Background: Generative artificial intelligence (AI) and large language models, such as OpenAI's ChatGPT, have shown promising potential in supporting medical education and clinical decision-making, given their vast knowledge base and natural language processing capabilities. As a general purpose AI system, ChatGPT can complete a wide range of tasks, including differential diagnosis without additional training. However, the specific application of ChatGPT in learning and applying a series of specialized, context-specific tasks mimicking the workflow of a human assessor, such as administering a standardized assessment questionnaire, followed by inputting assessment results in a standardized form, and interpretating assessment results strictly following credible, published scoring criteria, have not been thoroughly studied.
View Article and Find Full Text PDFAims: To synthesise the evidence on and to compare the diagnostic accuracy of the Nu-DESC and CAM in detecting postoperative delirium among hospitalised patients.
Design: Systematic review and diagnostic meta-analysis.
Data Sources: The PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations and Theses A&I, and PsycINFO databases were systematically searched from their inception to February 10, 2023.
Background: Whether cognitive and functional recovery in skilled nursing facilities (SNF) following hospitalization differs by delirium and Alzheimer's disease related dementias (ADRD) has not been examined.
Objective: To compare change in cognition and function among short-stay SNF patients with delirium, ADRD, or both.
Design: Retrospective cohort study using claims data from 2011 to 2013.
Background: There has been a marked rise in the use of observation care for Medicare beneficiaries visiting the emergency department (ED) in recent years. Whether trends in observation use differ for people with Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) is unknown.
Methods: Using a national 20% sample of Medicare beneficiaries ages 68+ from 2012 to 2018, we compared trends in ED visits and observation stays by AD/ADRD status for beneficiaries visiting the ED.
Background: Recently, the Ultra-Brief Confusion Assessment Method (UB-CAM), designed to help physicians and nurses to recognize delirium, showed high, but imperfect, accuracy compared with Research Reference Standard Delirium Assessments (RRSDAs). The aim of this study is to identify factors associated with disagreement between clinicians' app-based UB-CAM assessments and RRSDAs.
Methods: This is a secondary analysis of a prospective diagnostic test study.
Delirium is a significant geriatric condition associated with adverse clinical and economic outcomes. The cause of delirium is usually multifactorial, and person-centered multicomponent approaches for proper delirium management are required. In 2017, the John A.
View Article and Find Full Text PDF