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Evaluation of disparities in hospitalisation outcomes for deaf and hard of hearing patients with COVID-19: a multistate analysis of statewide inpatient databases from Florida, Maryland, New York and Washington.
BMJ Open
January 2025
The Lundquist Institute for Biomedical Innovation, Torrance, California, USA.
Objective: Investigate whether deaf or hard of hearing (D/HH) patients with COVID-19 exhibited different hospitalisation outcomes compared with hearing patients with COVID-19.
Design: Cohort study SETTING: Statewide Inpatient Databases for Florida, Maryland, New York and Washington, for the year 2020.
Participants: Records of patients aged 18-64 years with COVID-19 PRIMARY OUTCOMES AND MEASURES: Differences in in-hospital death, 90-day readmission, length of stay, hospitalisation cost, hospitalisation cost per day, intensive care unit (ICU) or coronary care unit (CCU) utilisation and ventilation use were evaluated.
Association of the blood urea nitrogen to serum albumin ratio and all-cause mortality in critical ill acute ischemic stroke patients: a retrospective cohort study of MIMIC-IV database 3.0.
Front Nutr
January 2025
Department of Immunology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China (UESTC), Mianyang, Sichuan, China.
Purpose: We aim to ascertain the extent to which the blood urea nitrogen (BUN) to serum albumin (ALB) ratio (BAR) could be implemented to anticipate the short- and long-term prognosis of acute ischemic stroke (AIS) patients in intensive care units (ICUs).
Methods: The data was derived from the Marketplace for Intensive Care Medical Information-IV (MIMIC-IV v3.0) database, primarily pertaining to AIS patients as categorized by the International Classification of Diseases (ICD)-9 and ICD-10.
Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring.
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.
View Article and Find Full Text PDFIntensive care unit nurses' redeployment experiences during the COVID-19 pandemic: A qualitative study.
Aust Crit Care
January 2025
Centre for Quality and Patient Safety Research - Eastern Health Partnership, Box Hill, Victoria 3128, Australia; School of Nursing and Midwifery and Centre for Quality and Patient Safety in the Institute for Health Transformation, Deakin University, Geelong, Victoria 3125, Australia.
Background: The pandemic response required the large-scale redeployment of nurses to support the care of patients with COVID-19. Surveys of staff and analysis of staff feedback indicated that the frequent redeployment of intensive care unit (ICU) registered nurses (RNs) led to dissatisfaction and contributed to voluntary reductions in hours and increased intentions to resign. Whilst much is understood about the redeployment of non-ICU RNs into ICUs to support patient care during periods of high demand, less is known about ICU RNs' experiences of being redeployed to general wards.
View Article and Find Full Text PDFspp. in neonatal sepsis: an urgent global threat.
Front Antibiot
September 2024
Institute of Infection & Immunity, St George's, University of London, London, United Kingdom.
Neonatal sepsis causes substantial morbidity and mortality, the burden of which is carried by low-income countries (LICs). The emergence of multidrug-resistant pathogens in vulnerable neonatal populations poses an urgent threat to infant survival. spp.
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