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.

Aim  Traditionally, cerebral palsy (CP) had been classified according to the distribution and quality of motor impairment. A standardized functional classification of gross motor skills has recently been validated – the Gross Motor Function Classification System (GMFCS). The relationship between the neurological subtype of CP and GMFCS level remains undefined in CP. Method  The Quebec Cerebral Palsy Registry (Registre de la paralysie cérébrale au Québec [REPACQ]) over a 4‐year birth interval (1999–2002 inclusive) identified 301 children with CP. Information on both CP subtype and GMFCS level was available for 243 children (138 males, 105 females) with final data extraction at a mean age of 44 months (SD 14mo, range 24–79mo). Proportions of children with a particular CP subtype at GMFCS levels I to III versus levels IV to V were determined and compared. Results  CP subtype versus GMFCS levels I to III or IV to V was distributed proportionally as follows: spastic diplegic, 51/52 (98%) versus 1/52 (2%); spastic quadriparetic, 20/85 (24%) versus 65/85 (76%); spastic hemiplegic, 76/77 (99%) versus 1/77 (1%); dyskinetic, 4/16 (25%) versus 12/16 (75%); other (triplegic or ataxic–hypotonic), 10/13 (77%) versus 3/13 (23%). These distributions (proportions) all yielded significant (p<0.001) Pearson χ2 values. Interpretation Neurological subtype is a powerful predictor of functional status related to ambulation. This has implications for counseling families.

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Aim: To provide an estimate of the period prevalence of cerebral palsy (CP) in the province of Quebec. Methods: Children with CP were identified from three consecutive birth cohorts (1999–2001) from the Quebec CP Registry, covering 6 of the 17 administrative health regions of the province. Two inferential approaches were applied for period prevalence estimation, frequentist and bayesian. Results: 228 children were identified with CP. Using a frequentist approach, the overall prevalence of CP was 1.84 per 1,000 children aged 9–11 years living in those areas in 2010 (95% CI 1.60–2.08). Using a bayesian approach taking into account the uncertainty about the registry’s sensitivity in capturing all cases, the overall prevalence is higher at 2.30 per 1,000 children with a 95% CI (1.99–2.65). Conclusion: Using a bayesian approach to adjust for the registry’s known high specificity and lower sensitivity, the prevalence estimate is in concordance with worldwide estimates and estimates using administrative databases in western Canadian provinces. Future studies are needed to validate the diagnosis of CP within administrative databases and to evaluate possible regional trends across Canada in both prevalence and health service utilization, which may highlight disparities in healthcare delivery.

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