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- Janis Fliegenschmidt, Nikolai Hulde, Maria G Preising, Silvia Ruggeri, Ralph Szymanowski, Laurent Meesseman, Hong Sun, and von DossowVeraVInstitute of Anesthesiology and Pain Therapy, Heart and Diabetes Center Bad Oeynhausen, NRW, Ruhr-University Bochum, Georgstraße 11, 32545, NRW, Germany. Electronic address: vvdossow@hdz-nrw.de..
- Institute of Anesthesiology and Pain Therapy, Heart and Diabetes Center Bad Oeynhausen, NRW, Ruhr-University Bochum, Georgstraße 11, 32545, NRW, Germany. Electronic address: janis.fliegenschmidt@ruhr-uni-bochum.de.
- J Clin Anesth. 2021 Dec 1; 75: 110473.
AbstractDelirium is a highly relevant complication of surgical interventions. Current research indicates that despite increased awareness for delirium, it is often overlooked. We implemented an AI-based tool to monitor delirium in cardiac surgery patients in our specialist clinic. This appears to be a promising approach to improve detection of delirium, especially for underrecognized forms and in peripheral wards without intensive screening. We present a case in which the AI identified delirium, confirmed by our routine screening and specialist evaluation.Copyright © 2021. Published by Elsevier Inc.
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