ArticleHealth services research2021
Derivation and validation of a novel comorbidity-based delirium risk index to predict postoperative delirium using national administrative healthcare database.
Article in Health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Association of Plasma BDNF Concentration and Val66Met Polymorphism with Postoperative Delirium After Cardiac Surgery Under General Anesthesia with Cardiopulmonary Bypass.Journal of clinical medicine · 2025Article
- Predicting ICU Delirium in Critically Ill COVID-19 Patients Using Demographic, Clinical, and Laboratory Admission Data: A Machine Learning Approach.Life (Basel, Switzerland) · 2025Article
- Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.PloS one · 2024Article
- Article
- Impact of Alcohol Misuse on Requirements for Critical Care Services and Development of Hospital Delirium in Patients With COVID-19 pneumonia.Critical care explorations · 2023Article
- Developing an Institute for Health Care Delivery Science: successes, challenges, and solutions in the first five years.Health care management science · 2021Article
- Derivation and validation of a novel comorbidity-based delirium risk index to predict postoperative delirium using national administrative healthcare database.Health services research · 2021Article
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Authors and funding
6 authors.
Funding
Abstract
objectiveTo derive and validate a comorbidity-based delirium risk index (DRI) to predict postoperative delirium. DATA SOURCE/STUDY
settingData of 506 438 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 20-25 percent of hospitalizations in the USA. Additionally, data of 1 130 569 knee arthroplasty surgeries were retrieved for external validation. STUDY
designThirty-six 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-Deyo Index for goodness-of-fit and predictive ability, using the Akaike information criterion (AIC), Bayesian information criterion (BIC), area under the ROC curve (AUC) for goodness-of-fit, 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. DATA COLLECTION: Hip fracture repair surgeries, knee arthroplasty surgeries, and comorbidities were identified by using ICD-9 codes. Postoperative delirium was defined by using ICD-9 codes and analyzing billing information for antipsychotics (specifically haloperidol, olanzapine, and quetiapine) typically recommended to treat delirium. PRINCIPAL
findingsThe derived DRI includes 14 comorbidities and assigns comorbidities weights ranging from 1 to 6. The DRI outperformed the Charlson-Deyo Comorbidity Index with better goodness-of-fit and predictive performance.
conclusionsDelirium 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.
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