Purpose Of Review: There have been significant advancements in depth of anesthesia (DoA) technology. The Anesthesia Patient Safety Foundation recently published recommendations to use a DoA monitor in specific patient populations receiving general anesthesia. However, the universal use of DoA monitoring is not yet accepted. This review explores the current state of DoA monitors and their potential impact on patient safety.
Recent Findings: We reviewed the current evidence for using a DoA monitor and its potential role in preventing awareness and preserving brain health by decreasing the incidence of postoperative delirium and postoperative cognitive dysfunction or decline (POCD). We also explored the evidence for use of DoA monitors in improving postoperative clinical indicators such as organ dysfunction, mortality and length of stay. We discuss the use of DoA monitoring in the pediatric population, as well as highlight the current limitations of DoA monitoring and the path forward.
Summary: There is evidence that DoA monitoring may decrease the incidence of awareness, postoperative delirium, POCD and improve several postoperative outcomes. In children, DoA monitoring may decrease the incidence of awareness and emergence delirium, but long-term effects are unknown. While there are key limitations to DoA monitoring technology, we argue that DoA monitoring shows great promise in improving patient safety in most, if not all anesthetic populations.
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http://dx.doi.org/10.1097/ACO.0000000000001430 | DOI Listing |
Objective: This study investigated the effect of reliability on the function allocation (FA) boundary by examining the interaction effect of degree of automation (DOA) and reliability on routine performance, failure performance, and attention allocation.
Background: According to the lumberjack effect, an increase in DOA will typically improve routine performance, while failure performance may remain undeteriorated until a specific, high DOA threshold is reached. This threshold can be regarded as the FA boundary.
J Forensic Sci
December 2024
Department of Medical and Surgical Sciences, Unit of Legal Medicine, University of Bologna, Bologna, Italy.
People diagnosed with substance use disorder (SUD) might represent a high-risk subpopulation for New Psychoactive Drugs (NPS) consumption, and hair analysis offers a unique perspective to assess drug prevalence in this population. The present study aims to assess the prevalence of NPS and their co-consumption with traditional drugs of abuse (DoA) in individuals diagnosed with SUD. Hair samples from patients under care at the addiction treatment service of Bologna, Italy, for a diagnosed SUD, were collected during 2023 and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS/MS), using a previously validated method.
View Article and Find Full Text PDFBrain Inform
November 2024
School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, Australia.
Accurate monitoring of the depth of anesthesia (DoA) is essential for ensuring patient safety and effective anesthesia management. Existing methods, such as the Bispectral Index (BIS), are limited in real-time accuracy and robustness. Current methods have problems in generalizability across diverse patient datasets and are sensitive to artifacts, making it difficult to provide reliable DoA assessments in real time.
View Article and Find Full Text PDFJ Acoust Soc Am
October 2024
Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York 14624, USA.
The vibrational response of an elastic panel to incident acoustic waves is determined by the direction-of-arrival (DOA) of the waves relative to the spatial structure of the panel's bending modes. By monitoring the relative modal excitations of a panel immersed in a sound field, the DOA of the source may be inferred. In reverberant environments, early acoustic reflections and the late diffuse acoustic field may obscure the DOA of incoming sound waves.
View Article and Find Full Text PDFAnimals (Basel)
August 2024
Animal and Veterinary Science Center (CECAV), University of Trás-os-Montes e Alto Douro (UTAD), Quinta de Prados, 5000-801 Vila Real, Portugal.
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