Insights into Geographic Patterns, Urban-Rural Contrasts, and Health Care Disparities in Glomerular Disease Incidence in a Canadian Province
Bibliographic record
Abstract
Rationale & Objective: Glomerular diseases (GDs) are a group of immune-mediated or genetic diseases that involve the filtering units of the kidneys, or glomeruli. Using centralized provincial kidney pathology records and census data, we aimed to examine the incidence and temporal trend of GDs in Saskatchewan, Canada and understand rural/urban differences in GD distribution. Study Design: Population-based epidemiologic study. Setting & Participants: All adult patients who underwent kidney biopsies in Saskatchewan, Canada, from 2002-2018. Exposures or Predictors: Biopsy diagnosis, 3-digit postal codes, laboratory parameters, dialysis initiation dates, and mortality data. Outcomes: Incidence of primary GD, dialysis initiation, and all-cause mortality. Analytical Approach: Regional variations in GD were analyzed using SaTScan v10.1.3 software. Incidence trends, rural/urban differences, and geospatial clustering were evaluated. Ethics approval was obtained from the provincial research and ethics board. Results: was identified for lupus nephropathy, with an incidence rate ratio of 1.73, a relative risk of 2.7, and a log likelihood ratio of 13.87. Limitations: Biopsies were dependent on the threshold of the ordering physician. Likely, frail and elderly patients and patients with early onset glomerulonephritis, late presentations, and higher bleeding risk were not biopsied, which led to an underrepresentation of these groups. Conclusions: The incidence and relative burden of GDs have increased over time in Saskatchewan, with notable rural/urban differences. We identified a geographic cluster for lupus nephropathy encompassing rural and urban areas. Patients in rural and remote areas had higher dialysis transition rates, and mortality rates were relatively higher in urban areas. Addressing and understanding the multifaceted factors driving these disparities are essential steps toward easing the burden of GDs on impacted communities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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".