Peripheral arterial disease in Ontario First Nations people with diabetes: a longitudinal population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Peripheral arterial disease is an important vascular complication of diabetes that may lead to lower-extremity amputation. We aimed to compare the treatment and complications of peripheral arterial disease between First Nations people and other people in Ontario with diabetes. METHODS: Using health care administrative databases, we identified annual cohorts, from 1995/96 to 2014/15, of all people aged 20-105 years in Ontario with a diagnosis of diabetes. We used the Indian Register to identify those who were First Nations people and compared them to all other people in Ontario. We identified revascularization procedures (angioplasty or bypass surgery) and lower-extremity amputation procedures in the 2 populations and determined the mortality rate among those who had had lower-extremity amputation. RESULTS: First Nations people received revascularization procedures at a rate comparable to that for other people in Ontario. However, they had lower-extremity amputation procedures at 3-5 times the frequency for other Ontario residents. First Nations people had higher mortality than other people in Ontario after lower-extremity amputation (adjusted hazard ratio 1.15, 95% confidence interval 1.05-1.26), with median survival of 3.5 years versus 4.1 years. INTERPRETATION: First Nations people in Ontario had a markedly increased risk for lower-extremity amputation compared to other people in Ontario, and their mortality rate after amputation was 15% higher. Future research is needed to understand what barriers First Nations people face to receive adequate peripheral arterial disease care and what interventions are necessary to achieve equitable outcomes of peripheral arterial disease for First Nations people in Ontario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".