A guide to prenatal counseling regarding neurodevelopment in congenital heart disease
Bibliographic record
Abstract
Advances in cardiac surgical techniques taking place over the past 50 years have resulted in the vast majority of children born with congenital cardiac malformations now surviving into adulthood. As the focus shifts from survival to the functional outcomes of our patients, it is increasingly being recognized that a significant proportion of patients undergoing infant cardiac repair experience adverse neurodevelopmental (ND) outcomes. The etiology of abnormal brain development in the setting of congenital heart disease is poorly understood, complex, and likely multifactorial. Furthermore, the efficacy of therapies available for the learning disabilities, attention deficit, and hyperactivity disorders and other ND deficits complicating congenital heart disease is currently uncertain. This situation presents a challenge for prenatal counseling as current antenatal testing does not usually provide prognostic information regarding the likely ND trajectories of individual patients. However, we believe it is important for parents to be informed about potential issues with child development when a new diagnosis of congenital heart disease is disclosed. Parents deserve a comprehensive and thoughtful approach to this subject, which conveys the uncertainties involved in predicting the severity of any developmental disorders encountered, while emphasizing the improvements in outcomes that have already been achieved in infants with congenital heart disease. A balanced approach to counseling should also discuss what local arrangements are in place for ND follow-up. This review presents an up-to-date overview of ND outcomes in patients with congenital heart disease, providing possible approaches to communicating this information to parents during prenatal counseling in a sensitive and accurate manner.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.015 |
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".