{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T11:06:27Z","timestamp":1780398387332,"version":"3.54.1"},"reference-count":37,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T00:00:00Z","timestamp":1623801600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nursing in Critical Care"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>The early prediction model for delirium in intensive care units (ICUs)\u2014E\u2010PRE\u2010DELIRIC\u2014has been created to predict delirium development during the length of stay in ICUs. However, there have been few early predictive models for delirium in the cardiac surgical ICU (CSICU), and the predictive ability of the E\u2010PRE\u2010DELIRIC among patients following cardiac surgeries is still unknown.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims and objectives<\/jats:title><jats:p>To validate the performance of E\u2010PRE\u2010DELIRIC in CSICU.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>A retrospective cohort study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data were retrospectively extracted from the electronic records for patients admitted in CSICU from January 2018 to December 2018 in a tertiary teaching hospital in China. Adult patients were included following the criteria of the E\u2010PRE\u2010DELIRIC model. Predictors, including age, history of cognitive impairment, history of alcohol abuse, urgent admission, use of corticosteroids, respiratory failure, blood urea nitrogen, and mean arterial pressure, at the time of ICU admission were retrieved, and delirium was assessed twice a day using the Confusion Assessment Method for the ICU. The performance of the E\u2010PRE\u2010DELIRIC model was evaluated by area under receiver operator characteristic curve, precision\u2010recall curve (AUPRC), Hosmer\u2010Lemeshow (HL) test, and calibration belt.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Of the 725 patients included, 120 (16.6%) developed delirium. The AUROC was 0.54 (95% confidence interval [CI], 0.48\u20100.59), and the AUPRC was 0.18 (95% CI, 0.12\u20100.20). The HL test showed a significant difference between predicted probability and delirium occurrence (<jats:italic>\u03c7<\/jats:italic><jats:sup>2<\/jats:sup> =\u200917.326, <jats:italic>P<\/jats:italic> = .027), and the overestimation chance of the E\u2010PRE\u2010DELIRIC score was 0.24 to 0.43.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The E\u2010PRE\u2010DELIRIC model has poor\u2010to\u2010fair predictive value in this study; thus, its application among the CSICU patients is limited. Development of reliable and validated tools for early prediction of delirium in CSICU is required.<\/jats:p><\/jats:sec><jats:sec><jats:title>Relevance to clinical practice<\/jats:title><jats:p>Early prediction of delirium risk at CSICU admission is of vital importance and could provide timely information to caregivers. However, the E\u2010PRE\u2010DELIRIC model should be applied cautiously in the CSICU because of the significant probability of over\u2010estimating the risk of developing delirium.<\/jats:p><\/jats:sec>","DOI":"10.1111\/nicc.12674","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T11:42:40Z","timestamp":1623843760000},"page":"233-239","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Validation of E\u2010PRE\u2010DELIRIC in cardiac surgical ICU delirium: A retrospective cohort study"],"prefix":"10.1111","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7404-5485","authenticated-orcid":false,"given":"Wen","family":"Gao","sequence":"first","affiliation":[{"name":"Nursing Department The Second Affiliated Hospital of Zhejiang University  Hangzhou China"},{"name":"Nursing Department, School of Medicine Zhejiang University  Hangzhou 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