Abstract 10371: Trajectories of Glycemic Control and Early Markers of Cardiovascular Disease in Canadian Adolescents with Type 1 Diabetes: The Cardea Study
Bibliographic record
Abstract
Introduction: Adequate glycemic control can prevent or delay complications of diabetes. Little is known about the role of glycemic control trajectories on early markers of CVD in youth. Hypothesis: Poor glycemic control trajectory will be associated with increased vascular ageing and altered myocardial structure. Methods: Cross-sectional study of 100 youth with T1D recruited at Sainte-Justine Hospital, Canada. Trajectories of glycated hemoglobin (Hb A1c ) were estimated with group-based trajectory modelling, using 3 to 6 values retrieved from patients’ medical records over the preceding year. Vessel stiffness was assessed by pulse-wave velocity (PWV) and distensibility by velocity time integral (VTI) and acceleration during a brachial flow-mediated dilation test. Cardiac magnetic resonance assessed ejection fraction, left ventricular mass indexed by height (LVMH), papillary mass and wall thickness. Linear regression models were estimated between Hb A1c trajectory group and each CVD marker, with age, sex, ethnicity and duration of diabetes at baseline as covariates. Results: Mean age was 16.4 yrs (SD=1.3) and median diabetes duration 6.1 yrs (IQR=3.4-10.4). Forty-eight percent were girls, 63% were White and 43% had overweight/obesity. Three trajectories of Hb A1c were identified ( Figure ). Compared with the optimal trajectory, belonging to the high Hb A1c trajectory was associated with a lower ejection fraction (beta [95% CI]: -2.1% [-6.2; 2.0]), LVMH (-6.3 g/m [-15.4; 2.8]) and papillary mass (-1.2 g [-2.2; -0.2]). Youth in the high Hb A1c trajectory displayed higher PWV (0.2 m/s [-0.4; 0.8]) and lower VTI (-2.9 cm/s 2 [-8.4; 2.7]) and acceleration (-63.6 cm/s 2 [-188.7; 61.5]) compared with the optimal trajectory group. Conclusions: Poor glycemic control is linked to increased vascular ageing and a lower myocardial mass in youth with T1D, which is consistent with our prior finding that youth with T1D exhibit a lower myocardial mass than healthy controls.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".