Stability and decline in gross motor function among children and youth with cerebral palsy aged 2 to 21 years
Bibliographic record
Abstract
This paper reports the construction of gross motor development curves for children and youth with cerebral palsy (CP) in order to assess whether function is lost during adolescence. We followed children previously enrolled in a prospective longitudinal cohort study for an additional 4 years, as they entered adolescence and young adulthood. The resulting longitudinal dataset comprised 3455 observations of 657 children with CP (369 males, 288 females), assessed up to 10 times, at ages ranging from 16 months to 21 years. Motor function was assessed using the 66-item Gross Motor Function Measure (GMFM-66). Participants were classified using the Gross Motor Function Classification System (GMFCS). We assessed the loss of function in adolescence by contrasting a model of function that assumes no loss with a model that allows for a peak and subsequent decline. We found no evidence of functional decline, on average, for children in GMFCS Levels I and II. However, in Levels III, IV, and V, average GMFM-66 was estimated to peak at ages 7 years 11 months, 6 years 11 months, and 6 years 11 months respectively, before declining by 4.7, 7.8, and 6.4 GMFM-66 points, in Levels III, IV, and V respectively, as these adolescents became young adults. We show that these declines are clinically significant.
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 | 0.001 | 0.007 |
| 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 | 0.000 |
| 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".