Bibliographic record
Abstract
Background: IgA nephropathy [IgAN] carries a high lifetime risk of kidney failure. Population-level studies facilitate analysis of health care utilization that may impact IgAN diagnosis and outcomes. Methods: We investigated time to biopsy using a population-level cohort of adults ≥18 years with IgAN in the provincial Glomerulonephritis [GN] Registry. The registry captures all patients with a biopsy diagnosis of IgAN from January 1, 2000 to December 31, 2020. Results: The GN Registry captured 1382 individuals with primary IgAN from 2000 to 2020. Between 2000-2005, the mean time from first nephrology visit to biopsy was 332 days, which increased to 713 days between 2015-2020. Over time, we observed increasing age (from mean of 43 to 46 years), decreasing eGFR (from median of 62 to 49 ml/min/1.73m2) and increasing baseline comorbidities at the time of biopsy (Table 1). Patients with a time from first nephrology visit to biopsy greater than 365 days had a 20-year ESKD risk of ≈ 50%; those with a time from first visit to biopsy between 15 and 60 days had a 20-year ESKD risk of ≈ 40% (figure 2). Conclusion: We observed an unexpected increase in the time to kidney biopsy in a population cohort of adult IgAN patients. Consistent with this, patients were older, more comorbid and had more advanced disease with lower eGFR at the time of biopsy. We are integrating MEST-C scores to see if this delay in diagnosis is associated with more advanced sclerotic disease at biopsy. We are currently investigating clinical, health system and socioeconomic factors that may explain this trend and difference in ESKD risk. Funding: Commercial Support - Novartis AGTable 1
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".