Association of Gestational Age at Birth and Changes on MRI With Prevalence and Spectrum of Comorbidities in Children With Cerebral Palsy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: For individuals with cerebral palsy (CP) and caregivers, comorbidities may be a greater challenge than neuromotor impairment. Clinicians may make assumptions regarding risk of comorbidities based simply on term vs preterm birth, but this has not been well examined. To better understand factors affecting comorbidity pattern, we investigated the relationship between gestational age (GA) and imaging pattern on the presence of specific comorbidities. METHODS: This is a cross-sectional study of data extracted from the Canadian Cerebral Palsy Registry of children with CP. Multivariable analysis was used to evaluate the relationship between brain injury, GA, and comorbidities. Comorbidities included in the analysis were communication, cognitive, visual, and auditory impairment, seizures in the past year, and gavage feeding. Each comorbidity was assessed as a separate nonexclusive outcome, with GA, MRI pattern, birth weight, postneonatal insult, 5-minute Apgar score, and male sex considered as potential modifiers. RESULTS: The only comorbidity affected by GA on multivariable analysis was seizures within the past year that were more prevalent in term children (odds ratio [OR] 1.1 95% CI 1.0-1.2) and was also affected by Apgar score (OR 0.9 95% CI 0.85-0.94), but not MRI pattern. MRI pattern appeared important for communication impairment (deep gray OR 4.2 95% CI 1.8-10.0; total brain injury OR 8.5, 95% CI 3.2-22.6; malformation OR 2.7, 95% CI 1.3-5.7) and cognitive impairment (deep gray OR 5.6, 95% CI 2.4-13.2; total brain injury OR 10.1, 95% CI 4.0-25.3; malformation OR 3.3, 95% CI 1.6-6.8; watershed OR 3.6, 95% CI 1.4-8.9). Focal injury compared with normal MRI was associated with reduced odds of visual impairment (OR 0.24, 95% CI 0.12-0.48), auditory impairment (OR 0.2195% CI 0.10-0.46) and communication impairment (OR 0.46, 95% CI 0.26-0.82), and overall number of comorbidities (coefficient -0.73, 95% CI -1.2 to -0.31). The number of comorbidities was increased by total brain injury pattern (coefficient 0.65, 95% CI 0.15-1.13) and reduced by focal brain injury (coefficient -0.73, 95% CI -1.2 to -0.31) and increasing 5-minute Apgar score (coefficient -0.11, 95% CI -0.16 to -0.07). DISCUSSION: In those with brain injuries sufficient to cause CP, development of additional comorbidities is less affected by GA at birth and more related to the underlying cause of CP as reflected by MRI patterns.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".