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dc.contributor.authorHeinrich, M
dc.contributor.authorWoike, Jan Kristian
dc.contributor.authorSpies, CD
dc.contributor.authorWegwarth, O
dc.date.accessioned2022-09-24T12:10:39Z
dc.date.issued2022-09-24
dc.identifier.issn2077-0383
dc.identifier.issn2077-0383
dc.identifier.other5629
dc.identifier.urihttp://hdl.handle.net/10026.1/19635
dc.description.abstract

<jats:p>Postoperative delirium (POD) is associated with increased complication and mortality rates, particularly among older adult patients. However, guideline recommendations for POD detection and management are poorly implemented. Fast-and-frugal trees (FFTrees), which are simple prediction algorithms, may be useful in this context. We compared the capacity of simple FFTrees with two more complex models—namely, unconstrained classification trees (UDTs) and logistic regression (LogReg)—for the prediction of POD among older surgical patients in the perioperative setting. Models were trained and tested on the European BioCog project clinical dataset. Based on the entire dataset, two different FFTrees were developed for the pre-operative and postoperative settings. Within the pre-operative setting, FFTrees outperformed the more complex UDT algorithm with respect to predictive balanced accuracy, nearing the prediction level of the logistic regression. Within the postoperative setting, FFTrees outperformed both complex models. Applying the best-performing algorithms to the full datasets, we proposed an FFTree using four cues (Charlson Comorbidity Index (CCI), site of surgery, physical status and frailty status) for the pre-operative setting and an FFTree containing only three cues (duration of anesthesia, age and CCI) for the postoperative setting. Given that both FFTrees contained considerably fewer criteria, which can be easily memorized and applied by health professionals in daily routine, FFTrees could help identify patients requiring intensified POD screening.</jats:p>

dc.format.extent5629-5629
dc.format.mediumElectronic
dc.languageen
dc.language.isoen
dc.publisherMDPI
dc.subjectfast-and-frugal decision trees
dc.subjectpostoperative outcomes
dc.subjectpostoperative delirium
dc.subjectclinical data prediction
dc.subjectmedical decision making
dc.titleForecasting postoperative delirium in older adult patients with Fast-and-Frugal decision trees
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000867966600001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue19
plymouth.volume11
plymouth.publication-statusPublished online
plymouth.journalJournal of Clinical Medicine
dc.identifier.doi10.3390/jcm11195629
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Health
plymouth.organisational-group/Plymouth/Faculty of Health/School of Psychology
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA04 Psychology, Psychiatry and Neuroscience
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA04 Psychology, Psychiatry and Neuroscience/UoA04 Psychology, Psychiatry and Neuroscience MANUAL
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.publisher.placeSwitzerland
dcterms.dateAccepted2022-09-21
dc.rights.embargodate2022-9-27
dc.identifier.eissn2077-0383
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.3390/jcm11195629
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeJournal Article/Review


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