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| http://dx.doi.org/10.1016/j.jadohealth.2021.09.008 | DOI Listing |
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Outcomes for people experiencing homelessness with COVID-19 presenting to emergency departments in Canada, compared with housed patients.
CMAJ
March 2025
Department of Emergency Medicine, Faculty of Medicine (Li, Hohl) and School of Population and Public Health (Li, McGrail, Law), University of British Columbia, Vancouver, BC; Departments of Pediatrics, Faculty of Medicine & Dentistry (Rosychuk) and of Mathematical and Statistical Sciences, Faculty of Science (Rosychuk), University of Alberta, Edmonton, Alta.
Background: Whether people experiencing homelessness (PEH) have different COVID-19 outcomes than housed patients in Canada remains unclear. We sought to ascertain whether rates of in-hospital mortality, hospital admission, critical care admission, and mechanical ventilation differed between PEH and housed people with symptomatic SARS-CoV-2 infection.
Methods: We conducted a propensity score-matched cohort study to compare the outcomes of PEH and housed patients presenting to emergency departments for acute symptomatic COVID-19.
VITALdb: to select the best viroinformatics tools for a desired virus or application.
Brief Bioinform
March 2025
Computational Biology and Translational Bioinformatics (CBTB) Laboratory, Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India.
The recent pandemics of viral diseases, COVID-19/mpox (humans) and lumpy skin disease (cattle), have kept us glued to viral research. These pandemics along with the recent human metapneumovirus outbreak have exposed the urgency for early diagnosis of viral infections, vaccine development, and discovery of novel antiviral drugs and therapeutics. To support this, there is an armamentarium of virus-specific computational tools that are currently available.
View Article and Find Full Text PDFRisk stratification for future cardiac arrest after COVID-19 vaccination.
World J Cardiol
February 2025
Department of Epidemiology, McCullough Foundation, Dallas, TX 75206, United States.
Unheralded cardiac arrest among previously healthy young people without antecedent illness, months or years after coronavirus disease 2019 (COVID-19) vaccination, highlights the urgent need for risk stratification. The most likely underlying pathophysiology is subclinical myopericarditis and reentrant ventricular tachycardia or spontaneous ventricular fibrillation that is commonly precipitated after a surge in catecholamines during exercise or the waking hours of terminal sleep. Small patches of inflammation and/or edema can be missed on cardiac imaging and autopsy, and the heart can appear grossly normal.
View Article and Find Full Text PDFPM concentration prediction using machine learning algorithms: an approach to virtual monitoring stations.
Sci Rep
March 2025
Department of Environmental Health Engineering, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
One of the most important pollutants is PM, which is particularly important to monitor pollutant levels to keep the pollutant concentration under control. In this research, an attempt has been made to predict the concentrations of PM using four Machine Learning (ML) models. The ML methods include Light Gradient Boosting Machine (LGBM), Extreme Gradient Boosting Regressor (XGBR), Random Forest (RF) and Gradient Boosting Regressor (GBR).
View Article and Find Full Text PDFPublishing Identifiable Patient Photographs in the Digital Age: Focus Group Study of Patients, Doctors, and Medical Students.
J Med Internet Res
March 2025
Department of Research in Biomedicine and Health, Center for Evidence-Based Medicine, University of Split School of Medicine, Split, Croatia.
Background: The publication of patient photographs in scientific journals continues to pose challenges regarding privacy and confidentiality, despite existing ethical guidelines. Recent studies indicate that key stakeholders-including health care professionals and patients-lack sufficient awareness of the ethical considerations surrounding patient photographs, particularly in the context of digital scientific publishing.
Objective: This qualitative study aims to explore how different stakeholders-patients, medical students, and doctors-understand the challenges of patient privacy and confidentiality in scientific publications.
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