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- Do we have today a reliable method to detect the moment of loss of consciousness during induction of general anaesthesia?Publication . Ferreira, Ana Isabel Leitão; Nunes, Catarina S.; Mendes, Joaquim; Amorim, PedroThis review aims to give an overview of the current state of monitoring depth of anaesthesia and detecting the moment of loss of consciousness, from the first clinical signs involved in anaesthesia to the latest technologies used in this area. Such techniques are extremely important for the development of automatic systems for anaesthesia control, including preventing intraoperative awareness episodes and overdoses. A search in the databases Pubmed and IEEE Xplore was performed using terms such anaesthetic monitoring, depth of anaesthesia, loss of consciousness, as well as anaesthesia indexes, namely BIS. Despite the several methods capable of monitoring the hypnotic state of anaesthesia, there is still no methodology to accurate detect the moment of loss of consciousness during induction of general anaesthesia.
- Electromyographic assessment of blink reflex throughout the transition from responsiveness to unresponsiveness during induction with propofol and remifentanilPublication . Ferreira, Ana Isabel Leitão; Vide, Sérgio; Felgueiras, João; Cardoso, Márcio; Nunes, Catarina S.; Mendes, Joaquim; Amorim, PedroGeneral anesthesia is a reversible drug-induced state of altered arousal characterized by loss of responsiveness due to brainstem inactivation. Precise identification of the moment in which responsiveness is lost during the induction of general anesthesia is extremely important to provide information regarding an individual's anesthetic requirements and help intraoperative drug titration. To characterize the transition from responsiveness to unresponsiveness more objectively, we studied neurophysiologic-derived parameters of electromyographic records of electrically evoked blink reflex as a means of identifying the precise moment of loss of responsiveness. Twenty-five patients received a slow infusion of propofol until loss of corneal reflex while successive blink reflexes were elicited and recorded every 6 s. The level of anesthesia was assessed using an adapted version of the Richmond Agitation-Sedation Scale. Different variables of the blink reflex components were calculated and compared to the adapted version of the Richmond Agitation-Sedation score and the estimated effect-site propofol concentration. Baselines of the blink reflex responses were similar to those in literature. After propofol infusion started, the most susceptible component of the blink reflex to propofol was R2 (EC50 = 1.358 (95% CI 1.321, 1.396) µg/mL) and the most resistant was R1 (EC50 = 3.025 (95% CI 2.960, 3.090) µg/mL). Most of the patients (24 out of 25) lost the R1 component when they were still responsive to shaking and shouting and corneal reflex could be elicited clinically (time = 102.48 ± 33.00 s). Habituation was present in R2 but not in R1. The R1 component of the blink reflex was found to have a strong correlation with the adapted version of the Richmond Agitation-Sedation Scale, with amplitude correlating better than areas (ρ = - 0.721 (0.123) versus ρ = - 0.688 (0.165)). We found a strong correlation between the R1 component with the estimated propofol effect-site concentration, with amplitude correlating better than areas (ρ = - 0.838 (0.113) versus ρ = - 0.823 (0.153)) and between the clinical scale and the propofol concentration (ρ = 0.856 (0.060)). The area and amplitude of the R1 component showed to be indicators of predicting different levels of anesthesia (Pk = 0.672 (0.183) versus Pk = 0.709 (0.134)) and these are connected to the propofol concentrations (Pk = 0.593 (0.10)). Our results suggest that electrically evoked blink reflex could be used during the induction of anesthesia as a surrogate of the Richmond Agitation-Sedation Scale to provide an objective endpoint as far as a - 4. At this point, at the moment of loss of R1, the propofol infusion may be stopped, as overshooting increases slightly the effect-site concentration afterward and eventually reaching loss of responsiveness. If the desired target is not achieved, the infusion can then be resumed.
