Design, implementation, and evaluation of a pediatric and adolescent type 2 diabetes management program at a tertiary pediatric center
Bibliographic record
Abstract
M Constantine Samaan,1–3 Marlie Valencia,1 Connie Cheung,1 Boguslaw Wilk,1,3 Keith Lau,1,4 Lehana Thabane1,5–8 1Department of Pediatrics, McMaster University, 2Division of Pediatric Endocrinology, 3Children's Exercise and Nutrition Center, 4Division of Pediatric Nephrology, McMaster Children's Hospital, 5Population Health Research Institute, 6Department of Clinical Epidemiology and Biostatistics, 7Department of Anesthesia, McMaster University, 8Centre for Evaluation of Medicines, Hamilton, ON, Canada Abstract: Global rates of type 2 diabetes in children and adolescents have increased significantly over the past three decades. Type 2 diabetes is a relatively new disease in this age group, and there is a dearth of information about how to structure treatment programs to manage its comorbidities and complications. In this paper, we describe the design and implementation of a personalized multidisciplinary, family-centered, pediatric and adolescent type 2 diabetes program at a tertiary pediatric center in Hamilton, Ontario, Canada. We report the process of designing and implementing such a program, and show that this multidisciplinary program led to improvement in glycated hemoglobin (n=17, 8% at baseline versus 6.4% at 1 year, 95% confidence interval (0.1–0.28), P-value <0.0001) and stabilized body mass index, with lowered C-peptide and no change in fitness or metabolic biomarkers of lipid metabolism and liver function. As type 2 diabetes becomes more prevalent in youth, the need for programs that successfully address the complex nature of this disease is central to its management and to mitigate its long-term adverse outcomes. Keywords: type 2 diabetes, pediatric, adolescents, program design, multidisciplinary
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".