The Histopathological Classification of ANCA-associated Glomerulonephritis Comes of Age
Bibliographic record
Abstract
The antineutrophil cytoplasm antibody (ANCA)-associated vasculitides (AAV) are multisystem disorders characterized by necrotizing inflammation of blood vessels, and are associated with an untreated mortality of around 90%1. These disorders include granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), eosinophilic granulomatosis with polyangiitis (EGPA), and renal limited vasculitis (RLV)2. Renal manifestations of AAV, which commonly include rapidly progressive glomerulonephritis, result in endstage renal failure or death in 40% of patients3. Despite the introduction of newer biological therapies, treatment continues to cause significant morbidity and mortality, and has been associated with more deaths at 1 year than the disease process itself4. A major challenge in the management of patients with renal AAV remains the identification of factors, both clinical and histopathological, which are predictive of response to therapy, risk of relapse, and renal and patient survival. Recognition of such factors would aid the implementation of patient-tailored therapy. Clinical factors that have been demonstrated to correlate with the prognosis of renal AAV include age, with increasing age correlating with poorer outcome; and presenting creatinine, with a better prognosis in patients presenting with a lower serum creatinine5. These clinical factors cannot, however, be considered in isolation. The “gold standard” for diagnosis of renal AAV remains the renal biopsy. A number of histopathological factors have been reported to correlate with renal prognosis6. A higher percentage of normal glomeruli has been well established as being predictive of better renal outcome6,7. A greater percentage of cellular crescents has been reported as predictive of a better response to therapy7. … Address correspondence to Prof. C.D. Pusey, Renal and Vascular Inflammation Section, Department of Medicine, Imperial College London, Hammersmith Campus, Du Cane Road, London W12 0NN, UK. E-mail: c.pusey{at}imperial.ac.uk
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".