- EEG signatures at the transition between conscious and unconscious state during induction of general anesthesia with remifentanil and propofolPublication . Ferreira, Ana Isabel Leitão; Mendes, Joaquim; Amorim, Pedro; Nunes, Catarina S.The precise identification of the moment of Loss Of Consciousness (LOC) during the induction phase of general anesthesia is of extreme importance for the individualization of drug doses. In the lack of an objective method to assess this moment, the development of a new methodology is needed. In this observational study, Electroencephalogram (EEG) signatures that were associated with the moment of LOC are examined as a starting point, so as to create a robust model for tracking the dynamic changes between conscious and unconscious states. The data from 12 patients under general anesthesia for neurosurgical procedures with remifentanil and propofol, are used is this study. Multitaper spectrograms were computed to observe the dynamics of EEG oscillations before and after LOC. At LOC, a decrease in gamma power and an increase in delta and alpha bands were identified.
- Usefulness of the blink reflex to assess the effect of propofol during induction of anesthesia in surgical patientsPublication . Ferreira, Ana Isabel Leitão; Nunes, Catarina S.; Mendes, Joaquim; Amorim, PedroThe aim of this study was to investigate the relation between the blink reflex evoked by an electrical stimulus and the depth of anesthesia induced with intravenous anesthetic drug propofol. The blink reflex was stimulated before the propofol infusion started (baseline) and after, every 6 s. The electromyographic responses and the level of sedation/anesthesia scores as well as the estimated effect-site concentration of propofol were recorded in 11 patients. The blink reflex responses were abolished when patients were still conscious. The clinical scale of anesthesia increased with increasing concentrations of propofol. To predict the level of sedation/anesthesia a multinomial logistic regression was performed using blink reflex extracted features at the frequency domain. Several features proved to be good predictor estimates and the model showed to be useful. This information could be helpful to assess the moment of loss of consciousness and thus personalize anesthesia.
- Implementation of neural networks to frontal electroencephalography for the identification of the transition responsiveness/unresponsiveness during induction of general anesthesiaPublication . Ferreira, Ana Isabel Leitão; Vide, Sérgio; Nunes, Catarina S.; Neto, Joaquim; Amorim, Pedro; Mendes, JoaquimObjective: General anesthesia is a reversible drug-induced state of altered arousal characterized by loss of responsiveness (LOR) due to brainstem inactivation. Precise identification of the LOR during the induction of general anesthesia is extremely important to provide personalized information on anesthetic requirements and could help maintain an adequate level of anesthesia throughout surgery, ensuring safe and effective care and balancing the avoidance of intraoperative awareness and overdose. So, main objective of this paper was to investigate whether a Convolutional Neural Network (CNN) applied to bilateral frontal electroencephalography (EEG) dataset recorded from patients during opioid-propofol anesthetic procedures identified the exact moment of LOR. Material and methods: A clinical protocol was designed to allow for the characterization of different clinical endpoints throughout the transition to unresponsiveness. Fifty (50) patients were enrolled in the study and data from all was included in the final dataset analysis. While under a constant estimated effect-site concentration of 2.5 ng/mL of remifentanil, an 1% propofol infusion was started at 3.3 mL//h until LOR. The level of responsiveness was assessed by an anesthesiologist every six seconds using a modified version of the Richmond Agitation-Sedation Scale (aRASS). The frontal EEG was acquired using a bilateral bispectral (BIS VISTA (TM) v2.0, Medtronic, Ireland) sensor. EEG data was then split into 5-second epochs, and for each epoch, the anesthesiologist's classification was used to label it as responsiveness (no-LOR) or unresponsiveness (LOR). All 5-second epochs were then used as inputs for the CNN model to classify the untrained segment as no-LOR or LOR. Results: The CNN model was able to identify the transition from no-LOR to LOR successfully, achieving 97.90 +/- 0.07% accuracy on the cross-validation set. Conclusion: The obtained results showed that the proposed CNN model was quite efficient in the responsiveness/unresponsiveness classification. We consider our approach constitutes an additional technique to the current methods used in the daily clinical setting where LOR is identified by the loss of response to verbal commands or mechanical stimulus. We therefore hypothesized that automated EEG analysis could be a useful tool to detect the moment of LOR, especially using machine learning approaches.
