Use Of Standardized Body Composition Measurements And Malnutrition Screening Tools To Detect Malnutrition Risk And Predict Clinical Outcomes In Children With Chronic Conditions

Background: Better tools are needed to diagnose and identify children at risk of clinical malnutrition.Objectives: We 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.Methods: This 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.Results: Subjects 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.Conclusions: LM 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.