ArticleThe American journal of clinical nutrition2020
Use of standardized body composition measurements and malnutrition screening tools to detect malnutrition risk and predict clinical outcomes in children with chronic conditions.
Article in The American journal of clinical nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Efficacy of long-term oral nutritional supplementation with dietary counseling on growth, body composition and bone mineralization in children with or at risk for undernutrition: a randomized controlled trial.Nutrition journal · 2025Trial
- Primary Immunodeficiency Diseases with BCG-Induced Diseases: A 15-Year Longitudinal Cohort Study.Journal of clinical immunology · 2026Article
- Comparative evaluation of nutritional risk screening tools in hospitalized children with acute gastroenteritis.Frontiers in nutrition · 2026Article
- Anthropometric and Body-Composition Changes in Severely Acute Malnourished Children (12-59 Months) Post-Nutritional Rehabilitation: A Follow-Up Study.Pediatric gastroenterology, hepatology & nutrition · 2025Article
- Height status matters for risk of mortality in critically ill children.Journal of intensive care · 2024Article
- Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans.The American journal of clinical nutrition · 2023Article
- Fat and lean mass predict time to hospital readmission or mortality in children treated for complicated severe acute malnutrition in Zimbabwe and Zambia.The British journal of nutrition · 2023Article
- Centile reference chart for resting metabolic rate through the life course.Archives of disease in childhood · 2023Article
- Disease-Related Malnutrition in Pediatric Patients with Chronic Disease: A Developing Country Perspective.Current developments in nutrition · 2023Review
- Carbapenem-resistant Enterobacterales colonization and subsequent infection in a neonatal intensive care unit in Shanghai, China.Infection prevention in practice · 2021Article
- Assessment of nutritional status in paediatric outpatients using bioelectrical impedance analysis and anthropometric z-scores.Journal of paediatrics and child health · 2021Article
- Nuchal Skinfold Thickness in Pediatric Brain Tumor Patients.Frontiers in endocrinology · 2021Article
- Body Composition Characteristics of a Load-Capacity Model: Age-Dependent and Sex-Specific Percentiles in 5- to 17-Year-Old Children.Obesity facts · 2021Article
- Pediatric undernutrition defined by body composition-are we there yet?The American journal of clinical nutrition · 2020Article
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10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundBetter tools are needed to diagnose and identify children at risk of clinical malnutrition.
objectivesWe aimed to compare body composition (BC) and malnutrition screening tools (MSTs) for detecting malnutrition on admission; and examine their ability to predict adverse clinical outcomes [increased length of stay (LOS) and complications] in complex pediatric patients.
methodsThis was a prospective study in children 5-18 y old admitted to a tertiary pediatric hospital (n = 152). MSTs [Pediatric Yorkhill Malnutrition Score (PYMS), Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), and Screening Tool for Risk of Impaired Nutritional Status and Growth (STRONGkids)] were completed on admission. Weight, height, and BC [fat mass (FM) and lean mass (LM) by DXA] were measured (n = 118). Anthropometry/BC and MSTs were compared with each other and with clinical outcomes.
resultsSubjects were significantly shorter with low LM compared to reference data. Depending on the diagnostic criteria used, 3%-17% were classified as malnourished. Agreement between BC/anthropometric parameters and MSTs was poor. STAMP and STRONGkids identified children with low weight, LM, and height. PYMS, and to a lesser degree STRONGkids, identified children with increased LOS, as did LM compared with weight or height. Patients with complications had lower mean ± SD LM SD scores (-1.38 ± 1.03 compared with -0.74 ± 1.40, P < 0.05). In multivariable models, PYMS high risk and low LM were independent predictors of increased LOS (OR: 3.76; 95% CI: 1.36, 10.35 and OR: 3.69; 95% CI: 1.24, 10.98, respectively). BMI did not predict increased LOS or complications.
conclusionsLM appears better than weight and height for predicting adverse clinical outcomes in this population. BMI was a poor diagnostic parameter. MSTs performed differently in associations to BC/anthropometry and clinical outcomes. PYMS and LM provided complementary information regarding LOS. Studies on specific patient populations may further clarify the use of these tools and measurements.
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