Prevalence of Chronic Kidney Disease and Survival among Aboriginal People
Bibliographic record
Abstract
Globally, it is known that the incidence of end-stage renal disease is higher among Aboriginals, but it is unknown whether this is due to an increased prevalence of chronic kidney disease or other unidentified factors. We studied 658,664 people of non-First Nations and 14,989 people of First Nations and found that the age- and sex-adjusted prevalence of chronic kidney disease was significantly higher among those of non-First Nations compared to those of First Nations (67.5 versus 59.5 per 1000 population; P < 0.0001). However, severe chronic kidney disease (estimated glomerular filtration rate <30 ml/min per 1.73 m2) was almost two-fold higher among people of First Nations (P < 0.0001). Cox proportional hazards models suggested that compared to people of non-First Nations, those of First Nations with chronic kidney disease had a 77% increased risk of death after adjusting for age, gender, diabetes and baseline eGFR. In conclusion, whether the higher incidence of end-stage renal disease among people of First Nations is due to suboptimal management of chronic kidney disease and its associated comorbidities, more rapid loss of kidney function, or other unidentified factors remains to be determined.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".