At a glance
ClinicalIndex Comparison RecordStandardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Elaboration, Development and Validation of Predictive Models of Weight and Height for the Evaluation of the Growth of Children and Adolescents With Cerebral Palsy
In Brief
An observational study for Cerebral Palsy and 2 related conditions. Completed, enrolled 388 participants across 1 site.
Detailed Summary
Cerebral palsy (CP) is the most frequent disability in children. The vast majority of these patients are malnourished. In this population, there are practical difficulties to perform a nutritional and growth assessment which makes it difficult to treat and follow up, because of the lack of reference growth in Argentina, and the difficulty in taking anthropometric measurements of weight and height because of their motor compromise, posture and muscle tone. The main objective is to design and validate predictive models for the nutritional and growth assessment of children and adolescents with CP and instruments for estimating weight and height from body segments, in order to improve care, quality of life of these patients to promote their social inclusion. Material and method: It will be an observational, descriptive and cross-sectional study. There will be two parts of the study, in the first part the population will be healthy children from 2 to 18 years old from Cordoba, Argentina. The sample size was calculated based on growth WHO standards data, for α=0.05 and 1-β=0.80, creating an stratified sampling divided in 16 age groups for each age. This first part will help to establish which body segments to use. In the second part, the population will be children and adolescents from 2 to 18 years old with diagnosis of CP from Córdoba, Argentina. A stratified sequential sampling shall be performed. The sample size will be 192 patients, 12 per age stratum. The variables studied will be: weight, height, body segments, sex, age, CP type, feeding path and type of feeding. For the analysis of the data the normal continuous variables will be described in means with their respective standard deviations and those of non-normal distribution in medians with their ranges. For the development of the predictive equations using body segments measures, a generalizable linear regression model will be used. The correlation coefficient r, determination R2 and test of F will be calculated with p \<0.05. To generate predictive growth models, the percentiles from 3 to 97 will be calculated, using the LMS method and a q-q graph.