Sedat Arslan, Nursel Dal, Kevser Tari Selcuk, Kezban Sahin, Ramazan Mert Atan
{"title":"Identifying malnutrition risk in hospitalized patients: an analysis of five tools in the light of GLIM criteria.","authors":"Sedat Arslan, Nursel Dal, Kevser Tari Selcuk, Kezban Sahin, Ramazan Mert Atan","doi":"10.1080/00325481.2024.2363169","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The prompt identification of malnutrition among hospitalized patients using the appropriate screening tool is paramount. The objective of our study is to compare the most recommended screening tools concerning the new GLIM criteria for malnutrition in hospitalized patients.</p><p><strong>Methods: </strong>In this cross-sectional study, we analyzed the data on 1,397 patients receiving inpatient treatment at Bandırma Training and Research Hospital between August 2022 and May 2023 to assess and compare malnutrition in them. Patients who received inpatient treatment in the internal and surgical clinics of Bandırma Training and Research Hospital. In addition to the GLIM criteria, we used nutritional screening and assessment tools such as NRS-2002, MST, GMS, MUST, and SNAQ. The GLIM criteria were considered the gold standard for the evaluation of sensitivity and specificity. Receiver operating characteristic (ROC) curves for the five screening tools were also used to assess the ability to distinguish malnutrition-risk patients accurately.</p><p><strong>Results: </strong>The comparison of the performances of different screening tools in detecting malnutrition demonstrated that while the GMS had the highest sensitivity (87.40%), the NRS-2002 had the highest specificity (91.70%). The area under the Curve (AUC) value indicated that the predictive values of the NRS-2002, MST, GMS, and SNAQ were excellent, and the predictive value of the MUST was good (<i>p</i> < 0.001). While the GLIM criteria in particular appear to be an effective tool for detecting malnutrition in hospitalized individuals, other screening tools are also useful in assessing their malnutrition risk.</p><p><strong>Conclusions: </strong>We emphasized MST's alignment with GLIM criteria, underscoring the importance of a multidisciplinary approach for early malnutrition diagnosis. Patients at risk of malnutrition can be diagnosed more quickly and accurately with appropriate screening tools and the effectiveness of treatments can be increased.</p>","PeriodicalId":94176,"journal":{"name":"Postgraduate medicine","volume":" ","pages":"504-513"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Postgraduate medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/00325481.2024.2363169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/4 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The prompt identification of malnutrition among hospitalized patients using the appropriate screening tool is paramount. The objective of our study is to compare the most recommended screening tools concerning the new GLIM criteria for malnutrition in hospitalized patients.
Methods: In this cross-sectional study, we analyzed the data on 1,397 patients receiving inpatient treatment at Bandırma Training and Research Hospital between August 2022 and May 2023 to assess and compare malnutrition in them. Patients who received inpatient treatment in the internal and surgical clinics of Bandırma Training and Research Hospital. In addition to the GLIM criteria, we used nutritional screening and assessment tools such as NRS-2002, MST, GMS, MUST, and SNAQ. The GLIM criteria were considered the gold standard for the evaluation of sensitivity and specificity. Receiver operating characteristic (ROC) curves for the five screening tools were also used to assess the ability to distinguish malnutrition-risk patients accurately.
Results: The comparison of the performances of different screening tools in detecting malnutrition demonstrated that while the GMS had the highest sensitivity (87.40%), the NRS-2002 had the highest specificity (91.70%). The area under the Curve (AUC) value indicated that the predictive values of the NRS-2002, MST, GMS, and SNAQ were excellent, and the predictive value of the MUST was good (p < 0.001). While the GLIM criteria in particular appear to be an effective tool for detecting malnutrition in hospitalized individuals, other screening tools are also useful in assessing their malnutrition risk.
Conclusions: We emphasized MST's alignment with GLIM criteria, underscoring the importance of a multidisciplinary approach for early malnutrition diagnosis. Patients at risk of malnutrition can be diagnosed more quickly and accurately with appropriate screening tools and the effectiveness of treatments can be increased.