Cerebral palsy in Canadian Indigenous children
Bibliographic record
Abstract
AIM: To determine whether inequities in health outcomes for Indigenous Canadians are also present in cerebral palsy (CP) by comparing CP profiles between Indigenous and non-Indigenous children. METHOD: Using the Canadian Cerebral Palsy Registry, we conducted a cross-sectional study. CP motor subtype, gross motor severity, comorbidities, perinatal adversity, preterm birth, and parental education were compared between 94 Indigenous (53 males, 41 females) and 1555 non-Indigenous (891 males, 664 females) children (all >5y). Multivariate analysis was done to analyze adverse CP factors, defined as CP gross motor severity and comorbidities. CP etiologies, either prenatal/perinatal or postnatal, were also compared. RESULTS: Indigenous children with CP have higher odds of having low parental education (odds ratio [OR] 6.15, 95% confidence interval [CI] 3.36-11.3) and comorbidities (OR 4.46, 95% CI 1.62-12.3), especially cognitive (OR 4.52, 95% CI 2.27-9.05), communication (OR 2.66, 95% CI 1.54-4.61), and feeding (OR 2.25, 95% CI 1.33-3.83) impairment. Indigenous children also have higher CP gross motor severity (p=0.03). Indigenous children are also more likely to have non-accidental head injury (n=4; OR 8.18, 95% CI 1.86-36.0) as the cause of their postnatal CP. INTERPRETATION: Indigenous populations have worse health outcomes as a result of intergenerational impacts of colonization. Our study shows that Indigenous children with CP have increased comorbidities and higher CP gross motor severity, reinforcing the need for a multidisciplinary approach to management. Furthermore, targeted prevention programs against preventable causes of CP, such as non-accidental head injury, may be beneficial. WHAT THIS PAPER ADDS: Indigenous children with cerebral palsy (CP) have more severe motor impairment and more comorbidities. Non-accidental head injury is a significant cause of postnatal CP.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".