Over 80% of Canadian COVID-19 first wave deaths occurred in long-term care homes. Focussing on Ontario, I trace the antecedents of the COVID-19 crisis in long-term care and document experiences of frontline staff and family members of residents during the pandemic. Following Povinelli, I argue that the marginalization of both residents and workers in Ontario's long-term care system over two decades has eroded possibilities for recognition of their personhood. I also question broader societal attitudes toward aging, disability and death that make possible the abandonment of the frail elderly.
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http://dx.doi.org/10.1080/01459740.2021.1927023 | DOI Listing |
Aims: Risk prediction indices used in worsening heart failure (HF) vary in complexity, performance, and the type of datasets in which they were validated. We compared the performance of seven risk prediction indices in a contemporary cohort of patients hospitalized for HF.
Methods And Results: We assessed the performance of the Length of stay and number of Emergency department visits in the prior 6 months (LE), Length of stay, number of Emergency department visits in the prior 6 months, and admission N-Terminal prohormone of brain natriuretic peptide (NT-proBNP (LENT), Length of stay, Acuity, Charlson co-morbidity index, and number of Emergency department visits in the prior 6 months (LACE), Get With The Guidelines Heart Failure (GWTG), Readmission Risk Score (RRS), Enhanced Feedback for Effective Cardiac Treatment model (EFFECT), and Acute Decompensated Heart Failure National Registry (ADHERE) risk indices among consecutive patients hospitalized for HF and discharged alive from January 2017 to December 2019 in a network of hospitals in England.
Front Endocrinol (Lausanne)
January 2025
Department of Medical Intensive Care Unit, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.
Background: Frailty is an increasingly important determinant in the field of health, and its identification has important clinical significance in the field of critical care medicine. However, there are still a large number of challenges in quick and accurate identification of frailty. This study aims to evaluate the value of the neutrophil/high-density lipoprotein cholesterol ratio (NHR) in frailty and its long-term survival.
View Article and Find Full Text PDFInfect Drug Resist
January 2025
Department of Medical Biochemistry, Faculty of Medicine, Bandırma Onyedi Eylül University, Bandırma/Balıkesir, Turkey.
Introduction: Nanobubble ozone stored in hyaluronic acid-decorated liposomes (patent application PCT/TR2022/050177) was used, and the Minimum Inhibitory Concentration (MIC) was found to be 1562 ppm. (patient isolate), (patient isolate), (MRSA) (ATCC12493), and (ATCC25922) bacteria, which are hospital-acquired and healthcare-associated infections, were used. A time-dependent efficacy study was conducted at 1600 ppm.
View Article and Find Full Text PDFFront Neurol
January 2025
Department of Neurology & Stroke, University Hospital Tübingen, Tübingen, Germany.
Background: Disorders of consciousness (DoC) in non-traumatic ICU-patients are often treated with amantadine, although evidence supporting its efficacy is limited.
Methods: This retrospective study analyzed non-traumatic DoC-patients treated with amantadine between January 2016 and June 2021. Data on patient demographics, clinical characteristics, treatment specifications, and outcomes were extracted from electronic medical records.
Front Med (Lausanne)
January 2025
Department of Stomatology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Sepsis remains a leading cause of morbidity and mortality worldwide due to its rapid progression and heterogeneous nature. This review explores the potential of Artificial Intelligence (AI) to transform sepsis management, from early detection to personalized treatment and real-time monitoring. AI, particularly through machine learning (ML) techniques such as random forest models and deep learning algorithms, has shown promise in analyzing electronic health record (EHR) data to identify patterns that enable early sepsis detection.
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