Consciousness fluctuation during general anesthesia: a theoretical approach to anesthesia awareness and memory modulation

A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis

Investigating neural mechanisms of anesthesia process and developing efficient anesthetized state detection methods are especially on high demand for clinical consciousness monitoring. Traditional anesthesia monitoring methods are not involved with the topological changes between electrodes covering the prefrontal-parietal cortices, by investigating electrocorticography (ECoG). To fill this gap, a framework based on the two-stream graph convolutional network (GCN) was proposed, i.e., one stream for extracting topological structure features, and the other one for extracting node features. The two-stream graph convolutional network includes GCN Model 1 and GCN Model 2. For GCN Model 1, brain connectivity networks were constructed by using phase lag index (PLI), representing different structure features. A common adjacency matrix was founded through the dual-graph method, the structure features were expressed on nodes. Therefore, the traditional spectral graph convolutional network can be directly applied on the graphs with changing topological structures. On the other hand, the average of the absolute signal amplitudes was calculated as node features, then a fully connected matrix was constructed as the adjacency matrix of these node features, as the input of GCN Model 2. This method learns features of both topological structure and nodes of the graph, and uses a dual-graph approach to enhance the focus on topological structure features. Based on the ECoG signals of monkeys, results show that this method which can distinguish awake state, moderate sedation and deep sedation achieved an accuracy of 92.75% in group-level experiments and mean accuracy of 93.50% in subject-level experiments. Our work verifies the excellence of the graph convolutional network in anesthesia monitoring, the high recognition accuracy also shows that the brain network may carry neurological markers associated with anesthesia.

Awareness during emergence from anesthesia: Features and future research directions

The anesthesia awareness with recall (AAWR) phenomenon represents a complication of general anesthesia consisting of memorization of intraoperative events reported by the patient immediately after the end of surgery or at a variable distance from it. Approximately 20% of AAWR cases occur during emergence from anesthesia. Clinically, these unexpected experiences are often associated with distress especially due to a sense of paralysis. Indeed, although AAWR at the emergence has multiple causes, in the majority of cases the complication develops when the anesthesia plan is too early lightened at the end of anesthesia and there is a lack of use, or misuse, of neuromuscular monitoring with improper management of the neuromuscular block. Because the distress caused by the sense of paralysis represents an important predictor for the development of severe psychological complications, the knowledge of the phenomenon, and the possible strategies for its prophylaxis are aspects of considerable importance. Nevertheless, a limited percentage of episodes of AAWR cannot be prevented. This paradox holds also during the emergence phase of anesthesia which represents a very complex neurophysiological process with many aspects yet to be clarified.

Electrodermal Activity Monitoring During Painful Stimulation in Sedated Adult Intensive Care Unit Patients: a Pilot Study

Introduction-Aim: Newer methods, such as infrared digital pupillometry and electrodermal activity (EDA) measurement have been suggested as good alternatives for analgesia monitoring in critically ill patients. This study analyzed EDA changes due to pain stimulus in sedated adult critical care patients Methods: Skin conductance variability, selected hemodynamic and respiratory parameters, Bispectral index (BIS) and ambient noise level, were monitored during 4 hour routine daytime in an adult ICU. 4h-Measurements were divided into 2 groups, based upon the sedation level of the patients: Group A - Ramsay Sedation Score 2-4 and Group B - Ramsay Sedation Score of 5-6. Selected recordings before and after pain stimulus were performed. The stimulus chosen was the pressure applied to nail bed for 10 sec, which was performed routinely during neurological examination. Patients' demographics, laboratory exams and severity scores were recorded. Pain status evaluation before every event was also performed by 2 independent observers via Critical Care Pain Observation Tool (CPOT) and Adult Non Verbal Pain Score (ANVPS) Results: In both groups the rate of EDA changes was greater than other monitoring parameters: more in Group A than in Group B. Yet, the difference between groups was not statistically significant.

CONCLUSION

EDA measurements are greater to pain stimuli, than cardiovascular, respiratory or even BIS monitoring. These encouraging results suggest that, further studies are needed to better define EDA role in ICU.