Estimating the Change in Renal Function During the First Year of Therapy in ANCA-Associated Vasculitis
Bibliographic record
Abstract
Introduction Studies in antineutrophil cytoplasmic autoantibody (ANCA)–associated vasculitis (AAV) consistently show that the months following diagnosis have the greatest impact on the long-term renal function. Yet, it remains uncertain how much early gain should be expected with treatment. We sought to determine the factors associated with the change in glomerular filtration rate (GFR) throughout the first year. Methods We retrospectively reviewed patients from 3 university hospitals who received treatments. We assessed the proportions of glomeruli with crescents, with global sclerosis, the AAV glomerulonephritis classification, the severity of chronic vascular and tubulo-interstitial disease, and the presence of acute tubular injury (ATI). We used repeated-measures analyses of variance (ANOVAs) to determine factors associated with the change in GFR throughout the first year. Results There were 162 individuals with AAV identified, 96 with a valid renal biopsy and 82 with at least 12 months of follow-up. The initial GFR of 30 ± 25 ml/min per 1.73 m 2 rose by 15 ± 20 during the first year. The severity of pathology findings, myeloperoxidase positivity, and those with kidney- and lung-limited disease presented with a lower GFR. Younger patients with a lower initial GFR and the presence of ATI correlated with a greater increase in GFR by 12 months. A higher proportion of crescents did not predict the change in GFR, contrary to global glomerulosclerosis, where each 10% increase added a loss of 2.7 ± 1.3 ml/min per 1.73 m 2 per year ( P = 0.03). These factors remained independent of each other. Conclusion Multiple factors influence renal recovery during the first year of therapy. Estimating the change in GFR early on will help identify and reassess outliers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".