{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T01:28:24Z","timestamp":1790558904565,"version":"4.1.0"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T00:00:00Z","timestamp":1716336000000},"content-version":"vor","delay-in-days":21,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"German Federal Ministry of Education and Research","award":["01GY2101"],"award-info":[{"award-number":["01GY2101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Post-operative delirium (POD) is a common complication in older patients, with an incidence of 14\u201356%. To implement preventative procedures, it is necessary to identify patients at risk for POD. In the present study, we aimed to develop a machine learning (ML) model for POD prediction in older patients, in close cooperation with the PAWEL (patient safety, cost-effectiveness and quality of life in elective surgery) project.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The model was trained on the PAWEL study\u2019s dataset of 878 patients (no intervention, age\u2009\u2265\u200970, 209 with POD). Presence of POD was determined by the Confusion Assessment Method and a chart review. We selected 15 features based on domain knowledge, ethical considerations and a recursive feature elimination. A logistic regression and a linear support vector machine (SVM) were trained, and evaluated using receiver operator characteristics (ROC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The selected features were American Society of Anesthesiologists score, multimorbidity, cut-to-suture time, estimated glomerular filtration rate, polypharmacy, use of cardio-pulmonary bypass, the Montreal cognitive assessment subscores \u2018memory\u2019, \u2018orientation\u2019 and \u2018verbal fluency\u2019, pre-existing dementia, clinical frailty scale, age, recent falls, post-operative isolation and pre-operative benzodiazepines. The linear SVM performed best, with an ROC area under the curve of 0.82 [95% CI 0.78\u20130.85] in the training set, 0.81 [95% CI 0.71\u20130.88] in the test set and 0.76 [95% CI 0.71\u20130.79] in a cross-centre validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We present a clinically useful and explainable ML model for POD prediction. The model will be deployed in the Supporting SURgery with GEriatric Co-Management and AI project.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ageing\/afae101","type":"journal-article","created":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T16:48:24Z","timestamp":1715618904000},"source":"Crossref","is-referenced-by-count":21,"title":["Introducing a machine learning algorithm for delirium prediction\u2014the Supporting SURgery with GEriatric Co-Management and AI project (SURGE-Ahead)"],"prefix":"10.1093","volume":"53","author":[{"given":"Samuel","family":"Benovic","sequence":"first","affiliation":[{"name":"Institute of Geriatric Research, Ulm University Medical Center , Ulm , Germany"},{"name":"Agaplesion Bethesda Clinic Ulm , Ulm , Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna H","family":"Ajlani","sequence":"additional","affiliation":[{"name":"Institute of the History , Philosophy and Ethics of Medicine, , Ulm , Germany"},{"name":"Ulm University , Philosophy and Ethics of Medicine, , Ulm , Germany"},{"name":"Department of Sociology with a Focus on Innovation and Digitalization , Institute of Sociology, , Linz , Austria"},{"name":"Johannes Kepler University Linz , Institute of Sociology, , Linz , Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Leinert","sequence":"additional","affiliation":[{"name":"Institute of Geriatric Research, Ulm University Medical Center , Ulm , Germany"},{"name":"Agaplesion Bethesda Clinic Ulm , Ulm , Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marina","family":"Fotteler","sequence":"additional","affiliation":[{"name":"Agaplesion Bethesda Clinic Ulm , Ulm , Germany"},{"name":"DigiHealth Institute, Neu-Ulm University of Applied Sciences , Neu-Ulm , 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