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This review systematically summarizes the current status of cognitive frailty in maintenance hemodialysis patients, including its prevalence, assessment and diagnostic criteria, associated risk factors, and the clinical application status and progress of related risk prediction models both domestically and internationally. The analysis aims to provide methodological references for future development and implementation of cognitive frailty risk prediction models tailored to this specific patient population.
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http://dx.doi.org/10.1111/1744-9987.70081 | DOI Listing |
Am J Emerg Med
September 2025
University of Toronto, Rotman School of Management, Canada.
Study Objective: Accurately predicting which Emergency Department (ED) patients are at high risk of leaving without being seen (LWBS) could enable targeted interventions aimed at reducing LWBS rates. Machine Learning (ML) models that dynamically update these risk predictions as patients experience more time waiting were developed and validated, in order to improve the prediction accuracy and correctly identify more patients who LWBS.
Methods: The study was deemed quality improvement by the institutional review board, and collected all patient visits to the ED of a large academic medical campus over 24 months.
JMIR Res Protoc
September 2025
Department of Medical Oncology, Early Phase Unit, Georges-François Leclerc Centre, Dijon, France.
Background: Sarcomas are rare cancer with a heterogeneous group of tumors. They affect both genders across all age groups and present significant heterogeneity, with more than 70 histological subtypes. Despite tailored treatments, the high metastatic potential of sarcomas remains a major factor in poor patient survival, as metastasis is often the leading cause of death.
View Article and Find Full Text PDFJMIR Res Protoc
September 2025
University of Nevada, Las Vegas, Las Vegas, NV, United States.
Background: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effectiveness of current prediction methods remains inconclusive. Limited research exists on patients' prearrest pathophysiological status and predictive and prognostic factors of IHCA, highlighting the need for a comprehensive synthesis of predictive methodologies.
View Article and Find Full Text PDFNeurol Neuroimmunol Neuroinflamm
November 2025
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Background And Objectives: Myelitis is a relatively common clinical entity for neurologists, with diverse underlying causes. The aim of this study was to describe the incidence of myelitis, its causes, clinical presentation, and factors predicting functional outcomes and relapses.
Methods: Using the Swedish National Patient Registry, we identified all adult patients in Stockholm County between 2008 and 2018 using International Classification of Diseases, 10th Edition (ICD-10) codes likely to include myelitis.
Crit Care Explor
September 2025
Department of Biostatistics, University of Florida Colleges of Medicine and Public Health and Health Professions, Gainesville, FL.
Objectives Background: Monocyte anisocytosis (monocyte distribution width [MDW]) has been previously validated to predict sepsis and outcome in patients presenting in the emergency department and mixed-population ICUs. Determining sepsis in a critically ill surgical/trauma population is often difficult due to concomitant inflammation and stress. We examined whether MDW could identify sepsis among patients admitted to a surgical/trauma ICU and predict clinical outcome.
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