Longitudinal assessments of motor performance and musculoskeletal abnormalities in preschool children with esophageal atresia
Bibliographic record
Abstract
BACKGROUND: Children with esophageal atresia (EA) may have impaired motor performance and musculoskeletal abnormalities, but when and in whom these abnormalities develop is still unknown. AIMS: To study motor performance and musculoskeletal abnormalities from infancy to pre-school age, and to assess risk factors for poor motor performance at 24 and 48 months. STUDY DESIGN: Prospective cohort study at 12, 24, and 48 months. SUBJECTS: Forty-six children with EA. OUTCOME MEASURES: Total and subtest scores and percentile ranks describing motor skills were obtained by using the Alberta Infant Motor Scale (AIMS) at 12 months, Peabody Developmental Motor Scale, Second Edition (PDMS-2) at 24 months, and Motor Assessment Battery for Children, Second Edition (MABC-2) at 48 months. Muscle strength was measured by Grippit, and musculoskeletal abnormalities were clinically evaluated according to a standardized protocol. RESULTS: The total median z-scores for AIMS, PDMS-2, and MABC-2 at group level were -0.571, -0.903, and -0.994 respectively, all significantly lower than in reference populations (p < 0.001). The decrease in motor skills between 12 and 48 months may have biological importance and was significantly more frequent in patients with more neonatal morbidity, anastomotic complications, and reduced muscle strength. The number of patients with musculoskeletal abnormalities increased from 11 % to 59 % between 24 and 48 months, but was not related to motor performance. CONCLUSIONS: Motor performance was low from infancy, reduced longitudinally, and related to neonatal morbidity in children with EA. Musculoskeletal abnormalities increased throughout childhood, but were not related to motor performance.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".