Kidney disease and care among First Nations people with diabetes in Ontario: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: End-stage kidney disease is a serious complication of diabetes. We describe the prevalence of chronic kidney disease, prevalence and incidence of end-stage kidney disease and quality of care of early-stage chronic kidney disease for First Nations people with diabetes compared to other Ontarians with diabetes. METHODS: We conducted a retrospective cohort study in Ontario using linked administrative data at ICES. We included adults with incident diabetes between 1994 and 2014, and used laboratory values to identify kidney disease and quality indicators for care for early-stage disease. We compared measures in First Nations people to those in other people in Ontario, and used direct age and sex standardization. We used Cox proportional hazards regression to compare the incidence of end-stage kidney disease between groups. RESULTS: Our study included 21 968 First Nations people with diabetes. The age- and sex-standardized prevalence of chronic kidney disease was higher for First Nations people than for other Ontarians (20.7% v. 18.4%), as was the prevalence of end-stage kidney disease (2.9% v. 1.0%). The incidence of end-stage kidney disease was higher among First Nations people than among other people in Ontario (9.3 v. 4.7 events per 10 000 person-years; age- and sex-adjusted hazard ratio 2.23, 95% confidence interval 1.72-2.89). The 2 groups were similarly likely to receive recommended medications, but First Nations people were less likely to receive laboratory tests for their kidney disease. INTERPRETATION: Despite receiving similar quality of care for early-stage kidney disease, First Nations people with diabetes had higher rates of end-stage kidney disease than other Ontarians. Further research is needed to better understand contributing factors to help inform future interventions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".