The Sound of Interconnectivity; The European Vasculitis Society 2022 Report
Bibliographic record
Abstract
The first European Vasculitis Society (EUVAS) meeting report was published in 2017. Herein, we report on developments in the past 5 years which were greatly influenced by the pandemic. The adaptability to engage virtually, at this critical time in society, embodies the importance of networks and underscores the role of global collaborations. We outline state-of-the-art webinar topics, updates on developments in the last 5 years, and proposals for agendas going forward. A host of newly reported clinical trials is shaping practice on steroid minimization, maintenance strategies, and the role of newer therapies. To guide longer-term strategies, a longitudinal 10-year study investigating relapse, comorbidity, malignancy, and survival rates is at an advanced stage. Disease assessment studies are refining classification criteria to differentiate forms of vasculitis more fully. A large international validation study on the histologic classification of anti-neutrophil cytoplasmic antibody (ANCA) glomerulonephritis, recruiting new multicenter sites and comparing results with the Kidney Risk Score, has been conducted. Eosinophilic granulomatosis with polyangiitis (EGPA) genomics offers potential pathogenic subset and therapeutic insights. Among biomarkers, ANCA testing is favoring immunoassay as the preferred method for diagnostic evaluation. Consolidated development of European registries is progressing with an integrated framework to analyze large clinical data sets on an unprecedented scale.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.014 |
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".