Temporal and Demographic Trends in Glomerular Disease Epidemiology in the Southeastern United States, 1986–2015
Bibliographic record
Abstract
Background and objectives Large-scale, contemporary studies exploring glomerular disease epidemiology in the United States are lacking. We aimed to determine 30-year temporal and demographic trends in renal biopsy glomerular disease diagnosis frequencies in the southeastern United States. Design, setting, participants, & measurements In this cross-sectional, observational study, we identified all patients with a native kidney biopsy specimen showing one of 18 widely recognized glomerular disease diagnoses referred to the University of North Carolina Chapel Hill Division of Nephropathology between 1986 and 2015. Biopsy era (1986–1995, 1996–2005, and 2006–2015) and demographics (age, sex, and race) were our primary and secondary predictors, respectively, and the relative frequency of each glomerular disease diagnosis was our primary outcome. Results Among 21,374 patients (mean age =48.3±18.3 years old; 50.8% men; 56.8% white; 38.3% black; 2.8% Latino; 1.4% Asian; 0.8% other), the frequency of diabetic glomerulosclerosis in renal biopsy specimens increased dramatically over the three decades (5.5%, 11.4%, and 19.1% of diagnoses, respectively; P for trend <0.001). The frequency of FSGS initially increased but then declined (22.6%, 27.2%, and 24.7%, respectively; P for trend =0.64). The frequencies of other common glomerular disease subtypes remained stable (IgA nephropathy and ANCA/pauci-immune GN) or declined (minimal change disease, membranous nephropathy, membranoproliferative GN, and lupus nephritis). These temporal trends were largely preserved within all demographic subgroups, although cross-sectional frequency distributions differed according to age, sex, and race. Conclusions We identified significant changes in relative renal biopsy frequencies of many glomerular disease subtypes over three decades. Temporal trends were consistently observed within all major demographic groups, although relative predominance of individual glomerular disease subtypes differed according to patient age, sex, and race. We propose that exploration of behavioral and environmental exposures that likely underlie these findings should be the focus of future hypothesis-driven research.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".