{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T20:31:39Z","timestamp":1791577899236,"version":"4.3.4"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T00:00:00Z","timestamp":1632096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:p>The controlling nutritional status (CONUT) score assesses nutritional status and is associated with short- and long-term prognoses in some diseases, but the significance of the CONUT score for the prediction of in-hospital mortality in older adults is unknown. The purpose was to determine the importance of the CONUT score for the prediction of in-hospital mortality, short-term complications, length of hospital stay, and hospital costs in older adults. Our retrospective cohort study analyzed data from 11,795 older adult patients from two multicenter cohort studies. We performed receiver operating characteristic curve analysis using in-hospital mortality as the endpoint and determined the appropriate CONUT score cut-off by the Youden index. The patients were divided into two high and low groups according to the CONUT cut-off value, and the differences in clinical characteristics and in-hospital clinical outcomes between the two groups were compared. We compared the accuracy of the CONUT score and other nutrition-related tools in predicting in-hospital mortality by calculating the area under the receiver operating characteristic curve and performed univariate and multivariate analyses of predictors of in-hospital mortality. Among all the patients, 178 (1.5%) patients experienced in-hospital death. The optimal cut-off values was 5.5 for the CONUT score. The high CONUT group had a higher incidence of short-term complications and prolonged hospital stay than the low CONUT group (CONUT score &amp;lt;6), but hospital costs were not significantly higher. The CONUT score had the highest predictive ability for in-hospital mortality among the five nutrition-related parameters compared. Multivariate analysis showed that a high CONUT score (CONUT score \u2265 6) was an independent predictor of in-hospital mortality. In conclusion, the present study demonstrated that the CONUT score could be used to predict in-hospital mortality in older adults.<\/jats:p>","DOI":"10.3389\/fnut.2021.738045","type":"journal-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T04:53:12Z","timestamp":1632113592000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":34,"title":["Controlling Nutritional Status Score as a Predictive Marker of In-hospital Mortality in Older Adult Patients"],"prefix":"10.3389","volume":"8","author":[{"given":"Chengyu","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingwei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyuan","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zijian","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junmin","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,9,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1282","DOI":"10.1016\/j.clnu.2016.03.008","article-title":"Nutritional status in older persons according to healthcare setting: A systematic review and meta-analysis of prevalence data using MNA(\u00ae)","volume":"35","author":"Cereda","year":"2016","journal-title":"Clin Nutr."},{"key":"B2","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.clnu.2013.04.008","article-title":"Nutrition screening tools: does one size fit all? 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