- Performance of blink reflex in patients during anesthesia induction with propofol and remifentanil: prediction probabilities and multinomial logistic analysisPublication . Ferreira, Ana Isabel Leitão; Nunes, Catarina S; Vide, Sérgio; Felgueiras, João; Cardoso, Márcio; Amorim, Pedro; Mendes, JoaquimThe amount of propofol needed to induce loss of responsiveness varied widely among patients, and they usually required less than the initial dose recommended by the drug package inserts. Identifying precisely the moment of loss of responsiveness will determine the amount of propofol each patient needs. Currently, methods to decide the exact moment of loss of responsiveness are based on subjective analysis, and the monitors that use objective methods fail in precision. Based on previous studies, we believe that the blink reflex can be useful to characterize, more objectively, the transition from responsiveness to unresponsiveness. The purpose of this study is to investigate the relation between the electrically evoked blink reflex and the level of sedation/anesthesia measured with an adapted version of the Richmond Agitation-Sedation Scale, during the induction phase of general anesthesia with propofol and remifentanil. Adding the blink reflex to other variables may allow a more objective assessment of the exact moment of loss of responsiveness and a more personalized approach to anesthesia induction.
- Patterns of hysteresis between induction and emergence of neuroanesthesia are present in spinal and intracranial surgeriesPublication . Ferreira, Ana Isabel Leitão; Correia, Rui; Vide, Sérgio; Ferreira, Ana Dias; Kelz, Max B.; Mendes, Joaquim; Nunes, Catarina S.; Amorim, PedroRecovery of consciousness is usually seen as a passive process, with emergence from anesthesia depicted as the inverse process of induction resulting from the elimination of anesthetic drugs from their central nervous system sites of action. However, that need not be the case. Recently it has been argued that we might encounter hysteresis to changes in the state of consciousness, known as neural inertia. This phenomenon has been debated in neuroanesthesia, as manipulation of the brain might further influence recovery of consciousness. The present study is aimed at assessing hysteresis between induction and emergence under propofol-opioid neuroanesthesia in humans using estimated propofol concentrations in both spinal and intracranial surgeries.
- Towards personalized anesthesia: predictive factors for propofol requirements for loss of consciousnessPublication . Nunes, Catarina S.; Ferreira, Ana Isabel Leitão; Correia, Rui P.; Amorim, Pedro
- The influence of two different drug infusion profiles on the pharmacodynamics model performancePublication . Ferreira, Ana Isabel Leitão; Nunes, Catarina S.; Gabriel, J.; Amorim, PedroTo model the effect of anesthetic drugs on the Bispectral Index (BIS) of the EEG is of great importance for a reliable predictive response model during surgery. In this study, the impact of using two different drug infusion profiles in a pharmacodynamics interaction model was studied and the methods were compared with respect to their performance. Clinical data of 22 patients were considered. The interaction model was optimized per patient using nonlinear least squares during the induction of anesthesia, and tested for prediction abilities of test patients. In the optimization phase, all models could follow the BIS trend with errors not significantly differ- ent from zero. In the test data the choice of drug infusion pro- file proved to have a significant impact, showing that the per- formance is greatly influenced by the interaction. Results also show a time delay between the BIS signal and the Modeled BIS in both groups. This delay corresponds to a delay in the dy- namics of the patient and could be related to the delay in BIS processing time. This work is an important step to predict the effect of anesthetic drugs.
- Neuro-fuzzy models to predict the required propofol amount for loss of consciousness during general anesthesia: a preliminary studyPublication . Ferreira, Ana Isabel Leitão; Mendes, Joaquim; Amorim, Pedro; Nunes, Catarina S.This study presents several models to predict the total amount of the anesthetic drug propofol required to achieve loss of consciousness during the induction phase of anesthesia, considering different clinical variables. The data from 49 patients under anesthesia for neurosurgical procedures, were used in this study. Takagi-Sugeno-Kang (TSK) fuzzy models were used to describe the effect of clinical variables on the amount of propofol required for loss of consciousness. The parameters of the TSK models were optimized using an Adaptive Network-Fuzzy Interference System. All models were trained with the data of 35 patients and tested with the data of 14 patients. These models proved to have reasonable prediction properties. The fuzzy model with the best balanced performance used only two inputs: the systolic arterial pressure and the Bispectral Index of the EEG.