Serum calprotectin and renal function decline in ANCA-associated vasculitides: a post hoc analysis of MAINRITSAN trial
Bibliographic record
Abstract
Objective Serum calprotectin appears to be an interesting biomarker associated with renal vascular disease activity in antineutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV). The aim of this study was to assess whether serum calprotectin levels can predict decline in renal function in AAV patients receiving maintenance therapy. Methods Serum calprotectin levels were assessed at inclusion and month 6 in AAV patients, in complete remission after induction therapy, randomly assigned to rituximab or azathioprine. Renal function decline was defined as a 25% decrease in estimated glomerular filtration rate (eGFR) and a change in the eGFR category, or a decrease of 15 mL/min/1.73 m2. Relapse was defined as a Birmingham Vasculitis Activity Score >0 attributable to active vasculitis. Results Seventy-six AAV were included. Serum calprotectin increased from baseline to month 6 in patients with renal function decline (7940 (−226.0, 28 691) ng/ml vs −4800 (−18 777, 3708) ng/ml; p<0.001). An increase of calprotectin level was associated with a higher risk of subsequent renal function decline even after adjustment (OR 6.50 (95% CI 1.7 to 24.9) p=0.006). A significantly higher risk of relapse was observed in proteinase 3- AAV patients with an increase of serum calprotectin levels (OR 5.6 (95% CI 1.0 to 31.2), p=0.03). Conclusion An increase in serum calprotectin by month 6 compared with inclusion during remission-maintenance therapy in AAV was associated with a higher risk of renal function decline in the following 12 months. Trial registration number NCT00748644 .
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".