Abstract 17051: Neurocognitive Disorders on Long-Term Follow up of Congenital Heart Disease Patients Undergoing Procedures in Childhood
Bibliographic record
Abstract
Introduction: Neurocognitive disorders (NCD) are a growing concern in congenital heart disease (CHD) patients. We hypothesized that early life cardiopulmonary bypass (CBP) as well as age at intervention (AAI) were risk factors for NCDs on long-term follow-up in CHD patients. Methods: Data source was the Quebec CHD database. We defined NCD based on ICD 9 and 10 codes including autism spectrum disorder, global developmental disorder, specific developmental disorder, attention deficit hyperactive disorder, intellectual disability or specific learning deficit. We compared NCD risk from 1983-2010 in 3 cohorts of patients undergoing procedures in childhood: percutaneous atrial septal defect (ASD) closure (no CBP group), surgical ASD closure (short CBP group), and complex CHD lesion repair surgeries (long CBP group). Patients were followed from intervention until NCD diagnosis, death, or administrative censoring whichever came first. Results: By 27 years of follow-up, the cumulative risk of NCD was significantly higher in the complex surgery group compared to the ASD surgery group (crude, 24.9% and 13.4%; p<0.0001) and with adjustments for AAI and sex (Cox regression, p=0.043). By 12 years of follow-up, the cumulative risk of NCD was significantly higher in the complex surgery group compared to the other two groups where the risk was almost identical. Cox models with different follow-up lengths identified younger AAI and male sex being significantly associated with increased risk in NCD. Conclusions: In long-term follow-up of CHD patients, younger AAI of CBP and male sex were associated with increased risk of NCD. Our findings suggest that CBP duration in a wide range of CHD lesions and cohort effects are important predictors of NCD. <!--EndFragment-->
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".