Thyroid Dysfunction in Patients with Antineutrophil Cytoplasmic Antibody–associated Vasculitis: A Monocentric Retrospective Study
Bibliographic record
Abstract
To the Editor: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is characterized by necrotizing vasculitis in small-sized vessels such as arterioles, capillaries, and venules1. The possibility of a link between thyroid dysfunction and autoimmunity has been considered and its prevalence was reported differently according to each autoimmune disease2. Given that AAV is one of the systemic autoimmune diseases affecting most major organs3, and there is cross-reactivity between thyroid peroxidase and myeloperoxidase (MPO) molecules4, the prevalence of thyroid dysfunction, including autoimmune thyroiditis, may be increased in patients with AAV. Previous studies reported the higher prevalence of thyroid dysfunction in patients with AAV than in the general population5,6,7. However, there was no study on the prevalence of thyroid dysfunction in AAV patients in Korea. In this study, we investigate the prevalence of thyroid dysfunction and searched for the predictors at diagnosis of its development during followup for 3 months or greater in Korean patients with AAV. We retrospectively reviewed the medical records of 186 patients with AAV, who were classified as having AAV at the Department of … Address correspondence to Prof. S.W. Lee, Division of Rheumatology, Department of Internal Medicine, and Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun–gu, Seoul 03722, South Korea. E-mail: sangwonlee{at}yuhs.ac
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".