Background: The need for a concept for the nationwide strategic transfer of critical care patients in Germany was highlighted during the COVID-19 (coronavirus disease 2019) pandemic. Despite the cloverleaf concept developed specifically for this purpose, the transfer of large numbers of critical care patients represents a major challenge. With the help of a computer simulation, the SCATTER research project uses a fictitious example to test, develop, and recommend transfer strategies.
Method: The simulation was programmed after collecting procedural and structural data on critical care transports within Germany. The simulation allows altering various parameters and testing different transfer scenarios. In a fictitious scenario, nationwide transfers starting from Schleswig-Holstein were simulated and evaluated using predetermined criteria.
Results: In the case of ground-based transfers, it became apparent that, depending on the selected target region, not all patients could be transferred due to the limited range of ground-based vehicles. Although a higher number of patients can be transferred by air, this is associated with additional gurney changes and potential risk to the patient. A distance-dependent transport strategy led to the identical results as purely air-bound transport, since air-bound transport was always chosen due to the long distances.
Discussion: The simulation can be used to develop recommendations and to draw important conclusions from different transfer strategies.
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http://dx.doi.org/10.1007/s00103-023-03811-3 | DOI Listing |
Am J Emerg Med
January 2025
Faculty of Medicine, Universidad de Valladolid, Valladolid, Spain; Emergency Department, Hospital Clínico Universitario, Gerencia Regional de Salud de Castilla y León, Valladolid, Spain.
Background: The study of the inclusion of new variables in already existing early warning scores is a growing field. The aim of this work was to determine how capnometry measurements, in the form of end-tidal CO2 (ETCO2) and the perfusion index (PI), could improve the National Early Warning Score (NEWS2).
Methods: A secondary, prospective, multicenter, cohort study was undertaken in adult patients with unselected acute diseases who needed continuous monitoring in the emergency department (ED), involving two tertiary hospitals in Spain from October 1, 2022, to June 30, 2023.
J Nurs Adm
December 2024
Author Affiliations: Research Associate (Dr Keys), The Center for Health Design, Concord, California; National Senior Director (Dr Fineout-Overholt), Evidence-Based Practice and Implementation Science, at Ascension in St. Louis, MO.
Objective: Relationships among coworker and patient visibility, reactions to physical work environment, and work stress in ICU nurses are explored.
Background: Millions of dollars are invested annually in the building or remodeling of ICUs, yet there is a gap in understanding relationships between the physical layout of nursing units and work stress.
Methods: Using a cross-sectional, correlational, exploratory, predictive design, relationships among variables were studied in a diverse sample of ICU nurses.
J Neurosurg Anesthesiol
November 2024
Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA.
This systematic review aimed to identify and describe best practice for the intraoperative anesthetic management of patients undergoing emergent/urgent decompressive craniotomy or craniectomy for any indication. The PubMed, Scopus, EMBASE, and Cochrane databases were searched for articles related to urgent/emergent craniotomy/craniectomy for intracranial hypertension or brain herniation. Only articles focusing on intraoperative anesthetic management were included; those investigating surgical or intensive care unit management were excluded.
View Article and Find Full Text PDFObjective: The aim of this study is to test the feasibility of a custom 3D-printed guide for performing a minimally invasive cochleostomy for cochlear implantation.
Study Design: Prospective performance study.
Setting: Secondary care.
PLoS One
January 2025
Department of Biomedical and Health Informatics, Tsui Laboratory, Children's Hospital of Philadelphia, Philadelphia, PA, United States of America.
Semantical text understanding holds significant importance in natural language processing (NLP). Numerous datasets, such as Quora Question Pairs (QQP), have been devised for this purpose. In our previous study, we developed a Siamese Convolutional Neural Network (S-CNN) that achieved an F1 score of 82.
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