6SerologyMultivariate analysisInternal medicineAntibodyPathology
DOInot available

Abstract

fetched live from OpenAlex

SETTING: Tertiary care chest hospital in Montreal, Canada, where the average annual incidence of TB is 10/100,000 population. OBJECTIVES: To evaluate the clinical correlates of humoral response to three Mycobacterium tuberculosis antigens. METHODS: Humoral response to three M. tuberculosis antigens, 38 kDa, 14 kDa and ESAT-6, was measured with ELISA in patients with a spectrum of TB-related conditions. The association of positive tests for each antigen, defined with receiver operator characteristics (ROC) analysis, and patient characteristics was assessed in multivariate regression. RESULTS: A total of 383 patients underwent serologic testing. In multivariate analysis, humoral response to 38 kDa was associated with active disease, response to 14 kDa was associated with inactive TB and female sex, and response to ESAT-6 with inactive TB, female sex, prior contact with TB, and recent arrival in Canada from high prevalence countries. CONCLUSIONS: Response to the 38 kDa antigen was associated with current active disease, and was very different from response to the 14 kDa and ESAT-6 antigens. These latter two antigens were associated with risk factors for future active, but not current disease, suggesting that they might be useful to identify persons with higher risk of reactivation of latent TB.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.259
Teacher spread0.228 · 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.

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

Citations98
Published2003
Admission routes2
Has abstractyes

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