A Changing Anti-Neutrophil Cytoplasmic Antibody Profile in a Patient With a Diagnosis of Eosinophilic Granulomatosis With Polyangiitis
Bibliographic record
Abstract
This report describes a hitherto unique case of eosinophilic granulomatosis with polyangiitis (EGPA), a subtype of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis. The patient was an 81-year-old man whose clinical course involved notable changes in the ANCA profile, specifically a transition from positive proteinase 3 (PR3)-ANCA to myeloperoxidase (MPO)-ANCA, followed by simultaneous positivity for both. The patient's medical history included bronchial asthma, allergic rhinitis, sinusitis, and multiple comorbidities. Despite being initially PR3-ANCA-positive, subsequent admissions demonstrated MPO-ANCA positivity along with eosinophilic manifestations, highlighting the complexity of diagnosis of EGPA. Diagnostic evaluation included imaging, serological markers, and clinical symptoms, which collectively supported the classification of EGPA. Notably, this case challenges the conventional diagnostic paradigms and emphasizes the evolving nature of ANCA profiles in vasculitis. The shift in ANCA profile prompted a reevaluation of the patient's diagnosis and treatment strategy. This case underscores the importance of considering fluctuations in ANCA in patients with a diagnosis of EGPA, management decisions, and potential implications for disease progression. Further research is warranted to elucidate the mechanisms underlying changes in ANCA and their clinical significance in vasculitis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".