Overestimating Neurodevelopment Using the Bayley-III After Early Complex Cardiac Surgery
Bibliographic record
Abstract
BACKGROUND: The newest measure of neurodevelopmental outcomes, the Bayley Scales of Infant and Toddler Development, 3rd Edition (Bayley-III), gives higher-than-expected scores for preterm infants; results after cardiac surgery are unknown. OBJECTIVES: The goal of this study was to report Bayley-III scores after cardiac surgery and compare the results with those of the Bayley Scales of Infant Development, 2nd Edition (BSID-II) on a subset of the same children. METHODS: In this prospective, inception cohort, neurodevelopmental outcome study after complex cardiac surgery in infants from 2004 to 2007, the Bayley-III was given to 110 survivors (68% boys) at a mean age of 21 months (SD: 4 months). Analysis of variance was used to compare intergroup differences. Results for both test editions on the same 25 children were compared by using paired-samples statistics. RESULTS: Mean (SD) Bayley-III mean composite scores (CSs) for 110 children were as follows: cognitive, 95.9 (14.1); language, 90.8 (18.1); and motor, 93.7 (14.2), differentiating selected cardiac surgery groups. The average difference in mean CSs was 7.4 points higher than BSID-II scores for a previous cohort from this site and 7.2 points higher than a systematic review report. Direct comparison of BSID-II and Bayley-III revealed an average difference in mean CSs of 6.1 points, similar to normative results. Mean cognitive CSs increased by 10.0 (P <.001), language by 1.4 (P = .526), and motor by 6.9 points (P = .009). CONCLUSIONS: Researchers should be careful attributing higher Bayley-III scores to changes in acute care. At-risk children who previously qualified for early developmental intervention may no longer do so. School-age longitudinal studies are needed to determine the accuracy of early developmental estimates using the Bayley-III.
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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".