Cardiovascular Disease Risk Factors Among Children and Adolescents With Depression
Bibliographic record
Abstract
Aim: To examine CVD risk factors among children and adolescents with Major Depressive Disorder (MDD). Methods: A cross-sectional study of 77 children and adolescents (mean age 14.1 years, 74% female) referred to a pediatric depression program. MDD was assessed using a semi-structured diagnostic interview. Cardiovascular assessments included family cardiovascular disease (CVD) history, cigarette smoking, body mass index (BMI), blood pressure, lipid and glucose concentrations. CVD risk factors among healthy weight and overweight/obese participants were compared. Results: Forty-six percent of participants had a family history of early CVD. On examination, 25% of participants had a BMI in overweight/obese range, and 25% of children had pre-hypertension (14%) or hypertension (11%). Total cholesterol levels were elevated among 28% of participants. Overweight/obese participants had increased non-HDL cholesterol concentrations compared with healthy-weight participants (36 vs. 10%, p = 0.01). There were no significant differences between healthy and overweight/obese groups for other CVD risk factors, including HDL cholesterol concentration, plasma glucose concentration, hypertension, cigarette smoking, and family history of early CVD. More than half (52%) of participants had at least two CVD risk factors. Conclusion: CVD risk factors are prevalent among children and adolescents with MDD. Routine CVD risk factor screening may be warranted among MDD youth, regardless of BMI, and may provide a valuable opportunity for prevention of future CVD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".