Clinical Functional Profile and Neuroimaging in Cerebral Palsy: A Population-Based Study
Author(s)
Paloma Arana-Rivera, MS1, Diana Marcela Nova Diaz, MSc2, Raquel Bernadó Fonz, MS1, Nerea Gorría Redondo, MS1, Laiene Olabarrieta-Landa, PhD2, Diego Rivera, Dr.2, Sergio Aguilera-Albesa, PhD1.
1University Hospital of Navarra, Pamplona, Spain, 2Public University of Navarra, Pamplona, Spain.
1University Hospital of Navarra, Pamplona, Spain, 2Public University of Navarra, Pamplona, Spain.
OBJECTIVES: To characterise the functional profile and comorbidities of children with cerebral palsy (CP) in a population, and to investigate their association with neuroimaging findings, as classified by MRICS scale.
METHODS: We established a regional registry of children with CP (3-17 years) that were born in the health system area from 2006 to 2021. We collected demographic, clinical, and functional data, including motor subtype, functional profile using 7 validated clinical scales, and comorbidities. Neuroimaging was reviewed based on the Magnetic Resonance Imaging Classification System (MRICS): A - malformations; B - white matter injury; C - grey matter injury; D - miscellaneous; and E - normal imaging. Statistical analysis was conducted using the Monte Carlo version of Chi-squared test in R.
RESULTS: 142 children with CP were included (mean age: 10 years; 58% male). Annual prevalence for CP was 1.56/1,000 newborns. The most common clinical subtypes were spastic bilateral (48.3%) and unilateral (35.7%) CP. Neuroimaging patterns were distributed as follows: type A (19%), B (25.4%), C (37.3%), D (13.4%), and E (4.9%). Grey matter injury (type C) was the most frequent finding. Only a small proportion had normal imaging. Functional severity and comorbidities differed significantly across MRICS groups. Types A and D were significantly associated with more severe motor impairment and higher rates of epilepsy and intellectual disability. Type B showed the most favourable functional and cognitive outcomes, while types C and E presented more heterogeneous profiles. Genetically confirmed CP cases were more frequently observed in types D and E.
CONCLUSIONS: Prevalence of CP in our region is close to other recent studies findings. There is a strong association between neuroimaging findings, functional status, and comorbidities in children with CP. The MRICS scale may serve as a useful tool to support aetiological classification, guide clinical counselling, and inform healthcare planning and allocation of specialised services.
METHODS: We established a regional registry of children with CP (3-17 years) that were born in the health system area from 2006 to 2021. We collected demographic, clinical, and functional data, including motor subtype, functional profile using 7 validated clinical scales, and comorbidities. Neuroimaging was reviewed based on the Magnetic Resonance Imaging Classification System (MRICS): A - malformations; B - white matter injury; C - grey matter injury; D - miscellaneous; and E - normal imaging. Statistical analysis was conducted using the Monte Carlo version of Chi-squared test in R.
RESULTS: 142 children with CP were included (mean age: 10 years; 58% male). Annual prevalence for CP was 1.56/1,000 newborns. The most common clinical subtypes were spastic bilateral (48.3%) and unilateral (35.7%) CP. Neuroimaging patterns were distributed as follows: type A (19%), B (25.4%), C (37.3%), D (13.4%), and E (4.9%). Grey matter injury (type C) was the most frequent finding. Only a small proportion had normal imaging. Functional severity and comorbidities differed significantly across MRICS groups. Types A and D were significantly associated with more severe motor impairment and higher rates of epilepsy and intellectual disability. Type B showed the most favourable functional and cognitive outcomes, while types C and E presented more heterogeneous profiles. Genetically confirmed CP cases were more frequently observed in types D and E.
CONCLUSIONS: Prevalence of CP in our region is close to other recent studies findings. There is a strong association between neuroimaging findings, functional status, and comorbidities in children with CP. The MRICS scale may serve as a useful tool to support aetiological classification, guide clinical counselling, and inform healthcare planning and allocation of specialised services.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
EPH46
Topic
Clinical Outcomes, Epidemiology & Public Health, Patient-Centered Research
Disease
Neurological Disorders, Pediatrics