Predictive Models of Weight and Height for the Evaluation of the Growth of Children and Adolescents With Cerebral Palsy

NCT03303755 | Completed

• 1 other identifier: IS001087
• Study Type: observational
• Target: 388
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Cerebral Palsy; Growth; Child

Outcome Measures

Primary Outcomes (2)

• Weight in children

  weight in kilograms

  2 year

• Height in children

  height in centimeters

  2 year

Secondary Outcomes (2)

• Estimated weight

  1 year

• estimated height

  1 year

Eligibility Criteria

• Age: 2 Years - 19 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64)
• 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.

You may qualify if:

• Children with diagnosis of cerebral palsy

You may not qualify if:

• children with endocrine or metabolic disorders, genetic diseases and other congenital anomalies that affect or have affected their growth or nutritional status.

Sponsors & Collaborators

• National Council of Scientific and Technical Research, Argentina: lead
• Universidad Nacional de Córdoba: collaborator

Study Sites (1)

Instituto de Investigaciones en Ciencias de la Salud, Argentina

Córdoba, 5000, Argentina

Location

Related Publications (8)

• Abdel-Rahman SM, Ahlers N, Holmes A, Wright K, Harris A, Weigel J, Hill T, Baird K, Michaels M, Kearns GL. Validation of an improved pediatric weight estimation strategy. J Pediatr Pharmacol Ther. 2013 Apr;18(2):112-21. doi: 10.5863/1551-6776-18.2.112.

  PMID: 23798905 BACKGROUND

• Brooks J, Day S, Shavelle R, Strauss D. Low weight, morbidity, and mortality in children with cerebral palsy: new clinical growth charts. Pediatrics. 2011 Aug;128(2):e299-307. doi: 10.1542/peds.2010-2801. Epub 2011 Jul 18.

  PMID: 21768315 BACKGROUND

• Le Roy O. C, Rebollo G. MJ, Moraga M. F, Díaz Sm. X, Castillo-Durán C. Nutrición del niño con enfermedades neurológicas prevalentes. Rev Chil Pediatr. 2010;81(2):103-113.

  BACKGROUND

• Day SM, Strauss DJ, Vachon PJ, Rosenbloom L, Shavelle RM, Wu YW. Growth patterns in a population of children and adolescents with cerebral palsy. Dev Med Child Neurol. 2007 Mar;49(3):167-71. doi: 10.1111/j.1469-8749.2007.00167.x.

  PMID: 17355471 BACKGROUND

• Vega-Sanchez R, de la Luz Gomez-Aguilar M, Haua K, Rozada G. Weight-based nutritional diagnosis of Mexican children and adolescents with neuromotor disabilities. BMC Res Notes. 2012 Jul 4;5:218. doi: 10.1186/1756-0500-5-218.

  PMID: 22559790 BACKGROUND

• Bell KL, Davies PS. Prediction of height from knee height in children with cerebral palsy and non-disabled children. Ann Hum Biol. 2006 Jul-Aug;33(4):493-9. doi: 10.1080/03014460600814028.

  PMID: 17060071 BACKGROUND

• Kong CK, Wong HS. Weight-for-height values and limb anthropometric composition of tube-fed children with quadriplegic cerebral palsy. Pediatrics. 2005 Dec;116(6):e839-45. doi: 10.1542/peds.2005-1029.

  PMID: 16322142 BACKGROUND

• Neela J, Raman L, Balakrishna N, Rao KV. Usefulness of calf circumference as a measure for screening low birth weight infants. Indian Pediatr. 1991 Aug;28(8):881-4.

  PMID: 1808075 BACKGROUND

Related Links

• Rosenbaum P, Paneth N, Leviton A, et al. 2007 Definition of CP. Dev Med Child Neurol Suppl. 2007;109(April):8-14

MeSH Terms

Conditions

Cerebral Palsy

Condition Hierarchy (Ancestors)

Brain Damage, Chronic; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases

Study Officials

• Eduardo Cuestas, PhD MD

  Instituto de Investigaciones en Ciencias de la Salud

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD Reasercher

Study Record Dates

• First Submitted: September 14, 2017
• First Posted: October 6, 2017
• Study Start: April 1, 2014
• Primary Completion: January 1, 2020
• Study Completion: April 1, 2020
• Last Updated: March 19, 2021

Record last verified: 2021-03

Locations

AR (1)