Unintended Return of Consciousness in a Patient during Surgery and General Anesthesia

Incidence, Associated Factors, and Behavioral Consequences of Intraoperative Awareness and Dreams During General Anesthesia Among Adult Patients: A Prospective Cohort Study

Background  The intraoperative awareness with recall phenomenon involves the memory of intraoperative events. The reported incidence is 0.001%. Awareness is rare intraoperatively but has profound implications. This research aimed to study intraoperative awareness and dream experiences in the Omani population undergoing general anesthesia. Methods This prospective cohort study involving 300 adult patients was conducted at a tertiary-level hospital between July and December 2021. Awareness was assessed in the post-anesthesia care unit and then at home on the seventh day and one month telephonically using a modified Brice questionnaire. The study's primary outcome was the incidence of IOA and dreams in adult Omani patients undergoing GA. The secondary outcome was identifying the factors associated with intraoperative awareness and dreams under GA. Results In this study, the incidence of awareness was 0.3% while 7.6% of patients reported intraoperative dreams. The patient who experienced IOA underwent an endoscopic retrograde cholangiopancreatography under GA with neuromuscular blockade and had a prolonged recovery. A total of 49.33% developed psychological effects postoperatively; anxiety, irritability, fear of surgery, change in memory, and repetitive nightmares were the most common ones. Because of the limited sample size, no factor associated significantly with these outcomes was found. Conclusion This study observed a higher incidence of intraoperative awareness and dreams. Awareness might be due to prolonged recovery and the use of neuromuscular blocking agents, but a focused study is required to confirm this finding. The incidence of intraoperative dreams and postoperative psychological effects of GA was also high. It may be worth exploring these findings with larger population-based research.

Automatic anesthesia depth staging using entropy measures and relative power of electroencephalogram frequency bands

Many of the surgeries performed under general anesthesia are aided by electroencephalogram (EEG) monitoring. With increased focus on detecting the anesthesia states of patients in the course of surgery, more attention has been paid to analyzing the power spectra and entropy measures of EEG signal during anesthesia. In this paper, by using the relative power of EEG frequency bands and the EEG entropy measures, a new method for detecting the depth of anesthesia states has been presented based on the least squares support vector machine (LS-SVM) classifiers. EEG signals were recorded from 20 patients before, during and after general anesthesia in the operating room at a sampling rate of 200 Hz. Then, 12 features were extracted from each EEG segment, 10 s in length, which are used for anesthesia state monitoring. No significant difference was observed (p > 0.05) between these features and the bispectral index (BIS), which is the commonly used measure of anesthetic effect. The used LS-SVM classifier based method is able to identify the anesthesia states with an accuracy of 80% with reference to the BIS index. Since the underlying equation of the utilized LS-SVM is linear, the computational time of the algorithm is not significant and therefore it can be used for online application in operation rooms.