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Healthcare Professionals' Perspectives on Sepsis Care Pathways-Qualitative Pilot Expert Interviews.
J Clin Med
January 2025
Institute of Infectious Diseases and Infection Control, Jena University Hospital, Friedrich-Schiller-University Jena, 07747 Jena, Germany.
: Despite recent decades' rapid advances in the management of patients with sepsis and septic shock, global sepsis mortality and post-acute sepsis morbidity rates remain high. Our aim was, therefore, to provide a first overview of sepsis care pathways as well as barriers and supportive conditions for optimal pre-clinical, clinical, and post-acute sepsis care in Germany. : Between May and September 2023, we conducted semi-structured, video-based, one-to-one pilot expert interviews with healthcare professionals representing pre-hospital, clinical, and post-acute care settings.
View Article and Find Full Text PDFAnalysis of Body Composition and Levels of Antimicrobial Peptides in Patients with Basal Cell Carcinoma: A Preliminary Study.
J Clin Med
January 2025
Department of Anatomy, Jagiellonian University Medical College, 33-332 Cracow, Poland.
: Excessive body fatness is the basis of many diseases, especially civilization-related ones. The aim of this study is to analyze the body composition and serum levels of selected antimicrobial peptides (AMPs) in patients with basal cell carcinoma (BCC), in comparison to healthy controls (HCs), and investigate whether any specific parameter significantly increases the risk of BCC development. : The body composition and measurements of serum levels of cathelicidin and human-beta-defensin-2 were analyzed in a group of 100 subjects (50 patients with BCC and 50 HCs).
View Article and Find Full Text PDFCapacity Planning (Capital, Staff and Costs) of Inpatient Maternity Services: Pitfalls for the Unwary.
Int J Environ Res Public Health
January 2025
Healthcare Analysis and Forecasting, Wantage OX12 0NE, UK.
This study investigates the process of planning for future inpatient resources (beds, staff and costs) for maternity (pregnancy and childbirth) services. The process of planning is approached from a patient-centered philosophy; hence, how do we discharge a suitably rested healthy mother who is fully capable of caring for the newborn baby back into the community? This demonstrates some of the difficulties in predicting future births and investigates trends in the average length of stay. While it is relatively easy to document longer-term (past) trends in births and the conditions relating to pregnancy and birth, it is exceedingly difficult to predict the future nature of such trends.
View Article and Find Full Text PDFDigital Mindfulness Training for Burnout Reduction in Physicians: Clinician-Driven Approach.
JMIR Form Res
January 2025
Brown University, Department of Behavioral and Social Sciences, Providence, RI, United States.
Background: Physician burnout is widespread in health care systems, with harmful consequences on physicians, patients, and health care organizations. Mindfulness training (MT) has proven effective in reducing burnout; however, its time-consuming requirements often pose challenges for physicians who are already struggling with their busy schedules.
Objective: This study aimed to design a short and pragmatic digital MT program with input from clinicians specifically to address burnout and to test its efficacy in physicians.
Spectral Analysis of Light-Adapted Electroretinograms in Neurodevelopmental Disorders: Classification with Machine Learning.
Bioengineering (Basel)
December 2024
Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA.
Electroretinograms (ERGs) show differences between typically developing populations and those with a diagnosis of autism spectrum disorder (ASD) or attention deficit/hyperactivity disorder (ADHD). In a series of ERGs collected in ASD ( = 77), ADHD ( = 43), ASD + ADHD ( = 21), and control ( = 137) groups, this analysis explores the use of machine learning and feature selection techniques to improve the classification between these clinically defined groups. Standard time domain and signal analysis features were evaluated in different machine learning models.
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