Prognostic value of brain abnormalities for cognitive functioning in cerebral palsy: A prospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Brain abnormalities in cerebral palsy (CP) are known to relate to motor outcome; however, their association with cognitive functioning is less clear. AIM OF THE STUDY: 1) To investigate the prognostic value of brain abnormalities for cognitive functioning; 2) To explore the added value of prognostic variables across ICF domains: motor function, epilepsy, gestational age, birthweight and educational level of the parents. METHODS: We retrospectively analyzed brain MRI scans of 75 children with CP (GMFCS level I-V, 36% born preterm), as part of a longitudinal study. MRI classification: qualitative classification of brain abnormality pattern and semi-quantitative grading of the extent of damage. Cognitive functioning, measured as non-verbal intelligent quotient (IQ), was dichotomized into 'impaired cognition' (IQ ≤ 70) and 'normal' (IQ > 70). Multivariable logistic regression produced odds ratios (OR) with 95% confidence interval (C.I.) of risk factors for impaired cognition. RESULTS: Overall, 27% of the tested participants had a non-verbal IQ below 70 and 36% of the participants was classified as 'having impaired cognition'. At a young age, a higher degree of white matter damage (OR 1.6, 95% C.I. 0.97-2.67) and a more severe GMFCS level (OR 3.2, 95% C.I. 1.70-5.98) are risk factors for impaired cognition at school-age (4-7 years of age). This model correctly predicts 89% of the cases. Brain damage alone predicts the presence of impaired cognition in 71% of the cases. INTERPRETATION: Brain MRI characteristics and GMFCS level at a young age can each help identify children with CP at risk for impaired cognition at school age and together have a strong predictive value.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".