WS1_1 Sputum Anti-neutrophil Cytoplasmic Antibodies (ANCA) in Eosinophilic Granulamatosis and Polyangiitis (eGPA)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".