One of the current challenges in medicine is monitoring the patients' depth of general anaesthesia (DGA). Accurate assessment of the depth of anaesthesia contributes to tailoring drug administration to the individual patient, thus preventing awareness or excessive anaesthetic depth and improving patients' outcomes. In the past decade, there has been a significant increase in the number of studies on the development, comparison and validation of commercial devices that estimate the DGA by analyzing electrical activity of the brain (i.e., evoked potentials or brain waves). In this paper we review the most frequently used sensors and mathematical methods for monitoring the DGA, their validation in clinical practice and discuss the central question of whether these approaches can, compared to other conventional methods, reduce the risk of patient awareness during surgical procedures.
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http://dx.doi.org/10.3390/s101210896 | DOI Listing |
Paediatr Anaesth
January 2025
Department of Anesthesia, Erasmus University Medical Centre, Rotterdam, the Netherlands.
Background: In children, monitoring depth of anesthesia is challenging because of the still developing brain. Electroencephalographic density spectral array monitoring provides age- and anesthetic drug-specific electroencephalographic patterns, making it suitable for use in children. Yet, not much is known about the benefits of using density spectral array on post-operative recovery in children.
View Article and Find Full Text PDFCureus
December 2024
Anesthesiology, Jikei University School of Medicine, Tokyo, JPN.
Background Femoral neuropathy is a significant postoperative complication in gynecological surgery that can severely impact patient mobility and quality of life. Among various mechanisms of nerve injury, retractor-induced compression against the pelvic sidewall has been identified as a particularly crucial causative factor. Despite this well-recognized mechanism and its clinical importance, few studies have investigated specific preventive strategies for this iatrogenic complication.
View Article and Find Full Text PDFJ Psychiatr Res
January 2025
Department of Medicine, Universitat Internacional de Catalunya, Barcelona. c/ Dr. Josep Trueta s/n, Sant Cugat del Vallès, 08195, Barcelona, Spain. Electronic address:
Background: Determining anesthetic depth has been used to assess the optimal timing of electrical stimulus application in electroconvulsive therapy (ECT). This has improved the quality and effectiveness of seizures, as some anesthetics used can decrease efficacy. This study evaluated the influence of the Patient State Index (PSi) on the course of ECT in patients with major depressive disorder (MDD).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
The formula-based estimation of the right internal jugular venous (IJV) catheterization depth can be inaccurate when using ultrasound guidance. External landmark-based and radiological landmark-based methods have been proposed as alternatives to estimate the insertion depth. This study aimed to evaluate these methods using transesophageal echocardiography (TEE)-guided insertion depth as the reference.
View Article and Find Full Text PDFAnesthesiology
January 2025
Department of Anesthesiology, Brigham and Women's Hospital and Harvard Medical School, Boston MA, USA.
Introduction: Accurate prognostication in comatose survivors of cardiac arrest is a challenging and high-stakes endeavor. We sought to determine whether internal EEG subparameters extracted by the Bispectral Index (BIS) monitor, a device commonly used to estimate depth-of-anesthesia intraoperatively, could be repurposed to predict recovery of consciousness after cardiac arrest.
Methods: In this retrospective cohort study, we trained a 3-layer neural network to predict recovery of consciousness to the point of command following versus not based on 48 hours of continuous EEG recordings in 315 comatose patients admitted to a single US academic medical center after cardiac arrest (Derivation cohort: N=181; Validation cohort: N=134).
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