Objective: Brain computed tomography (CT) is commonly performed to diagnose acute altered mental status (AMS), a critically important symptom in many serious diseases. However, negative CT results are common, which result in unnecessary CT use. Therefore, this study aimed to determine the clinical factors associated with positive CT findings.
Methods: Patients with acute AMS selected from an emergency department-based registry were retrospectively evaluated. Patients with non-traumatic and noncommunicable diseases on initial presentation and with Glasgow Comal Scale scores of <15 were included in the study.
Results: Among the 367 brain CT results of patients with AMS during the study period, 146 (39.8%) were positive. In a multivariate analysis, the presence of focal neurologic deficit (odds ratio [OR], 132.6; 95% confidence interval [CI], 37.8 to 464.6), C-reactive protein level <2 mg/dL (OR, 3.9; 95% CI, 1.4 to 10.6), and Glasgow Comal Scale score <9 (OR, 2.4; 95% CI, 1.2 to 4.8) were significantly associated with positive brain CT results.
Conclusion: The presence of focal neurologic deficit, initial Glasgow Comal Scale score of <9, and initial C-reactive protein levels of <2 mg/dL can facilitate the selection of brain CT to diagnose patients with acute AMS in the emergency department.
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http://dx.doi.org/10.15441/ceem.16.163 | DOI Listing |
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.
Pulm Circ
January 2025
Department of Imaging and Pathology, Biomedical MRI KU Leuven Leuven Belgium.
The pulmonary vasculature plays a pivotal role in the development and progress of chronic lung diseases. Due to limitations of conventional two-dimensional histological methods, the complexity and the detailed anatomy of the lung blood circulation might be overlooked. In this study, we demonstrate the practical use of optical serial block face imaging (SBFI), ex vivo microcomputed tomography (micro-CT), and nondestructive optical tomography for visualization and quantification of the pulmonary circulation's 3D architecture from macro- to micro-structural levels in murine lung samples.
View Article and Find Full Text PDFBrain Commun
January 2025
Department of Clinical Psychology and Psychobiology, Universidade de Santiago de Compostela (USC), Santiago de Compostela 15782, Spain.
Previous research has revealed patterns of brain atrophy in subjective cognitive decline, a potential preclinical stage of Alzheimer's disease. However, the involvement of myelin content and microstructural alterations in subjective cognitive decline has not previously been investigated. This study included three groups of participants recruited from the Compostela Aging Study project: 53 cognitively unimpaired adults, 16 individuals with subjective cognitive decline and hippocampal atrophy and 70 with subjective cognitive decline and no hippocampal atrophy.
View Article and Find Full Text PDFR Soc Open Sci
January 2025
University Hospitals Birmingham NHS Foundation Trust, Edgbaston, Birmingham B15 2GW, UK.
Multiple sclerosis (MS) is an autoimmune disease of the brain and spinal cord with both inflammatory and neurodegenerative features. Although advances in imaging techniques, particularly magnetic resonance imaging (MRI), have improved the process of diagnosis, its cause is unknown, a cure remains elusive and the evidence base to guide treatment is lacking. Computational techniques like machine learning (ML) have started to be used to understand MS.
View Article and Find Full Text PDFFront Psychol
January 2025
The MARCS Institute for Brain, Behaviour, and Development, Western Sydney University, Penrith, NSW, Australia.
Recent advancement in Artificial Intelligence (AI) has rendered image-synthesis models capable of producing complex artworks that appear nearly indistinguishable from human-made works. Here we present a quantitative assessment of human perception and preference for art generated by OpenAI's DALL·E 2, a leading AI tool for art creation. Participants were presented with pairs of artworks, one human-made and one AI-generated, in either a preference-choice task or an origin-discrimination task.
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