Congenital Heart Disease and Risk of Cardiovascular Disease: A Meta‐Analysis of Cohort Studies
Bibliographic record
Abstract
Background Despite remarkable success in the surgical and medical management of congenital heart disease ( CHD ), some survivors still experience cardiovascular complications over the long term. The goal of this study was to evaluate the association between CHD and risk of cardiovascular disease ( CVD ) by conducting a meta-analysis of cohort studies. Methods and Results A systematic literature search of several databases was conducted through April 2018 to identify studies reporting the risk of CVD , stroke, heart failure, and coronary artery heart disease in CHD survivors. The quality of individual studies was assessed using the Newcastle-Ottawa scale. The overall risk estimates were pooled using fixed-effects meta-analysis. Subgroup analyses were performed to explore possible sources of heterogeneity. Nine cohort studies comprising 684 200 participants were included. The overall combined relative risks for people with CHD compared with the controls were 3.12 (95% CI, 3.01-3.24) for CVD , 2.46 (95% CI, 2.30-2.63) for stroke, 5.89 (95% CI, 5.58-6.21) for heart failure, and 1.50 (95% CI, 1.40-1.61) for coronary artery heart disease. Significant heterogeneity was detected across studies regarding these risk estimates. Heterogeneity in the risk estimate of CVD was explained by geographic region, type of study design, sample source, age composition, and controlled confounders. Conclusions This meta-analysis of cohort studies of CHD found an association of increased risk of CVD in later life, although we cannot determine whether this association is confounded by a risk factor profile of CVD among CHD survivors or whether CHD is an independent risk factor.
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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 | 0.024 | 0.044 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.065 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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".