Objectives: This study aims to determine the availability of geriatrics-friendly protocols, pieces of equipment, and physical environments alongside potential opportunities of improvement in the emergency departments of our country.
Methods: This prospective, cross-sectional study was conducted between the 1 and 29 of February, in the year 2024, within the AI, AII, B group- and university hospitals in Turkey. A questionnaire form consisting of three subdivisions in which general pieces of information, information regarding appropriate personnel/management for geriatrics-friendly emergency departments, equipment/materials, and the presence of physical environments was presented online to the participants and the responses that were provided online were evaluated.
Results: The study was conducted with a total of 175 participants from hospital emergency departments. The number of hospitals with monthly older patient application amounts of 500 and above was 133 (76.0%). It was observed that personnel/management knowledge was, relative to guideline suggestions, at low levels. When the appropriateness of personnel/management knowledge and total equipment/materials were compared to hospital roles, it was determined that university hospitals adhered closest to the guideline and that inter-group differences were significant (p < 0.001).
Conclusions: It was determined that the compliance of emergency departments in Turkey with the criteria specified in the geriatric emergency department guidelines is at very low levels.
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http://dx.doi.org/10.1007/s41999-024-01022-w | DOI Listing |
Nurs Leadersh (Tor Ont)
June 2025
Director and Professor, School of Nursing Assistant Dean, Research, Faculty of Health Dalhousie University Affiliate Scientist, Nova Scotia Health Affiliate Scientist, Maritime SPOR Support Unit Halifax, NS Co-Director, Canadian Centre for Advanced Practice Nursing Research Hamilton, ON.
and along with it, the first issue of the () for the year 2025. We begin the year with significant and persistent health and healthcare challenges. Recently released data from the Canadian Institute for Health Information indicate that 5.
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Background: The optimal application of medical nutrition therapy (MNT) in treating gestational diabetes remains uncertain. MNT involves individualised nutrition assessment and counselling, which is labour-intensive and is not the sole type of intervention offered by clinical dietitians.
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J Clin Med
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Critical Care and Perioperative Population Health Research (CAPER) Program, Department of Anesthesiology, Duke University, Durham, NC 27708, USA.
Traumatic brain injury (TBI) is a complex condition and a leading cause of injury-related disability and death, with significant impacts on patient outcomes. Extracranial organ involvement plays a critical role in the outcome of patients following TBI. This review aims to provide a comprehensive overview of the pathophysiology, clinical presentation, and challenges in diagnosing patients with autonomic dysfunction after TBI.
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Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA.
Layperson cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) use are vital for improving survival rates after out-of-hospital cardiac arrest (OHCA), yet their application varies by community demographics. We evaluated the concerns and factors influencing willingness to perform CPR and use AEDs among laypersons in high-risk, low-resource communities. From April 2022 to March 2024, laypersons in Northern Manhattan's Community District 12 completed surveys assessing their attitudes toward CPR and AED use before attending Hands-Only CPR training.
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Innovation, Research and Teaching Service (SABES-ASDAA), Teaching Hospital of the Paracelsus Medical Private University (PMU), 39100 Bolzano, Italy.
: This study investigates the potential of artificial intelligence (AI), specifically large language models (LLMs) like ChatGPT, to enhance decision support in diagnosing epilepsy. AI tools can improve diagnostic accuracy, efficiency, and decision-making speed. The aim of this study was to compare the level of agreement in epilepsy diagnosis between human experts (epileptologists) and AI (ChatGPT), using the 2014 International League Against Epilepsy (ILAE) criteria, and to identify potential predictors of diagnostic errors made by ChatGPT.
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