Metaphors are a personal expression and form of self-awareness, providing a way of describing an experience with dissimilar concepts to convey meaning. Metaphors create new meaning and provide a deeper insight into the human spirit. They are grounded in reality and day-to-day life experiences. Reflective practitioners incorporate and integrate their vast knowledge base of experience, skills, and attitudes to assist in formulating their practice as a metaphor. It is through this experience and reflection that nurses can creatively express their images of self and nursing.
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Comparisons of integrated slice-specific dynamic shimming EPI and single-shot EPI diffusion-weighted imaging of the liver.
Eur J Radiol
January 2025
Department of Radiology, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, Hunan, 410011, China; Department of Radiology Quality Control Center, Changsha, Hunan Province, 410011, China; The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Institute of Health and Rehabilitation Science, Xi'an Jiaotong University, Xi'an 710049,China. Electronic address:
Purpose: To compare the quality of DWI images, signal loss of left hepatic lobe and diagnostic performance of apparent diffusion coefficient (ADC) values between SS-EPI and iShim-EPI in liver lesions.
Methods: Totally 142 patients were involved, images using SS-EPI and the prototype iShim-EPI were acquired before injection of gadoxetic acid-enhanced liver MRI.Image quality of demarcation of liver capsule, resolution, lesion distortion, artifacts, lesion confidence score, and signal loss in left hepatic lobe was assessed by two radiologists.
Feasibility and effects of cognitive training on cognition and psychosocial function in Huntington's disease: a randomised pilot trial.
J Neurol
January 2025
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, 18 Innovation Walk, Clayton, Victoria, 3800, Australia.
Background: Huntington's disease (HD) is a rare neurodegenerative disease that causes progressive cognitive, physical, and psychiatric symptoms. Computerised cognitive training (CCT) is a novel intervention that aims to improve and maintain cognitive functions through repeated practice. The effects of CCT have yet to be established in HD.
View Article and Find Full Text PDFThe Brussels consensus for non-invasive ICP monitoring when invasive systems are not available in the care of TBI patients (the B-ICONIC consensus, recommendations, and management algorithm).
Intensive Care Med
January 2025
Global Health Research Group in Acquired Brain and Spine Injuries, Cambridge, UK.
Background: Invasive systems are commonly used for monitoring intracranial pressure (ICP) in traumatic brain injury (TBI) and are considered the gold standard. The availability of invasive ICP monitoring is heterogeneous, and in low- and middle-income settings, these systems are not routinely employed due to high cost or limited accessibility. The aim of this consensus was to develop recommendations to guide monitoring and ICP-driven therapies in TBI using non-invasive ICP (nICP) systems.
View Article and Find Full Text PDFCardiac myosin binding protein C correlate with cardiac troponin I during an exercise training program in patients with HFrEF.
ESC Heart Fail
January 2025
Department of Cardiology, Stavanger University Hospital, Stavanger, Norway.
Background: Cardiac myosin binding protein C (cMyC) is an emerging new biomarker of myocardial injury rising earlier and cleared faster than cardiac troponins. It has discriminatory power similar to high-sensitive troponins in diagnosing myocardial infarction in patients presenting with chest pain. It is also associated with outcome in patients with acute heart failure.
View Article and Find Full Text PDFA 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
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