Malnutrition Screening And Body Composition Measurements In Paediatric Patients With Complex Diagnosis: Translating Research Into Clinical Practice

BACKGROUND: Paediatric patients have a high risk for malnutrition, and there is an increasing consensus worldwide on the need to find better tools to identify the risk, diagnose, and manage this condition to avoid the long-term consequences in child health and development. OBJECTIVE: Evaluate the practical aspects of measuring body composition (BC) in paediatric patients with complex conditions, and their possible advantages over measurements of weight/height to predict clinical outcomes and as possible malnutrition diagnostic parameters; while also validating three paediatric malnutrition screening tools (MSTs). DESIGN: This prospective study recruited and measured 152 children 5-18yr with different anthropometric and BC techniques within 48hr of admission and at discharge to a tertiary level hospital. MSTs (PYMS, STAMP, STRONGkids) were completed on admission and data collected on clinical outcomes: length of stay, complications, and worsening nutritional status. RESULTS: BC measurements by different techniques are practical and acceptable overall in paediatric patients. Malnutrition was prevalent in 13-20% of patients, measured by different anthropometric/BC parameters. Patients were on average short and underweight compared to healthy children, and had abnormal BC (low lean mass, variable fat mass). The parameters were significantly associated with clinical outcomes, and there seemed to be an advantage for BC to predict increased LOS and complications. Similarly, malnutrition risk on admission varied depending on the MST used. STAMP and STRONGkids were significantly associated with baseline weight, height, lean and fat mass; while PYMS had better associations to clinical outcomes (increased LOS). CONCLUSION: Malnutrition is relatively common, and BC measurements seem to have a place in the diagnosis and possibly the nutritional management of paediatric patients. Future work with specific patient groups and outcomes should help clarify what parameters/tools are the most helpful to ultimately decrease the prevalence of hospital malnutrition

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

Bioelectric impedance vector analysis (BIVA) in hospitalised children; predictors and associations with clinical outcomes

BACKGROUND: Clinical use of bioelectric impedance is limited by variability in hydration. Analysis of raw bioelectric impedance vectors (BIVA), resistance (R), reactance (Xc) and phase angle (PA) may be an alternative for monitoring disease progression/treatment. Clinical experience of BIVA in children is limited. We investigated predictors of BIVA and their ability to predict clinical outcomes in children with complex diagnoses. METHODS: R, Xc and PA were measured (BODYSTAT Quadscan 4000) on admission in 108 patients (4.6-16.8 years, mean 10.0). R and Xc were indexed by height (H) and BIVA-SDS for age and sex calculated using data from healthy children. Potential predictors and clinical outcomes (greater-than-expected length-of-stay (LOS), complications) were recorded. RESULTS: Mean R/H-SDS was significantly higher (0.99 (SD 1.32)) and PA-SDS lower (-1.22 (1.68))) than expected, with a wide range for all parameters. In multivariate models, the Strongkids risk category predicted R/H-SDS (adjusted mean for low, medium and high risk = 0.49, 1.28, 2.17, p = 0.009) and PA-SDS (adjusted mean -0.52, -1.53, -2.36, p = 0.01). BIVA-SDS were not significantly different in patients with or without adverse outcomes. CONCLUSIONS: These complex patients had abnormal mean BIVA-SDS suggestive of reduced hydration and poor cellular health according to conventional interpretation. R/H-SDS was higher and PA-SDS lower in those classified as higher malnutrition risk by the StrongKids tool. Further investigation in specific patient groups, including those with acute fluid shifts and using disease-specific outcomes, may better define the clinical role of BIV