The application of technological advances and clear articulation of how they improve patient outcomes are not always well described in the literature. Our research team investigated the numerous ways to measure conditions and behaviors that precede patient events and could signal an important change in health through a scoping review. We searched for evidence of technology use in fall prediction in the population of older adults in any setting. The research question was described in the population-concept-context format: "What types of sensors are being used in the prediction of falls in older persons?" The purpose was to examine the numerous ways to obtain continuous measurement of conditions and behaviors that precede falls. This area of interest may be termed emerging knowledge . Implications for research include increased attention to human-centered design, need for robust research trials that clearly articulate study design and outcomes, larger sample sizes and randomization of subjects, consistent oversight of institutional review board processes, and elucidation of the human costs and benefits to health and science.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1097/CIN.0000000000001052 | DOI Listing |
ASN Neuro
January 2025
Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, USA.
In light of the increasing importance for measuring myelin ratios - the ratio of axon-to-fiber (axon + myelin) diameters in myelin internodes - to understand normal physiology, disease states, repair mechanisms and myelin plasticity, there is urgent need to minimize processing and statistical artifacts in current methodologies. Many contemporary studies fall prey to a variety of artifacts, reducing study outcome robustness and slowing development of novel therapeutics. Underlying causes stem from a lack of understanding of the myelin ratio, which has persisted more than a century.
View Article and Find Full Text PDFBrain Sci
January 2025
Translational Neuroscience Program, Wayne State University, Detroit, MI 48201, USA.
Introduction: The cerebellum is a common lesion site in persons with multiple sclerosis (PwMS). Physiologic and anatomic studies have identified a topographic organization of the cerebellum including functionally distinct motor and cognitive areas. In this study, a recent parcellation algorithm was applied to a sample of PwMS and healthy controls to examine the relationships among specific cerebellar regions, fall status, and common clinical measures of motor and cognitive functions.
View Article and Find Full Text PDFCurr Opin Microbiol
January 2025
Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Electronic address:
Designing microbiomes for applications in health, bioengineering, and sustainability is intrinsically linked to a fundamental theoretical understanding of the rules governing microbial community assembly. Microbial ecologists have used a range of mathematical models to understand, predict, and control microbiomes, ranging from mechanistic models, putting microbial populations and their interactions as the focus, to purely statistical approaches, searching for patterns in empirical and experimental data. We review the success and limitations of these modeling approaches when designing novel microbiomes, especially when guided by (inevitably) incomplete experimental data.
View Article and Find Full Text PDFCalcif Tissue Int
January 2025
Department of Bioengineering, Temple University, 1947 N. 12th St, Philadelphia, PA, 19122, USA.
Bone mechanical function is determined by multiple factors, some of which are still being elucidated. Here, we present a multivariate analysis of the role of bone tissue composition in the proximal femur stiffness of cadaver bones (n = 12, age 44-93). Stiffness was assessed by testing under loading conditions simulating a sideways fall onto the hip.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Department of Law, Institute of Legal Medicine, University of Macerata, Macerata, Italy.
Introduction: Adverse events in hospitals significantly compromise patient safety and trust in healthcare systems, with medical errors being a leading cause of death globally. Despite efforts to reduce these errors, reporting remains low, and effective system changes are rare. This systematic review explores the potential of artificial intelligence (AI) in clinical risk management.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!