Overweight and obese youth with type 1 or type 2 diabetes share similar elevation in triglycerides during middle and late adolescence
Bibliographic record
Abstract
BACKGROUND: Overweight and obesity have been observed in children with type 1 diabetes (T1D). This further increases their future risk of Cardiovascular Disease (CVD) as well as the development of other risk factors, such as dyslipidemia. AIMS: To compare lipid profiles in children and adolescents with Type 1 diabetes and lean mass (T1L), Type 1 diabetes and overweight or obese (T1OW/OB), and type 2 diabetes (T2D). METHODS: This was a cross-sectional study of 669 patients with T1D or T2D aged 2-19 years using retrospective data collected from 2003 to 2014. Included patients were categorized into lean (BMI < 85th ile and overweight or Obese (BMI ≥ 85th ile). Patients were subcategorized into three age groups: < 10 years, 10-14 years, and 15-19 years. RESULTS: 7.6% of patients had T2D. Of the patients with T1D, 58.9% were lean, 26.4% were overweight, and 14.7% were obese. Total Cholesterol (TC), Low-density lipoprotein cholesterol (LDL-C) and Non-HDL-C levels were similar across groups. In the 15-19 years group, Triglycerides (TG) levels were significantly higher in T1OW/OB and similar to T2D. High-density lipoprotein Cholesterol (HDL-C) was significantly lower in T2D. Weight status significantly correlated with TG and HDL-C levels in T1D and T2D groups. CONCLUSIONS: T1OW/OB constitutes a significant proportion of the T1D population. Patients with obesity and T1D, especially if in their late adolescence, have an adverse lipid profile pattern that is comparable to adolescents with T2D. Based on these findings, risk for future CVD in T1OW/OB and T2D may be equivalent.
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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 | 0.000 |
| 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 | 0.000 |
| 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".