Differing clinical features in Aboriginal vs. non-Aboriginal children presenting with type 2 diabetes
Bibliographic record
Abstract
OBJECTIVES: Childhood type 2 diabetes (T2D) is increasing and may present differently across various populations. This study compares clinical features of T2D at diagnosis in Aboriginal children with Caucasian children and children from other high-risk ethnic groups. PATIENTS AND METHODS: This retrospective observational study used data from a Canadian surveillance study where newly diagnosed cases of childhood T2D were reported (n = 227). Using descriptive statistics, clinical features at diagnosis of T2D were compared across different ethnic groups including Aboriginal (n = 100), Caucasian (n = 57), and other high-risk ethnic groups (n = 64). Comparisons were made between Aboriginal children living in central Canada (Manitoba/northwestern Ontario) (n = 74) and Aboriginal children from other regions of Canada (n = 26). RESULTS: Aboriginal children were younger, less obese, and less likely to have polycystic ovarian syndrome and dyslipidemia when compared to Caucasian children and children from other high-risk ethnic groups (p < 0.05). Aboriginal children from central Canada vs. those from other regions of Canada did not differ in age, body mass index z-score, family history of T2D, or presence of acanthosis nigricans. Those from central Canada had lower hemoglobin A1c levels (p < 0.05) and were less likely to have dyslipidemia than Aboriginal children from other regions (p < 0.05). CONCLUSIONS: Clinical features and rates of comorbidity in children with newly diagnosed T2D differ across various populations (Caucasian, Aboriginal, and children who belong to other high-risk ethnic groups) and across distinct Aboriginal populations (those living in central Canada vs. those living in other regions of Canada). Future research should determine specific genetic and environmental factors that contribute to these differences.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".