Growth and Health in Children With Moderate-to-Severe Cerebral Palsy
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Bibliographic record
Abstract
BACKGROUND: Children with cerebral palsy frequently grow poorly. The purpose of this study was to describe observed growth patterns and their relationship to health and social participation in a representative sample of children with moderate-severe cerebral palsy. METHODS: In a 6-site, multicentered, region-based cross-sectional study, multiple sources were used to identify children with moderate or severe cerebral palsy. There were 273 children enrolled, 58% male, 71% white, with Gross Motor Function Classification System levels III (22%), IV (25%), or V (53%). Anthropometric measures included: weight, knee height, upper arm length, midupper arm muscle area, triceps skinfold, and subscapular skinfold. Intraobserver and interobserver reliability was established. Health care use (days in bed, days in hospital, and visits to doctor or emergency department) and social participation (days missed of school or of usual activities for child and family) over the preceding 4 weeks were measured by questionnaire. Growth curves were developed and z scores calculated for each of the 6 measures. Cluster analysis methodology was then used to create 3 distinct groups of subjects based on average z scores across the 6 measures chosen to provide an overview of growth. RESULTS: Gender-specific growth curves with 10th, 25th, 50th, 75th, and 90th percentiles for each of the 6 measurements were created. Cluster analyses identified 3 clusters of subjects based on their average z scores for these measures. The subjects with the best growth had fewest days of health care use and fewest days of social participation missed, and the subjects with the worst growth had the most days of health care use and most days of participation missed. CONCLUSIONS: Growth patterns in children with cerebral palsy were associated with their overall health and social participation. The role of these cerebral palsy-specific growth curves in clinical decision-making will require further study.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it