Background: Delirium is frequent though undetected in older patients admitted to the Emergency Department (ED).
Aims: To develop and validate a delirium risk assessment tool for older persons admitted to the ED Observation Unit (OU).
Methods: We used data from two samples of 65 + year-old patients, one admitted to the ED of Brescia Hospital (n = 257) and one to the ED of Desio Hospital (n = 107), Italy. Data from Brescia were used as training sample, those collected in Desio as testing one. Delirium was assessed using the 4AT and patients' characteristic were retrieved from medical charts. Variables found to be associated with delirium in the training sample were tested for the creation of a delirium risk assessment tool. The resulting tool's performances were assessed in the testing subsample.
Results: Of all possible scores tested, the combination with the highest discriminative ability in the training sample included: age ≥ 75 years, dementia diagnosis, chronic use of neuroleptics, and hearing impairment. The delirium score exhibited an AUC of 0.874 and 0.893 in the training and testing samples, respectively. For a 1-point increase in the score, the odds of delirium increased more than twice in both samples.
Discussion: We propose a delirium risk assessing tool that includes variables that can be easily collected at ED admission and that can be calculated rapidly.
Conclusion: A risk assessment tool could help improving delirium detection in older persons referring to ED.
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http://dx.doi.org/10.1007/s40520-021-01792-4 | DOI Listing |
Neurosurg Rev
January 2025
Department of Neurological Surgery, Oregon Health & Science University, Portland, OR, USA.
Deep brain stimulation (DBS) is a valuable treatment for Parkinson's disease (PD), but postoperative delirium (POD) is a common complication. Understanding the risk factors for POD is crucial for optimizing patient selection and developing preventative measures. This systematic review and meta-analysis aims to identify predictors of POD in PD patients undergoing DBS surgery.
View Article and Find Full Text PDFAust Crit Care
January 2025
Critical Care Research Group, Prince Charles Hospital, Brisbane, Queensland, Australia; School of Dentistry, University of Queensland, Brisbane, Queensland, Australia.
Background: Many intensive care unit (ICU) survivors experience new or worsening impairments, termed post-intensive care syndrome. Substantial investment has been made in identifying patients at risk and developing interventions, but evidence remains equivocal. A more nuanced understanding of risk and outcomes is therefore warranted.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Anesthesiology, Daping Hospital, Army Medical University, Chongqing, China.
Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Orthopedics and Trauma Surgery, University Hospital Düsseldorf, Düsseldorf, Germany.
Background: An aging population in combination with more gentle and less stressful surgical procedures leads to an increased number of operations on older patients. This collectively raises novel challenges due to higher age heavily impacting treatment. A major problem, emerging in up to 50% of cases, is perioperative delirium.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Division of Geriatrics, School of Medicine, University of California San Francisco.
Importance: The Walter Index is a widely used prognostic tool for assessing 12-month mortality risk among hospitalized older adults. Developed in the US in 2001, its accuracy in contemporary non-US contexts is unclear.
Objective: To evaluate the external validity of the Walter Index in predicting posthospitalization mortality risk in Brazilian older adult inpatients.
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