{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:33:16Z","timestamp":1762432396536,"version":"build-2065373602"},"reference-count":41,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007656","name":"Loyola University Chicago","doi-asserted-by":"publisher","award":["Center for Health Outcomes and Informatics Research"],"award-info":[{"award-number":["Center for Health Outcomes and Informatics Research"]}],"id":[{"id":"10.13039\/100007656","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aspenjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nut in Clin Prac"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Patients with low muscle mass and acute SARS\u2010CoV\u20102 infection meet the Global Leadership Initiative on Malnutrition (GLIM) etiologic and phenotypic criteria to diagnose malnutrition, respectively. However, available cut\u2010points to classify individuals with low muscle mass are not straightforward. Using computed tomography (CT) to determine low muscularity, we assessed the prevalence of malnutrition using the GLIM framework and associations with clinical outcomes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective cohort was conducted gathering patient data from various clinical resources. Patients admitted to the COVID\u201019 unit (March 2020 to June 2020) with appropriate\/evaluable CT studies (chest or abdomen\/pelvis) within the first 5 days of admission were considered eligible. Sex\u2010 and vertebral\u2010specific skeletal muscle indices (SMI; cm<jats:sup>2<\/jats:sup>\/m<jats:sup>2<\/jats:sup>) from healthy controls were used to determine low muscle mass. Injury\u2010adjusted SMI were derived, extrapolated from cancer cut\u2010points and explored. Descriptive statistics and mediation analyses were completed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Patients (<jats:italic>n<\/jats:italic>\u2009=\u2009141) were 58.2 years of age and racially diverse. Obesity (46%), diabetes (40%), and cardiovascular disease (68%) were prevalent. Using healthy controls and injury\u2010adjusted SMI, malnutrition prevalence was 26% (<jats:italic>n<\/jats:italic>\u2009=\u200936\/141) and 50% (<jats:italic>n<\/jats:italic>\u2009=\u200971\/141), respectively. Mediation analyses demonstrated a significant reduction in the effect of malnutrition on outcomes in the presence of Acute Physiology and Chronic Health Evaluation II, supporting the mediating effects of severity of illness intensive care unit (ICU) admission, ICU length of stay, mechanical ventilation, complex respiratory support, discharge status (all <jats:italic>P<\/jats:italic> values\u2009=\u20090.03), and 28\u2010day mortality (<jats:italic>P<\/jats:italic>\u2009=\u20090.04).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Future studies involving the GLIM criteria should consider these collective findings in their design, analyses, and implementation.<\/jats:p><\/jats:sec>","DOI":"10.1002\/ncp.11024","type":"journal-article","created":{"date-parts":[[2023,6,14]],"date-time":"2023-06-14T00:11:31Z","timestamp":1686701491000},"page":"1009-1020","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Applying the Global Leadership Initiative on Malnutrition criteria in patients admitted with SARS\u2010CoV\u20102 infection using computed tomography imaging"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0032-514X","authenticated-orcid":false,"given":"Patricia","family":"Sheean","sequence":"first","affiliation":[{"name":"Parkinson School of Health Sciences and Public Health Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paula","family":"O'Connor","sequence":"additional","affiliation":[{"name":"Parkinson School of Health Sciences and Public Health Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cara","family":"Joyce","sequence":"additional","affiliation":[{"name":"Clinical Research Office Loyola University Chicago Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amy","family":"Wozniak","sequence":"additional","affiliation":[{"name":"Clinical Research Office Loyola University Chicago Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vasilios","family":"Vasilopoulos","sequence":"additional","affiliation":[{"name":"Department of Radiology (3D lab) Loyola University Medical Center Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Perry","family":"Formanek","sequence":"additional","affiliation":[{"name":"Department of Medicine Loyola University Medical Center Maywood Illinois USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,6,13]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/jcsm.12383"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/jpen.1440"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30183-5"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2020.0994"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.metabol.2020.154244"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.15585\/mmwr.mm7010e4"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/ijo.2010.5"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0216991"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1186\/cc12901"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clnu.2012.12.012"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1152\/jappl.1998.85.1.115"},{"issue":"1","key":"e_1_2_10_13_1","first-page":"53","article-title":"Adipose tissue volume determinations in women by computed tomography: technical considerations","volume":"10","author":"Kvist H","year":"1986","journal-title":"Int J Obes"},{"issue":"6","key":"e_1_2_10_14_1","first-page":"570","article-title":"Measuring visceral adipose tissue content from contrast enhanced computed tomography","volume":"20","author":"Vehmas T","year":"1996","journal-title":"Int J Obes Relat Metab Disord"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1139\/H08-075"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.nutr.17.1.527"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1152\/japplphysiol.00744.2004"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1177\/0148607113500308"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1186\/cc13189"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.clnesp.2018.03.122"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-29825-5"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1097\/00003246-198510000-00009"},{"key":"e_1_2_10_23_1","unstructured":"Underlying Medical Conditions Associated with Higher Risk for Severe COVID\u201019: Information for Healthcare Professionals. 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