Screening for kidney disease in Indigenous Canadian children: The FINISHED screen, triage and treat program
Bibliographic record
Abstract
Indigenous populations are disproportionately affected by kidney failure at younger ages than other ethnic groups in Canada. As symptoms do not occur until disease is advanced, early kidney disease risk is often unrecognized. We sought to evaluate the yield of community-based screening for early risk factors for kidney disease in youth from rural Indigenous communities in Canada. The FINISHED project screened 11 rural First Nations communities in Manitoba, Canada after community and school engagement. The results for the 10- to 17-year olds are reported here. Body mass index (BMI), blood pressure, estimated glomerular filtration rate (eGFR), hemoglobin A1c’s (HbA1c) and urine albumin-to-creatinine ratios (ACR) were assessed. All children were triaged and referred to either primary or tertiary care, depending on risk. A total of 353 were screened (estimated 22.4% of population). The median age was 12 years (IQR 10 to 13), 55% were female and 55% were overweight or obese. Overall, 21.8% of children had at least one abnormality. Hypertension was identified in 5.4% and 11.9% had prehypertension. None of the children had an eGFR < 60 ml/min/1.73 m2 however 10.5% had an ACR > 3 mg/mmol and 6.2% had an eGFR < 90 ml/min/1.73 m2 suggestive of early kidney disease. Diabetes was identified in 1.4%, and 1.4% had HbA1c’s between 6.1% and 6.49%. Risk factors for chronic kidney disease are highly prevalent in rural Indigenous children. More research is required to confirm the persistence of these findings, and to evaluate the efficacy of screening children to prevent or delay progression to kidney failure.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".