Prediction of preschool functional abilities after early complex cardiac surgery
Bibliographic record
Abstract
BACKGROUND: It is important to identify early predictors of functional limitations in children after congenital heart surgery to optimise their independence as they prepare for school. The purpose of this study is to determine potentially modifiable predictor variables of functional abilities in pre-school children who underwent complex cardiac surgery at 6 weeks of age or earlier. METHODS: This prospective inception cohort study comprised a sample of 165 survivors (63% boys) who had complex cardiac surgery (75% biventricular repairs) at Stollery Children's Hospital, Edmonton, Alberta. We excluded children with chromosomal abnormalities. When children were 4-5 years of age, the parents completed the Adaptive Behavioral Assessment System II. Regression analysis was used to assess the association between multiple risk factors and each of the four continuous composite scores. RESULTS: The mean scores for the practical domain and general adaptive composite score of the Adaptive Behavioural Assessment System were lower than the conceptual and social domains, with 13.3% of the children having a delay in the practical domain. There was a significant association between the general adaptive (p=0.003; 0.012), conceptual (p=0.0004; 0.042), social (p=0.0007; 0.028), and the practical (p=0.046; 0.003) domain composite scores with the mother's education and preoperative plasma lactate, respectively. CONCLUSION: Maternal education may be a marker for the social context of children, and warrants societal attention to improve functional outcomes. Preoperative lactate as a potentially modifiable variable may warrant increased attention to early diagnosis and aggressive resuscitation of young infants with congenital heart disease.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".