The Incidence of Arterial and Venous Thrombosis in Antineutrophil Cytoplasmic Antibody–associated Vasculitis
Bibliographic record
Abstract
To the Editor: We read with interest in The Journal of Rheumatology the article by Kang, et al , “High Incidence of Arterial and Venous Thrombosis in Antineutrophil Cytoplasmic Antibody-associated Vasculitis,”1 which reported a dramatically high incidence of arterial (ATE) and venous thrombosis events (VTE) in a hospital-based cohort of patients with antineutrophil cytoplasmic antibody–associated vasculitis (AAV). The study generally supports the previously reported increased risk of ATE and VTE in patients affected by AAV2–8, but has a number of inaccuracies and methodological issues that inflate the incidence rates of ATE and VTE. First, the authors compared clinical and laboratory features at baseline between groups defined by events that occurred during the followup (ATE vs no ATE, and VTE vs no VTE, Table 1 and … Address correspondence to Dr. D. Cornec, CHU Brest, Rheumatology, Boulevard Tanguy Prigent, Brest, 29609, France. E-mail: divi.cornec{at}chu-brest.fr
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".