Comparison of the glim, espen and icd-10 criteria to diagnose malnutrition and predict 30-day outcomes: An observational study in an oncology population Poulter, S, Steer, B, Baguley, Brenton, Edbrooke, L and Kiss, Nicole 2021, Comparison of the glim, espen and icd-10 criteria to diagnose malnutrition and predict 30-day outcomes: An observational study in an oncology population, Nutrients, vol. 13, no. 8, pp. 1-13, doi: 10.3390/nu13082602. Attached Files Name Description MIMEType Size Downloads Title Comparison of the glim, espen and icd-10 criteria to diagnose malnutrition and predict 30-day outcomes: An observational study in an oncology population Author(s) Poulter, S Steer, B Baguley, Brenton orcid.org/0000-0003-3974-8107 Edbrooke, L Kiss, Nicole orcid.org/0000-0002-6476-9834 Journal name Nutrients Volume number 13 Issue number 8 Article ID ARTN 2602 Start page 1 End page 13 Total pages 13 Publisher MDPI / MDPI AG (Multidisciplinary Digital Publishing Institute) Place of publication Basel, Switzerland Publication date 2021-07-28 ISSN 2072-6643 2072-6643 Keyword(s) Science & Technology Life Sciences & Biomedicine Nutrition & Dietetics GLIM ESPEN ICD-10 malnutrition cancer predictive validity mortality unplanned admission NUTRITIONAL-STATUS SCREENING TOOL PREVALENCE IMPACT RISK SURVIVAL SUPPORT Summary The 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. Language eng DOI 10.3390/nu13082602 Field of Research 0908 Food Sciences 1111 Nutrition and Dietetics HERDC Research category C1 Refereed article in a scholarly journal Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30154155 Document type: Journal Article Collections: Faculty of Health Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version Go to link with your DU access privileges   Connect to Elements publication management system Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Thu, 05 Aug 2021, 08:25:47 EST Fri, 06 Aug 2021, 05:00:37 EST Fri, 06 Aug 2021, 06:03:45 EST Fri, 06 Aug 2021, 09:24:16 EST Sat, 07 Aug 2021, 02:46:11 EST Sat, 18 Sep 2021, 02:35:57 EST Fri, 24 Jun 2022, 13:37:20 EST Fri, 24 Jun 2022, 13:47:24 EST Fri, 24 Jun 2022, 13:53:36 EST Tue, 05 Jul 2022, 16:13:11 EST Tue, 19 Jul 2022, 10:52:10 EST Thu, 28 Jul 2022, 07:35:17 EST Filtered Full Citation counts:   Cited 2 times in TR Web of Science Cited 2 times in Scopus Search Google Scholar Access Statistics: 14 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Thu, 05 Aug 2021, 08:25:47 EST