Software and equation to estimate weight in children and adolescents with cerebral palsy when they cannot be weight by a direct method

RUIZ BRUNNER, MARÍA DE LAS MERCEDES; VALFRÉ, ALEJANDRA; LUCIANO, SOFIA; CUESTAS EDUARDO; CIERI, MARIA ELISABETH; RODRIGUEZ MARCO, PILAR

Paris

Conferencia; 31st EACD meeting; 2019

European Academy of Child Disability

Introduction: Weight is essential for growth assessment, but is difficult to measure in children with cerebral palsy (CP) because of their motor impairment, or because the lack scales for wheelchair available. The aim of this study was to develop a preliminaryn equation and software to estimate weight using segmental measures for children with CP.Patients and methods: Observational and cross-sectional study. Children and adolescents with CP of both gender from 2 to 19 years old from the City of Córdoba (Argentina) were included. Children with endocrine, metabolic and, genetic diseases or congenital abnormalities were excluded. A multiple linear regression model was performed analyzing coefficients(r), adjusted R2 and RMSE. Bland-Altman plot was used to evaluated agreement. From the equation a software was developed.Results: 228 children and adolescents were included with decimal ages between 2,010-19,030 and diagnosed with CP. 61% of them (95%CI54.34- 67.37%) were males. Their level of function was classified in mild-moderatewalkers with GMFCS level I-III(44,74% 95%CI38,17-51,44),and severelevel IV-V(55,26% 95%CI48,55-61,83). In order to develop the weight predictive equation, it was analyzed the interaction between the weight other variables such us mid arm circumference (MAC), Knee height (KH) function level, and age. The following preliminary equations were developed: For Children with level I to III: Weight=MAC*2,43+age*0,59+KH*0,37-39,4. And level IV to V: Weight=MAC*1,68+age*-0,15+KH*0,90-37,42.. Bland?Altman plots showed that equations can provea strong consistency between the observed and the estimated values for weight. A prototype of software was developed to estimate weight. Conclusion: It is possible to predict weight in children with cerebral palsyCP using segmental measures that are easy to obtain and combined with basic data of the child.