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Malnutrition risk in hospitalized children: use of 3 screening tools in a large European population.

Ludwig-Maximilians-University of Munich, Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Centre, Munich, Germany; Human Nutrition, School of Medicine, College of Medicine, Veterinary and Life Sciences, Royal Hospital for Sick Children, University of Glasgow, Glasgow, United Kingdom; Erasmus Medical Center, Sophia Children's Hospital, Department of Pediatrics, Rotterdam, Netherlands; Clinical Nutrition Laboratory, Nutrition/Dietetics Department, Technological Education Institute, Thessaloniki, Greece; Beatrix Children's Hospital, University Hospital Groningen, Groningen, Netherlands; Department of Pediatrics, Nutrition and Metabolic Diseases, The Children's Memorial Health Institute, Warsaw, Poland; Clinic Pediatrics I, Clinical Emergency Hospital for Children, Cluj-Napoca (Klausenburg), Romania; Institute of Gastroenterology, Nutrition and Liver Diseases, Schneider Children's Medical Center of Israel, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; and. Department of Pediatrics, Medical University of Warsaw, Warsaw, Poland. Ludwig-Maximilians-University of Munich, Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Centre, Munich, Germany; office.koletzko@med.uni-muenchen.de.

The American journal of clinical nutrition. 2016;(5):1301-10
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Abstract

BACKGROUND Several malnutrition screening tools have been advocated for use in pediatric inpatients. OBJECTIVE We evaluated how 3 popular pediatric nutrition screening tools [i.e., the Pediatric Yorkhill Malnutrition Score (PYMS), the Screening Tool for the Assessment of Malnutrition in Pediatrics (STAMP), and the Screening Tool for Risk of Impaired Nutritional Status and Growth (STRONGKIDS)] compared with and were related to anthropometric measures, body composition, and clinical variables in patients who were admitted to tertiary hospitals across Europe. DESIGN The 3 screening tools were applied in 2567 inpatients at 14 hospitals across 12 European countries. The classification of patients into different nutritional risk groups was compared between tools and related to anthropometric measures and clinical variables [e.g., length of hospital stay (LOS) and infection rates]. RESULTS A similar rate of completion of the screening tools for each tool was achieved (PYMS: 86%; STAMP 84%; and STRONGKIDS 81%). Risk classification differed markedly by tool, with an overall agreement of 41% between tools. Children categorized as high risk (PYMS: 25%; STAMP 23%; and STRONGKIDS 10%) had a longer LOS than that of children at low risk (1.4, 1.4, and 1.8 d longer, respectively; P < 0.001). In high-risk patients identified with the PYMS, 22% of them had low (<-2) body mass index (BMI) SD-scores (SDSs), and 8% of them had low height-for-age SDSs. For the STAMP, the percentages were 19% and 14%, respectively, and for the STRONGKIDS, the percentages were 23% and 19%, respectively. CONCLUSIONS The identification and classification of malnutrition risk varied across the pediatric tools used. A considerable portion of children with subnormal anthropometric measures were not identified with all of the tools. The data obtained do not allow recommending the use of any of these screening tools for clinical practice. This study was registered at clinicaltrials.gov as NCT01132742.

Methodological quality

Publication Type : Observational Study

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