Major Depressive Disorder and Cardiovascular Disease Risk in Children and Adolescents
Bibliographic record
Abstract
OBJECTIVE: Major depressive disorder (MDD) in youth is an independent risk factor for premature cardiovascular disease (CVD). While previous research has considered individual CVD risk factors in relation to depression, this study examined the association between depression and CVD risk among children and adolescents with MDD using a validated composite measure. METHODS: Youth with MDD were recruited through an outpatient psychiatry program and underwent semistructured psychiatric diagnostic assessment to confirm diagnosis. Healthy control participants were recruited from community settings. All participants completed the Center for Epidemiological Studies Depression Scale for Children to assess depressive symptoms. The continuous metabolic syndrome score, a validated measure for cardiometabolic risk assessment in youth, was computed using aggregated standardized z-scores of CVD risk factors, including fasting blood glucose, body mass index, blood pressure, fasting triglycerides, and high-density lipoprotein cholesterol. Hierarchical multiple regression models tested the association between depression (diagnosis and symptoms) and CVD risk while accounting for covariates. RESULTS: Participants (N=277; 73.6% female) had a mean age of 15.2 (SD=1.8) years. Cardiovascular disease risk was significantly higher among youth with depression (n=196, mean=0.77, SD=2.98) compared with healthy controls (n=81, mean=-0.39, SD=2.77; P=.002). Depression diagnosis and depressive symptoms were associated with increased CVD risk (β=0.40, P=.004; β=0.15, P=.02, respectively), after adjusting for covariates. CONCLUSIONS: Adolescents with MDD demonstrate increased cardiovascular disease risk compared with healthy youth, highlighting early evidence of association between depression and cardiovascular disease. Consequently, childhood and adolescence may serve as crucial periods for preventive intervention targeting cardiovascular health among youth with depression.
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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 | 0.001 | 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 | 0.001 |
| 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".