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Variations in Values of State, Response Entropy and Haemodynamic Parameters Associated with Development of Different Epileptiform Patterns during Volatile Induction of General Anaesthesia with Two Different Anaesthetic Regimens Using Sevoflurane in Comparison with Intravenous Induct: A Comparative Study.

ABSTRACT: BACKGROUND AND OBJECTIVES:Raw electroencephalographic (EEG) signals are rarely used to monitor the depth of volatile induction of general anaesthesia (VIGA) with sevoflurane, even though EEG-based indices may show aberrant values. We aimed to identify whether response (RE) and state entropy (SE) variations reliably reflect the actual depth of general anaesthesia in the presence of different types of epileptiform patterns (EPs) in EEGs during induction of general anaesthesia. MATERIALS AND METHODS:A randomized, prospective clinical study was performed with 60 patients receiving VIGA using sevoflurane with the increasing concentrations (group VIMA) or the vital capacity (group VCRII) technique or an intravenous single dose of propofol (group PROP). Facial electromyography (fEMG), fraction of inspired sevoflurane (FiAA), fraction of expired sevoflurane (FeAA), minimal alveolar concentration (MAC) of sevoflurane, RE and SE, and standard electroencephalographic evaluations were performed in these patients. RESULTS:In contrast to periodic epileptiform discharges, erroneous SE and RE values in the patients' EEGs were associated with the presence of polyspikes (PS) and rhythmic polyspikes (PSR), which were more likely to indicate toxic depth rather than false emergence from anaesthesia with no changes in the FiAA, FeAA, and MAC of sevoflurane. CONCLUSION:Calculated RE and SE values may be misleading during VIGA when EPs are present in patients' EEGs. During VIGA with sevoflurane, we recommend monitoring raw EEG data in scientific studies to correlate it with potentially erroneous RE and SE values and the end-tidal concentration of sevoflurane in everyday clinical practice, when monitoring raw EEG is not available, because they can mislead anaesthesiologists to reduce sevoflurane levels in the ventilation gas and result in unintentional true emergence from anaesthesia. Further studies are required to investigate the behaviour of EEG-based indices during rapid changes in sevoflurane concentrations at different stages of VIGA and the influence of polyspikes and rhythmic polyspikes on the transformation of EEG signals into a digital form.

SUBMITTER: Stasiowski M

PROVIDER: S-EPMC7349226 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Variations in Values of State, Response Entropy and Haemodynamic Parameters Associated with Development of Different Epileptiform Patterns during Volatile Induction of General Anaesthesia with Two Different Anaesthetic Regimens Using Sevoflurane in Comparison with Intravenous Induct: A Comparative Study.

Stasiowski Michał M Duława Anna A Szumera Izabela I Marciniak Radosław R Niewiadomska Ewa E Kaspera Wojciech W Krawczyk Lech L Ładziński Piotr P Grabarek Beniamin Oskar BO Jałowiecki Przemysław P

Brain sciences 20200612 6

<h4>Background and objectives</h4>Raw electroencephalographic (EEG) signals are rarely used to monitor the depth of volatile induction of general anaesthesia (VIGA) with sevoflurane, even though EEG-based indices may show aberrant values. We aimed to identify whether response (RE) and state entropy (SE) variations reliably reflect the actual depth of general anaesthesia in the presence of different types of epileptiform patterns (EPs) in EEGs during induction of general anaesthesia.<h4>Materials ...[more]

PMID: 32545600

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Project description:IntroductionTotal hip replacement is one of the most commonly performed major orthopaedic operations. Goal-directed therapy (GDT) using haemodynamic monitoring has previously demonstrated outcome benefits in high-risk surgical patients under general anaesthesia. GDT has never been formally assessed during regional anaesthesia.MethodsPatients undergoing total hip replacement while under regional anaesthesia were randomised to either the control group (CTRL) or the protocol group (GDT). Patients in the GDT group, in addition to standard monitoring, were connected to the FloTrac sensor/Vigileo monitor haemodynamic monitoring system, and a GDT protocol was used to maximise the stroke volume and target the oxygen delivery index to > 600 mL/minute/m2.ResultsPatients randomised to the GDT group were given a greater volume of intravenous fluids during the intraoperative period (means ± standard deviation (SD): 6,032 ± 1,388 mL vs. 2,635 ± 346 mL; P < 0.0001), and more of the GDT patients received dobutamine (0 of 20 CTRL patients vs. 11 of 20 GDT patients; P < 0.0003). The GDT patients also received more blood transfused during the intraoperative period (means ± SD: 595 ± 316 mL vs. 0 ± 0 mL; P < 0.0001), although the CTRL group received greater volumes of blood replacement postoperatively (CTRL patients 658 ± 68 mL vs. GDT patients 198 ± 292 mL; P < 0.001). Overall blood consumption (intraoperatively and postoperatively) was not different between the two groups. There were an increased number of complications in the CTRL group (20 of 20 CTRL patients (100%) vs. 16 of 20 GDT patients (80%); P = 0.05). These outcomes were predominantly due to a difference in minor complications (20 of 20 CTRL patients (100%) vs. 15 of 20 GDT patients (75%); P = 0.047).ConclusionsGDT applied during regional anaesthesia in patients undergoing elective total hip replacement changes intraoperative fluid management and may improve patient outcomes by decreasing postoperative complications. Larger trials are required to confirm our findings.

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Project description:Estimating the depth of anaesthesia (DoA) in operations has always been a challenging issue due to the underlying complexity of the brain mechanisms. Electroencephalogram (EEG) signals are undoubtedly the most widely used signals for measuring DoA. In this paper, a novel EEG-based index is proposed to evaluate DoA for 24 patients receiving general anaesthesia with different levels of unconsciousness. Sample Entropy (SampEn) algorithm was utilised in order to acquire the chaotic features of the signals. After calculating the SampEn from the EEG signals, Random Forest was utilised for developing learning regression models with Bispectral index (BIS) as the target. Correlation coefficient, mean absolute error, and area under the curve (AUC) were used to verify the perioperative performance of the proposed method. Validation comparisons with typical nonstationary signal analysis methods (i.e., recurrence analysis and permutation entropy) and regression methods (i.e., neural network and support vector machine) were conducted. To further verify the accuracy and validity of the proposed methodology, the data is divided into four unconsciousness-level groups on the basis of BIS levels. Subsequently, analysis of variance (ANOVA) was applied to the corresponding index (i.e., regression output). Results indicate that the correlation coefficient improved to 0.72 ± 0.09 after filtering and to 0.90 ± 0.05 after regression from the initial values of 0.51 ± 0.17. Similarly, the final mean absolute error dramatically declined to 5.22 ± 2.12. In addition, the ultimate AUC increased to 0.98 ± 0.02, and the ANOVA analysis indicates that each of the four groups of different anaesthetic levels demonstrated significant difference from the nearest levels. Furthermore, the Random Forest output was extensively linear in relation to BIS, thus with better DoA prediction accuracy. In conclusion, the proposed method provides a concrete basis for monitoring patients' anaesthetic level during surgeries.

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