Impact of a screen, triage and treat program for identifying chronic disease risk in Indigenous children
Bibliographic record
Abstract
Background: The First Nations Community Based Screening to Improve Kidney Health and Prevent Dialysis project was a point-of-care screening program in rural and remote First Nations communities in Manitoba that aimed to identify and treat hypertension, diabetes and chronic kidney disease. The program identified chronic disease in 20% of children screened. We aimed to characterize clinical screening practices before and after intervention in children aged 10–17 years old and compare outcomes with those who did not receive the intervention. Methods: This observational, prospective cohort study started with community engagement and followed the principles of ownership, control, access and possession (OCAP). We linked participant data to administrative data at the Manitoba Centre for Health Policy to assess rates of primary care and nephrology visits, disease-modifying medication prescriptions and laboratory testing (i.e., glycosylated hemoglobin [HbA1c], estimated glomerural filtration rate [eGFR] and urine albumin- or protein-to-creatinine ratio). We analyzed the differences in proportions in the 18 months before and after the intervention. We also conducted a 1:2 propensity score matching analysis to compare outcomes of children who were screened with those who were not. Results: We included 324 of 353 children from the screening program (43.8% male; median age 12.3 yr) in this study. After the intervention, laboratory testing increased by 5.8% (95% confidence interval [CI] 1.1% to 10.1%) for HbA1c, by 9.9% (95% CI 4.2% to 15.5%) for eGFR and by 6.2% (95% CI 2.3% to 10.0%) for the urine albumin- or protein-to-creatinine ratio. We observed significant improvements in laboratory testing in screened patients in the group who were part of the program, compared with matched controls. Interpretation: Chronic disease surveillance and care increased significantly in children after the implementation of a point-of-care screening program in rural and remote First Nation communities. Interventions such as active surveillance programs have the potential to improve the chronic disease care being provided to First Nations children.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".