{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T07:57:49Z","timestamp":1788422269499,"version":"build-2803163510"},"reference-count":85,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T00:00:00Z","timestamp":1601942400000},"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":["Health Services Research"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>To derive and validate a comorbidity\u2010based delirium risk index (DRI) to predict postoperative delirium.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Source\/Study Setting<\/jats:title><jats:p>Data of 506\u00a0438 hip fracture repair surgeries from 2006 to 2016 were collected to derive DRI and perform internal validation from the Premier Healthcare Database, which provided billing information on 20\u201025 percent of hospitalizations in the USA. Additionally, data of 1\u00a0130\u00a0569 knee arthroplasty surgeries were retrieved for external validation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Design<\/jats:title><jats:p>Thirty\u2010six commonly seen comorbidities were evaluated by logistic regression with the outcome of postoperative delirium. The hip fracture repair surgery cohort was separated into a training dataset (60 percent) and an internal validation (40 percent) dataset. The least absolute shrinkage and selection operator (LASSO) procedure was applied for variable selection, and weights were assigned to selected comorbidities to quantify corresponding risks. The newly developed DRI was then compared to the Charlson\u2010Deyo Index for goodness\u2010of\u2010fit and predictive ability, using the Akaike information criterion (AIC), Bayesian information criterion (BIC), area under the ROC curve (AUC) for goodness\u2010of\u2010fit, and odds ratios for predictive performance. Additional internal validation was performed by splitting the data by four regions and in 4 randomly selected hospitals. External validation was conducted in patients with knee arthroplasty surgeries.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Collection<\/jats:title><jats:p>Hip fracture repair surgeries, knee arthroplasty surgeries, and comorbidities were identified by using ICD\u20109 codes. Postoperative delirium was defined by using ICD\u20109 codes and analyzing billing information for antipsychotics (specifically haloperidol, olanzapine, and quetiapine) typically recommended to treat delirium.<\/jats:p><\/jats:sec><jats:sec><jats:title>Principal Findings<\/jats:title><jats:p>The derived DRI includes 14 comorbidities and assigns comorbidities weights ranging from 1 to 6. The DRI outperformed the Charlson\u2010Deyo Comorbidity Index with better goodness\u2010of\u2010fit and predictive performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Delirium risk index is a valid comorbidity index for covariate adjustment and risk prediction in the context of postoperative delirium. Future work is needed to test its performance in different patient populations and varying definitions of delirium.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1475-6773.13565","type":"journal-article","created":{"date-parts":[[2020,10,6]],"date-time":"2020-10-06T07:48:57Z","timestamp":1601970537000},"page":"154-165","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Derivation and validation of a novel comorbidity\u2010based delirium risk index to predict postoperative delirium using national administrative healthcare database"],"prefix":"10.1111","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2796-3483","authenticated-orcid":false,"given":"Xiaobo","family":"Zhong","sequence":"first","affiliation":[{"name":"Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai New York USA"},{"name":"Tisch Cancer Institute Icahn School of Medicine at Mount Sinai New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jung\u2010Yi","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lihua","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Population Health Science and Policy Icahn School of Medicine at Mount Sinai New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A. 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