Development and validation of an international preoperative risk assessment model for postoperative delirium.
Background Postoperative delirium (POD) is a frequent complication in older adults, characterised by disturbances in attention, awareness and cognition, and associated with prolonged hospitalisation, poor functional recovery, cognitive decline, long-term dementia and increased mortality. Early ident...
| Published in: | Age & Ageing Vol. 52; no. 6; pp. 1 - 11 |
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| Main Authors: | , , , , , , , |
| Format: | Article |
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Oxford University Press / USA
Jun2023
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=164654199&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 164654199 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00020729 AGA jtl: Age & Ageing issn: 00020729 maglogo: N pubinfo: dt: Jun2023 vid: 52 iid: 6 pid: 622 pub: Oxford University Press / USA artinfo: ui: 164654199 10.1093/ageing/afad086 ppf: 1 ppct: 10 formats: tig: atl: Development and validation of an international preoperative risk assessment model for postoperative delirium. aug: au: Dodsworth, Benjamin T Reeve, Kelly Falco, Lisa Hueting, Tom Sadeghirad, Behnam Mbuagbaw, Lawrence Goettel, Nicolai Gelsomino, Nayeli Schmutz affil: PIPRA AG , Zurich 8005 , Switzerland Institute of Data Analysis and Process Design, Zurich University of Applied Sciences , Winterthur 8400 , Switzerland Zühlke Engineering AG , Zürcherstrasse 39J, Schlieren 8952 , Switzerland Evidencio , Irenesingel 19, Haaksbergen 7481 GJ , Netherlands Department of Health Research Methods, Evidence, and Impact, McMaster University , Hamilton ON L8S 4L8 , Canada Department of Anesthesia, McMaster University , Hamilton ON L8S 4L8 , Canada Department of Pediatrics, McMaster University , Hamilton, ON L8S 4L8 , Canada Biostatistics Unit, Father Sean O'Sullivan Research Centre, St Joseph's Healthcare , Hamilton, ON L8S 4L8 , Canada Centre for Development of Best Practices in Health (CDBPH), Yaoundé Central Hospital , Yaoundé 12117 , Cameroon Division of Epidemiology and Biostatistics, Department of Global Health, Stellenbosch University , Cape Town 7600 , South Africa Department of Anesthesiology, University of Florida College of Medicine , Gainesville FL 32610 , USA Department of Clinical Research, University of Basel , Basel 4031 , Switzerland Department of Anaesthesia, University Hospital Basel , Spitalstrasse 21, Basel 4031 , Switzerland su: Switzerland Germany Patient care Old age Research evaluation Confidence intervals Operative surgery Preoperative period Research methodology Surgical complications Risk assessment Comparative studies Delirium Theory Descriptive statistics Research funding Prediction models Logistic regression analysis Algorithms sug: subj: Patient care Old age Switzerland Germany Research evaluation Confidence intervals Operative surgery Preoperative period Research methodology Surgical complications Risk assessment Comparative studies Delirium Theory Descriptive statistics Research funding Prediction models Logistic regression analysis Algorithms keyword: algorithm clinical practice older people postoperative delirium risk prediction algorithm clinical practice older people postoperative delirium risk prediction ab: Background Postoperative delirium (POD) is a frequent complication in older adults, characterised by disturbances in attention, awareness and cognition, and associated with prolonged hospitalisation, poor functional recovery, cognitive decline, long-term dementia and increased mortality. Early identification of patients at risk of POD can considerably aid prevention. Methods We have developed a preoperative POD risk prediction algorithm using data from eight studies identified during a systematic review and providing individual-level data. Ten-fold cross-validation was used for predictor selection and internal validation of the final penalised logistic regression model. The external validation used data from university hospitals in Switzerland and Germany. Results Development included 2,250 surgical (excluding cardiac and intracranial) patients 60 years of age or older, 444 of whom developed POD. The final model included age, body mass index, American Society of Anaesthesiologists (ASA) score, history of delirium, cognitive impairment, medications, optional C-reactive protein (CRP), surgical risk and whether the operation is a laparotomy/thoracotomy. At internal validation, the algorithm had an AUC of 0.80 (95% CI: 0.77–0.82) with CRP and 0.79 (95% CI: 0.77–0.82) without CRP. The external validation consisted of 359 patients, 87 of whom developed POD. The external validation yielded an AUC of 0.74 (95% CI: 0.68–0.80). Conclusions The algorithm is named PIPRA (Pre-Interventional Preventive Risk Assessment), has European conformity (ce) certification, is available at http://pipra.ch/ and is accepted for clinical use. It can be used to optimise patient care and prioritise interventions for vulnerable patients and presents an effective way to implement POD prevention strategies in clinical practice. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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