Kidney Disease Among Registered Métis Citizens of Ontario: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: Indigenous peoples in Canada have higher rates of kidney disease than non-Indigenous Canadians. However, little is known about the risk of kidney disease specifically in the Métis population in Canada. Objective: To compare the prevalence of chronic kidney disease and incidence of acute kidney injury and end-stage kidney disease among registered Métis citizens in Ontario and a matched sample from the general Ontario population. Design: Population-based, retrospective cohort study using data from the Métis Nation of Ontario’s Citizenship Registry and administrative databases. Setting: Ontario, Canada; 2003-2013. Patients: Ontario residents ≥18 years. Measurements: Prevalence of chronic kidney disease and incidence of acute kidney injury and end-stage kidney disease. Secondary outcomes among patients hospitalized with acute kidney injury included non-recovery of kidney function and mortality within 1 year of discharge. Methods: Database codes and laboratory values were used to determine study outcomes. Métis citizens were matched (1:4) to Ontario residents on age, sex, and area of residence. The analysis included 12 229 registered Métis citizens and 48 916 adults from the general population. Results: We found the prevalence of chronic kidney disease was slightly higher among Métis citizens compared with the general population (3.1% vs 2.6%, P = 0.002). The incidence of acute kidney injury was 1.2 per 1000 person-years in both Métis citizens and the general population ( P = 0.54). Of those hospitalized with acute kidney injury, outcomes were similar among Métis citizens and the general population except 1-year mortality, which was higher for Métis citizens (24.5% vs 15.3%, P = 0.03). The incidence of end-stage kidney disease did not differ between groups (<3.0 per 10 000 person-years, P = 0.73). Limitations: The Métis Nation of Ontario Citizenship Registry only captures about 20% of Métis people in Ontario. Administrative health care codes used to identify kidney disease are highly specific but have low sensitivity. Conclusions: Rates of kidney disease were similar or slightly higher for Métis citizens in Ontario compared with the matched general population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".