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Record W2747227097 · doi:10.1093/rheumatology/kex115

WS1_1 Sputum Anti-neutrophil Cytoplasmic Antibodies (ANCA) in Eosinophilic Granulamatosis and Polyangiitis (eGPA)

2017· article· en· W2747227097 on OpenAlexaff
Sruthi Thomas, Manali Mukherjee, Svetlana Davychenko, Hui Fang Lim, Melanie Kjarsgaard, Katherine Radford, Diane M. Robins, Nader Khalidi, Parameswaran Nair

Bibliographic record

VenueLara D. Veeken · 2017
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Disorders and Syndromes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineGranulomatosis with polyangiitisEosinophilicSputumImmunologyAntibodyAnti-neutrophil cytoplasmic antibodyEosinophilInternal medicineVasculitisPathologyAsthmaTuberculosis

Abstract

fetched live from OpenAlex

Objectives: Eosinophilic granulomatosis with polyangiitis (eGPA) is a systemic small-vessel vasculitis characterized by hypereosinophilia, with a pathophysiology linked to the autoinflammatory effect of anti-neutrophil cytoplasmic antiantibodies (ANCA). However, of clinically diagnosed eGPA patients only 40% are ANCA seropositive [Curr Opin Rheumatol, 2014. 26(1): p.16-23]. We hypothesized that ANCA-negative patients with severe respiratory involvement would present with ANCAs localized to the lungs. Methods: We collected matched sera and induced sputum from 20 eGPA patients (diagnosis based on 4/6 criteria by the American College of Rheumatology), 11 prednisone-dependent severe eosinophilic asthmatics, and 13 healthy volunteers. ANCA-positive patient sera were used to validate the commercial immunofluorescence (IIF) kit (Immco Diagnostics Buffalo, NY, USA) and anti-MPO ELISA. The intensity of the IIF-staining was scored by three blinded observers. Further, to negate false pANCA patterns portrayed by anti-nuclear antibodies, both ethanol, and formalin-fixed neutrophil-substrate slides, in addition to Hep-2 IIF were employed. For sputum, to reduce signal-to-noise ratio, immunoglobulins were immunoprecipitated using Protein A/G beads, and IIF was performed at 1:2 titers as per manufacturer's protocol.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.266
Teacher spread0.250 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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