Association between First Nations ethnicity and progression to kidney failure by presence and severity of albuminuria
Bibliographic record
Abstract
BACKGROUND: Despite a low prevalence of chronic kidney disease (estimated glomerular filtration rate [GFR]<60 mL/min per 1.73 m2), First Nations people have high rates of kidney failure requiring chronic dialysis or kidney transplantation. We sought to examine whether the presence and severity of albuminuria contributes to the progression of chronic kidney disease to kidney failure among First Nations people. METHODS: We identified all adult residents of Alberta (age≥18 yr) for whom an outpatient serum creatinine measurement was available from May 1, 2002, to Mar. 31, 2008. We determined albuminuria using urine dipsticks and categorized results as normal (i.e., no albuminuria), mild, heavy or unmeasured. Our primary outcome was progression to kidney failure (defined as the need for chronic dialysis or kidney transplantation, or a sustained doubling of serum creatinine levels). We calculated rates of progression to kidney failure by First Nations status, by estimated GFR and by albuminuria category. We determined the relative hazard of progression to kidney failure for First Nations compared with non-First Nations participants by level of albuminuria and estimated GFR. RESULTS: Of the 1 816 824 participants we identified, 48 669 (2.7%) were First Nations. First Nations people were less likely to have normal albuminuria compared with non-First Nations people (38.7% v. 56.4%). Rates of progression to kidney failure were consistently 2- to 3-fold higher among First Nations people than among non-First Nations people, across all levels of albuminuria and estimated GFRs. Compared with non-First Nations people, First Nations people with an estimated GFR of 15.0-29.9 mL/min per 1.73 m2 had the highest risk of progression to kidney failure, with similar hazard ratios for those with normal and heavy albuminuria. INTERPRETATION: Albuminuria confers a similar risk of progression to kidney failure for First Nations and non-First Nations people.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".