Increase of Antimyeloperoxidase Antineutrophil Cytoplasmic Antibody (ANCA) in Patients with Renal ANCA-associated Vasculitis: Association with Risk to Relapse
Bibliographic record
Abstract
OBJECTIVE: The diagnostic values of antiproteinase 3 and antimyeloperoxidase tests using antineutrophil cytoplasmic antibodies (ANCA) are well established. Our study determined whether an increase in ANCA level was a predictor of disease flareup. METHODS: Our study included 126 patients with ANCA-associated renal vasculitis treated at 9 nephrology centers in Japan. The relationship between increased ANCA levels and relapse was assessed using time-dependent multivariate Cox regression models adjusted for clinically relevant factors. The outcome of interest was the time from remission to first relapse. RESULTS: During the observation period [median 41 mos, interquartile range (IQR) 23-66 mos], 118 patients (95.8%) achieved remission at least once. After achieving remission, 34 patients relapsed (21.7%). Time-dependent multivariate Cox regression models revealed that lung involvement (adjusted HR 2.29, 95% CI 1.13-4.65, p = 0.022) and increased ANCA levels (adjusted HR 17.4, 95% CI 8.42-36.0, p < 0.001) were significantly associated with relapse. The median time from ANCA level increase to relapse was 0.6 months (IQR 0-2.1 mos). CONCLUSION: In our study, an increase in ANCA level during remission was associated with a risk of disease relapse. A rise in ANCA level may be useful for guiding treatment decisions in appropriate subsets of patients with ANCA-associated vasculitis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".