Health status of children with moderate to severe cerebral palsy
Bibliographic record
Abstract
The aim of the study was to evaluate the health of children with cerebral palsy (CP) using a global assessment of quality of life, condition-specific measures, and assessments of health care use. A multicenter population-based cross-sectional survey of 235 children, aged 2 to 18 years, with moderate to severe impairment, was carried out using Gross Motor Function Classification System (GMFCS) levels III (n = 56), IV (n = 55), and V (n = 122). This study group scored significantly below the mean on the Child Health Questionnaire (CHQ) for Pain, General Health, Physical Functioning, and Impact on Parents. These children used more medications than children without CP from a national sample. Fifty-nine children used feeding tubes. Children in GMFCS level V who used a feeding tube had the lowest estimate of mental age, required the most health care resources, used the most medications, had the most respiratory problems, and had the lowest Global Health scores. Children with the most severe motor disability who have feeding tubes are an especially frail group who require numerous health-related resources and treatments. Also, there is a relationship among measures of health status such as the CHQ, functional abilities, use of resources, and mental age, but each appears to measure different aspects of health and well-being and should be used in combination to reflect children's overall health status.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".