Assessing the Performance of the Birmingham Vasculitis Activity Score at Diagnosis for Children with Antineutrophil Cytoplasmic Antibody-associated Vasculitis in A Registry for Childhood Vasculitis (ARChiVe)
Bibliographic record
Abstract
OBJECTIVE: There are no validated tools for measuring disease activity in pediatric vasculitis. The Birmingham Vasculitis Activity Score (BVAS) is a valid disease activity tool in adult vasculitis. Version 3 (BVAS v.3) correlates well with physician's global assessment (PGA), treatment decision, and C-reactive protein in adults. The utility of BVAS v.3 in pediatric vasculitis is not known. We assessed the association of BVAS v.3 scores with PGA, treatment decision, and erythrocyte sedimentation rate (ESR) at diagnosis in pediatric antineutrophil cytoplasmic antibody-associated vasculitis (AAV). METHODS: Children with AAV diagnosed between 2004 and 2010 at all ARChiVe centers were eligible. BVAS v.3 scores were calculated with a standardized online tool (www.vasculitis.org). Spearman's rank correlation coefficient (r(s)) was used to test the strength of association between BVAS v.3 and PGA, treatment decision, and ESR. RESULTS: A total of 152 patients were included. The physician diagnosis of these patients was predominantly granulomatosis with polyangiitis (n = 99). The median BVAS v.3 score was 18.0 (range 0-40). The BVAS v.3 correlations were r(s) = 0.379 (95% CI 0.233 to 0.509) with PGA, r(s) = 0.521 (95% CI 0.393 to 0.629) with treatment decision, and r(s) = 0.403 (95% CI 0.253 to 0.533) with ESR. CONCLUSION: Applied to children with AAV, BVAS v.3 had a weak correlation with PGA and moderate correlation with both ESR and treatment decision. Prospective evaluation of BVAS v.3 and/or pediatric-specific modifications to BVAS v.3 may be required before it can be formalized as a disease activity assessment tool in pediatric AAV.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".