Embracing the Nutritional Assessment in Cerebral Palsy: A Toolkit for Healthcare Professionals for Daily Practice

Software and equations using segmental measures to estimate height in children and adolescents with cerebral palsy considering the level of gross motor function

BACKGROUND & AIMS

In children with Cerebral palsy (CP) bone deformities create a difficulty in the collection of height measures by direct methods. Body segments are an alternative to study for anthropometric evaluation in children with CP. Motor compromise affects growth in these children. To our knowledge, no equations have been developed to estimate height that consider the level of involvement of children with CP. The aim was to develop equations to estimate height using segmental measures for children with cerebral palsy (CP).

METHODS

This was a cross-sectional study. The sample consisted of children and adolescents with CP of both sexes from 2 to 19 years old from five cities in Argentina. Children whose height and knee-heel height (KH) could be measured were included. Height, KH, and clinical covariables were collected. Linear regression models with height as the dependent variable and KH as predictors adjusted for significant covariates were developed and compared for R2, adjusted R2, and the root mean square of the error.

RESULTS

242 children and adolescents (mean age 9 ± 4 years) with a confirmed diagnosis of CP were included. The interaction between height and other variables such KH, sex, GMFCS, and age was analyzed. Two equations were developed to estimate height according to GMFCS level (GMFCS Level I-III: H = 1.5 × KH(cm) + 2.28 × age(years) + 51; GMFCS Level IV-V: H = 2.13 × KH (cm)+ 0.91 × age(years) + 37). The concordance correlation coefficient between estimated and observed height was 0.95 (95%CI [0.94; 0.96]).

CONCLUSION

Height in children and adolescents with CP can be predicted using KH, GMFCS, and age. The equations and software can estimate height when this cannot be obtained directly.

The evolution of nutrition management in children with severe neurological impairment with a focus on cerebral palsy

Nutritional management of children with severe neurological impairment (SNI) is highly complex, and the profile of this population is changing. The aim of this narrative review was to give the reader a broad description of evolution of the nutritional management of children with SNI in a high resource setting. In the last decade, there has been an emphasis on using multiple anthropometric measures to monitor nutritional status in children with SNI, and several attempts at standardising the approach have been made. Tools such as the Feeding and Nutrition Screening Tool, the Subjective Global Nutrition Assessment, the Eating and Drinking Ability Classification System and the Focus on Early Eating and Drinking Swallowing (FEEDS) toolkit have become available. There has been an increased understanding of how the gut microbiome influences gastrointestinal symptoms common in children with SNI, and the use of fibre in the management of these has received attention. A new diagnosis, 'gastrointestinal dystonia', has been defined. The increased use and acceptance of blended food tube feeds has been a major development in the nutritional management of children with SNI, with reported benefits in managing gastrointestinal symptoms. New interventions to support eating and drinking skill development in children with SNI show promise. In conclusion, as the life expectancy of people with SNI increases due to advances in medical and nutrition care, our approach necessitates a view to long-term health and quality of life. This involves balancing adequate nutrition to support growth, development and well-being while avoiding overnutrition and its associated detrimental long-term effects.

Assessment Scales in Cerebral Palsy: A Comprehensive Review of Tools and Applications

Cerebral palsy (CP) is a complex neurological condition characterized by motor dysfunction affecting millions worldwide. This comprehensive review delves into the critical role of assessment in managing CP. Beginning with exploring its definition and background, we elucidate the diverse objectives of CP assessment, ranging from diagnosis and goal setting to research and epidemiology. We examine standard assessment scales and tools, discuss the challenges inherent in CP assessment, and highlight emerging trends, including integrating technology, personalized medicine, and neuroimaging. The applications of CP assessment in clinical diagnosis, treatment planning, research, and education are underscored. Recommendations for the future encompass standardization, interdisciplinary collaboration, research priorities, and professional training. In conclusion, we emphasize the importance of assessment as a compass guiding the care of individuals with CP, issuing a call to action for improved assessment practices to shape a brighter future for those affected by this condition.

Gurka vs Slaughter equations to estimate the fat percentage in children with cerebral palsy from all subtypes and levels of the Gross Motor Function Classification System

BACKGROUND

Body composition assessment in children with cerebral palsy (CP) is a challenge, specially the fat percentage. There are different methods that can be used to estimate the fat percentage in this population, such as anthropometric equations, but there is still a need to determine which is the best and most accurate. The purpose of the study was to determine the method that best estimates the fat percentage in children from all CP subtypes and levels of the Gross Motor Function Classification System (GMFCS).

METHODS

Analytical cross-sectional study in which 108 children with CP diagnosed by a pediatric neurologist were included with any type of dysfunction and from all levels of the GFMCS. Slaughter equation, Gurka equation and Bioelectrical impedance analysis (BIA) as reference method, were used. Groups were stratified by sex, CP subtypes, GMFCS level and Tanner stage. Median differences, Kruskal-Wallis, Mann-Whitney U test, Spearman's correlation coefficients and simple regressions were used, also multivariate models were performed.

RESULTS

The Slaughter equation differed from the other methods in the total population and when it was compared by sex, CP subtypes, gross motor function and Tanner stage. The Gurka equation showed significant differences by sex and gross motor function. Gurka equation correlated positively and significantly with BIA to estimate the fat percentage in all the CP subtypes and levels of the GMFCS. Tricipital skinfold (TSF), arm fat area (AFA) and weight for age index (W/A) showed the highest variability with respect to fat percentage.

CONCLUSION

Gurka equation is more appropriate and accurate than Slaughter equation to estimate the fat percentage in children with CP from all subtypes and levels of the GMFCS.

Prediction Model for Identifying Factors Associated with Epilepsy in Children with Cerebral Palsy

(1) Background: Cerebral palsy (CP) is associated with a higher incidence of epileptic seizures. This study uses a prediction model to identify the factors associated with epilepsy in children with CP. (2) Methods: This is a retrospective longitudinal study of the clinical characteristics of 102 children with CP. In the study, there were 58 males and 44 females, 65 inpatients and 37 outpatients, 72 had epilepsy, and 22 had intractable epilepsy. The mean age was 16.6 ± 1.2 years, and the age range for this study was 12−18 years. Data were collected on the CP etiology, diagnosis, type of epilepsy and spasticity, clinical history, communication abilities, behaviors, intellectual disability, motor function, and feeding abilities from 2005 to 2020. A prediction model, Epi-PredictMed, was implemented to forecast the factors associated with epilepsy. We used the guidelines of “Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis” (TRIPOD). (3) Results: CP etiology [(prenatal > perinatal > postnatal causes) p = 0.036], scoliosis (p = 0.048), communication (p = 0.018), feeding disorders (p = 0.002), poor motor function (p < 0.001), intellectual disabilities (p = 0.007), and the type of spasticity [(quadriplegia/triplegia > diplegia > hemiplegia), p = 0.002)] were associated with having epilepsy. The model scored an average of 82% for accuracy, sensitivity, and specificity. (4) Conclusion: Prenatal CP etiology, spasticity, scoliosis, severe intellectual disabilities, poor motor skills, and communication and feeding disorders were associated with epilepsy in children with CP. To implement preventive and/or management measures, caregivers and families of children with CP and epilepsy should be aware of the likelihood that these children will develop these conditions.