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Comparison of the glim, espen and icd-10 criteria to diagnose malnutrition and predict 30-day outcomes: An observational study in an oncology population
journal contribution
posted on 2021-07-28, 00:00 authored by S Poulter, B Steer, Brenton BaguleyBrenton Baguley, L Edbrooke, Nicole KissNicole KissThe Global Leadership Initiative on Malnutrition (GLIM) criteria are consensus criteria for the diagnosis of malnutrition. This study aimed to investigate and compare the prevalence of malnutrition using the GLIM, European Society for Clinical Nutrition and Metabolism (ESPEN) and International Statistical Classification of Diseases version 10 (ICD-10) criteria; compare the level of agreement between these criteria; and identify the predictive validity of each set of criteria with respect to 30-day outcomes in a large cancer cohort. GLIM, ESPEN and ICD-10 were applied to determine the prevalence of malnutrition in 2794 participants from two cancer malnutrition point prevalence studies. Agreement between the criteria was analysed using the Cohen’s Kappa statistic. Binary logistic regression models were used to determine the ability of each set of criteria to predict 30-day mortality and unplanned admission or readmission. GLIM, ESPEN and ICD-10 criteria identified 23.0%, 5.5% and 12.6% of the cohort as malnourished, respectively. Slight-to-fair agreement was reported between the criteria. All three criteria were predictive of mortality, but only the GLIM and ICD-10 criteria were predictive of unplanned admission or readmission at 30 days. The GLIM criteria identified the highest prevalence of malnutrition and had the greatest predictive ability for mortality and unplanned admission or readmission in an oncology population.
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Journal
NutrientsVolume
13Issue
8Article number
ARTN 2602Pagination
1 - 13Publisher
MDPI / MDPI AG (Multidisciplinary Digital Publishing Institute)Location
Basel, SwitzerlandPublisher DOI
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ISSN
2072-6643eISSN
2072-6643Language
EnglishPublication classification
C1 Refereed article in a scholarly journalUsage metrics
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