Patterns of Disease Progression Among Children and Adults with IgA Nephropathy/Vasculitis in CureGN
Bibliographic record
Abstract
Background: IgA nephropathy (IgAN) is the most common glomerular disease world-wide. Identifying demographic and clinical characteristics that place patients at increased risk for disease progression is critical for optimizing therapeutic interventions and targeting clinical trials. Methods: CureGN is a multi-center cohort study of children and adults with biopsyproven glomerular disease, including 823 patients with IgA nephropathy/vasculitis with nephritis (IgAN/IgAVN). We used latent class analysis to segregate 316 incident and prevalent patients, with at least 4 UPCR measurements within the first 2 years of their follow-up, into 3 groups based on longitudinal UPCR trajectories over 2 years. Using Cox proportional hazard models, we then modeled disease progression, defined as the composite outcome of 40% eGFR decline or kidney failure (initiation of dialysis, transplant, or 2 eGFRs <15ml/min/1.73m2), as a function of UPCR trajectory group while adjusting for age, eGFR at enrollment, use of immunosuppression, RAAS blockade, and IgAN/IgAVN status. Results: 149 incident and 167 prevalent patients (enrolled <6 months and > 6 months from biopsy (max 5 years), respectively) were followed for a median of 6.1 (IQR 4.5,6.9) years. Three groups were identified based on UPCR trajectories (Figure). Among incident patients, those with the highest UPCR (group 3) demonstrated faster eGFR decline (median (IQR) decline -4.0 (-7.3,-0.1) ml/min/1.73m2/year compared to +1.3 (-2.0,+3.1) in group 1 and -0.9 (-3.9,+1.7) in group 2) and had 5.4-times higher hazard of progressing to the composite outcome compared to Groups 1+2 combined (p=0.0016). Among prevalent patients, those with the highest UPCR (Group 3) had 3.9-times higher hazard of progressing to the composite outcome (p=0.0049). No association between immunosuppression use and the composite outcome was detected. Conclusions: In both incident and prevalent IgAN/IgAVN cohorts proteinuria trajectories define patients into distinct clinical groups and are a strong independent predictor of disease progression. Funding: NIDDK Support
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".