Predictive Models of Weight and Height for the Evaluation of the Growth of Children and Adolescents With Cerebral Palsy
Condition: Cerebral Palsy; Growth; Child
MeSH terms: Cerebral Palsy
Study type: Observational

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.
    

Detailed description: 
      The aim is to design predictive models of weight and height, through predictive equations
      using segmental measurements and to develop specific growth patterns, for the nutritional and
      growth evaluation of children and adolescents with cerebral palsy from different provinces of
      Argentina.

      This research is a cross-sectional study, which consisted of two stages. First, data were
      collected from children and adolescents aged 2 to 18 years with typical development from
      which the anthropometric variables associated with weight and height were determined and then
      used for the analysis of the population with CP. A stratified sampling was made with 17
      strata according to age for each sex, pre-establishing a minimum of 20 children for each
      stratum. Data were collected transversely in two hospitals and two schools in the City of
      Córdoba until all strata were completed.

      In a second stage, data is collected from children and adolescents diagnosed with CP between
      the ages of 2 and 19 years. Data were included from 17 rehabilitation centers and therapeutic
      educational centers in 5 provinces of the country (Córdoba, Buenos Aires (CABA), Jujuy,
      Santiago del Estero and Catamarca). A sequential non-probabilistic sampling was made,
      including all possible cases of each participating institution. The variables studied were
      demographic variables, anthropometric measures, nutritional status, type of malnutrition and
      in the case of the population with PC also variables such as data on access to health,
      diagnosis, co-morbidities and feeding were included. Normal continuous variables were
      described as mean and standard deviations, while those of non-normal distribution in medians
      with their interquartile ranges. Variables are compared by means of t-test or Mann-Whitney as
      appropriate. Categorical data are expressed in percentages with a 95% confidence interval
      [95% CI]. To analyze association between variables, Chi square of Mantel-Haentzel was
      calculated, and OR with its 95% CI. For the development of predictive equations, a
      generalizable linear regression model will be used. The correlation coefficient r,
      determination R2 and F test were calculated with a p <0.05. Growth patterns were made using
      the Generalized Additive Models for Location Scale and Shape (GAMLSS) method. Nutritional
      status was assessed using the WHO Anthro Plus V1.0.4 program using the WHO standards (2007).
      The approval of the local ethics committee was obtained and written informed consent was
      obtained from the participants.

      The study of nutrition in patients with PC is an emerging field, for which this work plan
      seeks to develop methodologies that promote social inclusion by making substantial and
      necessary contributions to improve the treatment of this pathology.
    

Observational model: Other
Time perspective: Prospective
Sampling method: Non-Probability Sample
Study population: 
        The population of this study will be made up of children aged 2 to 18 years with a
        diagnosis of PCs who attend public and private health institutions in Córdoba.