Brain in Congenital Heart Disease Across the Lifespan
Bibliographic record
Abstract
The number of patients surviving with congenital heart disease (CHD) has soared over the last 3 decades. Adults constitute the fastest-growing segment of the CHD population, now outnumbering children. Research to date on the heart-brain intersection in this population has been focused largely on neurodevelopmental outcomes in childhood and adolescence. Mutations in genes that are highly expressed in heart and brain may cause cerebral dysgenesis. Together with altered cerebral perfusion in utero, these factors are associated with abnormalities of brain structure and brain immaturity in a significant portion of neonates with critical CHD even before they undergo cardiac surgery. In infancy and childhood, the brain may be affected by risk factors related to heart disease itself or to its interventional treatments. As children with CHD become adults, they increasingly develop heart failure, atrial fibrillation, hypertension, diabetes mellitus, and coronary disease. These acquired cardiovascular comorbidities can be expected to have effects similar to those in the general population on cerebral blood flow, brain volumes, and dementia. In both children and adults, cardiovascular disease may have adverse effects on achievement, executive function, memory, language, social interactions, and quality of life. Against the backdrop of shifting demographics, risk factors for brain injury in the CHD population are cumulative and synergistic. As neurodevelopmental sequelae in children with CHD evolve to cognitive decline or dementia during adulthood, a growing population of CHD can be expected to require support services. We highlight evidence gaps and future research directions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 0.001 |
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 teacher head, 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".