COVID-19 has demonstrated the devastating consequences of the rapid spread of an airborne virus in residential aged care. We report the use of CO2-based ventilation assessment to empirically identify potential 'super-spreader' zones within an aged care facility, and determine the efficacy of rapidly implemented, inexpensive, risk reduction measures.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1093/ageing/afac316 | DOI Listing |
CHEST Crit Care
December 2024
Division of Pulmonary, Allergy, and Critical Care (G. L. A.), University of Pennsylvania Perelman School of Medicine, Philadelphia, PA; the Division of Pulmonary and Critical Care Medicine (S. M. S.), University of Rochester Medical Center, Rochester, NY; the Department of Anaesthesia and Critical Care (A. R., Z. F., and M. T. D. S.), Greys Hospital, KwaZulu-Natal Department of Health, the Department of Anaesthesia and Critical Care (J. I.), Harry Gwala Regional Hospital, KwaZulu-Natal Department of Health, Pietermaritzburg, the Department of Anaesthesia and Critical Care (R. D. W. and M. T. D. S.), School of Clinical Medicine, University of KwaZulu-Natal, Durban, South Africa; the Faculty Medicine and Pharmacy (R. D. W.), Vrije Universiteit Brussel (VUB), Brussels, Belgium; and the Department of Intensive Care (R. D. W.), John Radcliffe Hospital, Oxford University Trust Hospitals, Oxford, England.
Background: A proposed new global definition of ARDS seeks to update the Berlin definition and account for nonintubated ARDS and ARDS diagnoses in resource-variable settings.
Research Question: How do ARDS epidemiologic characteristics change with operationalizing the new global definition of ARDS in a resource-limited setting?
Study Design And Methods: We performed a real-use retrospective cohort study among adult patients meeting criteria for the Berlin definition of ARDS or the global definition of ARDS at ICU admission in two public hospitals in the KwaZulu-Natal Department of Health, South Africa, from January 2017 through June 2022.
Results: Among 5,760 adults (aged ≥ 18 years) admitted to the ICU, 2,027 patients (35.
Background Fragility fractures, often caused by osteoporosis, are a major public health concern among the growing population of the United Kingdom (UK). In addition to being a major source of illness and mortality, the rising incidence of osteoporosis places a heavy strain on healthcare systems if it is not adequately managed. In order to lower the risk of additional fractures, current guidelines place a strong emphasis on the timely evaluation and treatment of fragility fractures.
View Article and Find Full Text PDFFront Neurol
December 2024
Servicio de Neurología, Fundación Valle del Lili, Cali, Colombia.
Objective: This study aims to describe clinical variables and quality care indicators in pediatric stroke management at a high-complexity pediatric care center in Latin America.
Methods: Retrospective study of patients with stroke, aged 2-18 years from 2011 to 2021. The principal outcomes were the mRs and mortality.
Digit Health
December 2024
Department of Biological and Environmental Sciences and Technologies (DiSTeBA), Università del Salento, Lecce, Italy.
Objective: Osteoarthritis (OA), particularly knee OA, is a leading cause of disability and poses significant challenges in healthcare management. Mobile applications (apps) have emerged as potential tools to support therapeutic exercise by providing tailored programs, instructional content, and progress tracking. This systematic review evaluates the efficacy of mobile apps in enhancing therapeutic exercise for knee OA management.
View Article and Find Full Text PDFDigit Health
December 2024
School of Public Administration, Central South University, Changsha, Hunan, China.
Objective: To evaluate the service quality of integrated health and social care institutions for older adults in residential settings in China, addressing a critical gap in the theoretical and empirical understanding of service quality assurance in this rapidly expanding sector.
Methods: This study employs three machine learning algorithms-Backpropagation Neural Networks (BPNN), Feedforward Neural Networks (FNN), and Support Vector Machines (SVM)-to train and validate an evaluative item system. Comparative indices such as Mean Squared Error, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and predictive performance metrics were employed to assess the models.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!