Monitoring Developmental Risk and Promoting Success for Children With Congenital Heart Disease: Recommendations for Cardiac Neurodevelopmental Follow-Up Programs
Bibliographic record
Abstract
Survival of children born with complex congenital heart disease (CHD) has improved dramatically in recent years. However, research studies document high rates of neurologic abnormality and neurodevelopmental impairment in this patient population. The American Heart Association (AHA) and American Academy of Pediatrics (AAP) recently released guidelines for developmental screening, surveillance, and evaluation of children with CHD. The AHA and AAP jointly developed the guidelines in light of increased awareness of long-term cognitive, behavioral, and social sequelae of CHD and the underutilization of remedial services and supports that address these concerns. The guidelines provide an impetus for hospitals to incorporate formal neurodevelopmental follow-up as an integral component of cardiac care. Existing cardiac neurodevelopment programs are rapidly emerging in the United States, Canada, and abroad. Members of the Society of Pediatric Psychology’s Cardiology Special Interest Group collaborated in this effort to describe the essential components of cardiac neurodevelopmental follow-up programs, review implementation and program development challenges, and consider future directions for the field of cardiac neurodevelopment.
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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 | 0.020 | 0.076 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".