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Aim: Advanced Practice Nurses are expected to provide lifesaving care to patients with complex acute illnesses in emergency and critical care settings. However, little is known about their competencies and barriers to practice in emergency and critical care settings. This review investigated these nurses' competencies to practice.
Methods: A scoping review was conducted in accordance with Arksey and O'Malley's framework. Extensive research searches were conducted using seven electronic databases: MEDLINE, CINAHL, Scopus, Web of Science, Ichushi Web, Mednar and GreyNet International. Definitions and explanations of Advanced Practice Nurse competencies were categorized into elements and grouped according to similarity.
Results: The database searches identified 2,483 studies, and data were extracted for 23 studies. Analysed studies were published between 2000 and 2021 and conducted in eight countries. Seven competencies were identified: performing advanced practice nursing, acute patient care, diagnostic assessment, interdisciplinary collaboration and consultation, leadership and system management, documenting patient care and supporting patient and family decision-making.
Conclusion: This review identified competencies unique to Advanced Practice Nurses in emergency and critical care settings. Further research is required to facilitate understanding of the crucial roles of advanced care nurses among healthcare providers.
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http://dx.doi.org/10.1111/ijn.13205 | DOI Listing |
Interv Neuroradiol
September 2025
Department of Neurosurgery, Shinshu University School of Medicine, Matsumoto, Japan.
BackgroundA stable guiding system is essential for successful carotid artery stenting (CAS), particularly when navigating tortuous aortic or supra-aortic anatomy. However, data on the mechanical behavior of stent delivery systems remain scarce.ObjectiveTo assess and compare the bending stiffness and trackability of five commercially available carotid stent delivery systems using bench-top experiments.
View Article and Find Full Text PDFFEMS Microbiol Rev
September 2025
CIISA - Centre for Interdisciplinary Research in Animal Health, Faculty of Veterinary Medicine, University of Lisbon, Lisbon, Portugal.
African Swine Fever (ASF), caused by the highly contagious African swine fever virus (ASFV), poses a significant threat to domestic and wild pigs worldwide. Despite its limited host range and lack of zoonotic potential, ASF has severe socio-economic and environmental consequences. Current control strategies primarily rely on early detection and culling of infected animals, but these measures are insufficient given the rapid spread of the disease.
View Article and Find Full Text PDFMacromol Rapid Commun
September 2025
Key Laboratory of Bio-based Material Science and Technology of Ministry of Education, Northeast Forestry University, Harbin, P. R. China.
Rapid advancement of flexible electronics has generated a demand for sustainable materials. Cellulose, a renewable biopolymer, exhibits exceptional mechanical strength, customizable properties, biodegradability, and biocompatibility. These attributes are largely due to its hierarchical nanostructures and modifiable surface chemistry.
View Article and Find Full Text PDFJ Empir Res Hum Res Ethics
September 2025
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Biobanking in China has seen rapid development, placing the country as a key player globally. However, significant ethical challenges arise, particularly around donor autonomy in informed consent for collecting and using biological materials and personal data. This study examines how Chinese biobanks inform donors about their participation and the ethical content of consent documents.
View Article and Find Full Text PDFMed Biol Eng Comput
September 2025
Department of Computer Science, Università degli Studi di Bari Aldo Moro, Bari, Italy.
Fetal standard plane detection is essential in prenatal care, enabling accurate assessment of fetal development and early identification of potential anomalies. Despite significant advancements in machine learning (ML) in this domain, its integration into clinical workflows remains limited-primarily due to the lack of standardized, end-to-end operational frameworks. To address this gap, we introduce FetalMLOps, the first comprehensive MLOps framework specifically designed for fetal ultrasound imaging.
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