Unlabelled: Monitoring and analysis of anesthesia depth status data refers to evaluating the anesthesia depth status of patients during the surgical process by monitoring their physiological index data, and conducting analysis and judgment. The depth of anesthesia is crucial for the safety and success of the surgical process. By monitoring the state of anesthesia depth, abnormal conditions of patients can be detected in a timely manner and corresponding measures can be taken to prevent accidents from occurring. Traditional anesthesia monitoring methods currently include computer tomography, electrocardiogram, respiratory monitoring, etc. In this regard, traditional physiological indicator monitoring methods have certain limitations and cannot directly reflect the patient's neural activity status. The monitoring and analysis methods based on neuroscience can obtain more information from the level of brain neural activity.
Purpose: In this article, the monitoring and analysis of anesthesia depth status data would be studied through neuroscience.
Methods: Through a controlled experiment, the monitoring accuracy of traditional anesthesia status monitoring algorithm and neuroscience-based anesthesia status monitoring algorithm was studied, and the information entropy and oxygen saturation of electroencephalogram signals in patients with different anesthesia depth were explored.
Results: The experiment proved that the average monitoring accuracy of the traditional anesthesia state monitoring algorithm in patients' blood drug concentration and oxygen saturation reached 95.55 and 95.00%, respectively. In contrast, the anesthesia state monitoring algorithm based on neuroscience performs better, with the average monitoring accuracy of drug concentration and oxygen saturation reaching 98.00 and 97.09%, respectively. This experimental result fully proved that the monitoring performance of anesthesia state monitoring algorithms based on neuroscience is better.
Conclusion: The experiment proved the powerful monitoring ability of the anesthesia state monitoring algorithm based on neuroscience used in this article, and explained the changing trend of brain nerve signals and oxygen saturation of patients with different anesthesia depth states, which provided a new research method for the monitoring and analysis technology of anesthesia depth state data.
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http://dx.doi.org/10.1515/biol-2022-0719 | 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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