Comorbidities in cerebral palsy and their relationship to neurologic subtype and GMFCS level
Bibliographic record
Abstract
OBJECTIVE: Utilizing a population-based registry, the burden of comorbidity was ascertained in a sample of children with cerebral palsy and stratified according to both neurologic subtype and functional capability with respect to gross motor skills. METHODS: The Quebec Cerebral Palsy Registry was utilized to identify children over a 4-year birth interval (1999-2002 inclusive) with cerebral palsy. Information on neurologic subtype classified according to the qualitative nature and topographic distribution of the motor impairment on neurologic examination, Gross Motor Function Classification System (GMFCS) categorization of motor skills, and the presence of certain comorbidities (cortical blindness, auditory limitations, nonverbal communication skills, gavage feeding status, and coexisting afebrile seizures in the prior 12 months) was obtained. RESULTS: The frequency of individual comorbidities, their proportional distribution, and mean number of occurrences basically falls into a significant dichotomous distribution. Across the spectrum of comorbidities considered, these comorbidities are relatively infrequently encountered in those with spastic hemiplegic or spastic diplegic variants or ambulatory GMFCS status (levels I-III), while these entities occur at a frequent level for those with spastic quadriplegic, dyskinetic, or ataxic-hypotonic variants or nonambulatory GMFCS status (levels IV and V). CONCLUSION: The enhanced burdens of comorbidity are unevenly distributed in children with cerebral palsy in a manner that can be associated with either a specific neurologic subtype (spastic quadriplegic, dyskinetic, ataxic-hypotonic) or nonambulatory motor status (Gross Motor Function Classification System levels IV and V). This provides enhanced value to the utilization of these classification approaches.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".