2021
DOI: 10.1111/dmcn.14981
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Nutritional screening of children and adolescents with cerebral palsy: a scoping review

Abstract: Aim To examine nutritional screening methods for children and adolescents with cerebral palsy. Method A scoping review was performed using established methodologies. In June 2020 we searched PubMed, Embase, CINAHL Complete, and the Cochrane Central Register of Controlled Trials to identify articles on tools/methods for nutritional screening of our target groups. Results Thirty studies were included, containing various tools/methods used to identify under‐ and/or overnutrition by weight/height, circumferences, … Show more

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Cited by 10 publications
(10 citation statements)
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References 57 publications
(401 reference statements)
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“…The subjective clinical assessment (i.e., visible severe wasting) is considered to perform poorer than any anthropometry-based method, while WFH/l-based case-detection methods are considered to perform worse than MUAC, especially in certain circumstances ( 39 , 40 ). Hence, MUAC, based on the currently available evidence, is considered to be the best case-detection method for pediatric malnutrition in terms of easiness, age independence, precision, accuracy, sensitivity, specificity and lack of special equipment, formal training requirement or calculation ( Table 2 ) ( 39 , 40 ).…”
Section: The Significance Of Muac As a Single Datapoint Measurementmentioning
confidence: 99%
See 2 more Smart Citations
“…The subjective clinical assessment (i.e., visible severe wasting) is considered to perform poorer than any anthropometry-based method, while WFH/l-based case-detection methods are considered to perform worse than MUAC, especially in certain circumstances ( 39 , 40 ). Hence, MUAC, based on the currently available evidence, is considered to be the best case-detection method for pediatric malnutrition in terms of easiness, age independence, precision, accuracy, sensitivity, specificity and lack of special equipment, formal training requirement or calculation ( Table 2 ) ( 39 , 40 ).…”
Section: The Significance Of Muac As a Single Datapoint Measurementmentioning
confidence: 99%
“…The subjective clinical assessment (i.e., visible severe wasting) is considered to perform poorer than any anthropometry-based method, while WFH/l-based case-detection methods are considered to perform worse than MUAC, especially in certain circumstances ( 39 , 40 ). Hence, MUAC, based on the currently available evidence, is considered to be the best case-detection method for pediatric malnutrition in terms of easiness, age independence, precision, accuracy, sensitivity, specificity and lack of special equipment, formal training requirement or calculation ( Table 2 ) ( 39 , 40 ). Simplicity: MUAC was reported to be faster and easier to perform screening in the community setting than other indicators including WFA, HFA and WFH ( 41 ) and to reveal immediate classifications of malnutrition by using a readily understandable “traffic light” system with colors ( 39 ).…”
Section: The Significance Of Muac As a Single Datapoint Measurementmentioning
confidence: 99%
See 1 more Smart Citation
“…The assessment of nutritional status in children with cerebral palsy (CP) is not simple [ 1 ]. Therefore, the measurement and evaluation of body composition should be considered an essential and routine indicator in the evaluation, assessment, and nutritional intervention of these children [ 2 6 ].…”
Section: Introductionmentioning
confidence: 99%
“…For children with CP, anthropometric measurements can be difficult to assess, mainly if they have contractures, spasticity, scoliosis, and positioning problems that hinder the use of conventional weighing and other measuring methods [ 20 ]. In the last few decades, several indirect methods to determine anthropometrics in children with CP were developed, albeit with no consensus on the ideal one/ones despite de extensive discussion on the topic [ 20 , 21 , 22 ]. A variety of growth charts can be used to assess and monitor growth [ 23 ].…”
Section: Introductionmentioning
confidence: 99%