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Poincare Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia.

ABSTRACT: The Poincaré plot obtained from electroencephalography (EEG) has been used to evaluate the depth of anesthesia. A standalone EEG Analyzer application was developed; raw EEG signals obtained from a bispectral index (BIS) monitor were analyzed using an on-line monitoring system. Correlations between Poincaré plot parameters and other measurements associated with anesthesia depth were evaluated during emergence from inhalational general anesthesia. Of the participants, 20 were adults anesthetized with sevoflurane (adult_{_S E V} ), 20 were adults anesthetized with desflurane (adult_{_D E S} ), and 20 were pediatric patients anesthetized with sevoflurane (ped_{_S E V} ). EEG signals were preprocessed through six bandpass digital filters (f0: 0.5-47 Hz, f1: 0.5-8 Hz, f2: 8-13 Hz, f3: 13-20 Hz, f4: 20-30 Hz, and f5: 30-47 Hz). The Poincaré plot-area ratio (PP_AR = PP _{A_fx} /PP _{A_f0} , fx = f1?f5) was analyzed at five frequency ranges. Regardless of the inhalational anesthetic used, there were strong linear correlations between the logarithm of PP _AR at f5 and BIS (R ² = 0.67, 0.79, and 0.71, in the adult_{_S E V} , adult_{_D E S} , and ped_{_S E V} groups, respectively). As an additional observation, a part of EMG activity at the gamma range of 30-47 Hz probably influenced the calculations of BIS and PP _{AR_f5} with a non-negligible level. The logarithm of PP_AR in the gamma band was most sensitive to state changes during the emergence process and could provide a new non-proprietary parameter that correlates with changes in BIS during measurement of anesthesia depth.

SUBMITTER: Hayase K

PROVIDER: S-EPMC7900422 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Poincaré Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia.

Hayase Kazuma K Kainuma Atsushi A Akiyama Koichi K Kinoshita Mao M Shibasaki Masayuki M Sawa Teiji T

Frontiers in physiology 20210209

The Poincaré plot obtained from electroencephalography (EEG) has been used to evaluate the depth of anesthesia. A standalone EEG Analyzer application was developed; raw EEG signals obtained from a bispectral index (BIS) monitor were analyzed using an on-line monitoring system. Correlations between Poincaré plot parameters and other measurements associated with anesthesia depth were evaluated during emergence from inhalational general anesthesia. Of the participants, 20 were adults anesthetized w ...[more]

PMID: 33633587

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Project description:The Poincaré plot is a geometrical technique used to visualize and quantify the correlation between two consecutive data points in a time-series. Since the dynamics of fluctuations in physiological rhythms exhibit long-term correlation and memory, this study aimed to extend the Poincaré plot by calculating the correlation between sequential data points in a time-series, rather than between two consecutive points. By incorporating this so-called lag, we hope to integrate a temporal aspect into quantifying the correlation, to depict whether a physiological system holds prolonged association between events separated by time. In doing so, it attempts to instantaneously characterize the intrinsic behavior of a complex system. We tested this hypothesis on three different physiological time-series: heart rate variability in patients with liver cirrhosis, respiratory rhythm in asthma and body temperature fluctuation in patients with cirrhosis, to evaluate the potential application of the extended Poincaré method in clinical practice. When studying the cardiac inter-beat intervals, the extended Poincaré plot revealed a stronger autocorrelation for patients with decompensated liver cirrhosis compared to less severe cases using Pearson's correlation coefficient. In addition, long-term variability (known as SD2 in the extended Poincaré plot) appeared as an independent prognostic variable. This holds significance by acting as a non-invasive tool to evaluate patients with chronic liver disease and potentially facilitate transplant selection as an adjuvant to traditional criteria. For asthmatics, employing the extended Poincaré plot allowed for a non-invasive tool to differentially diagnose various classifications of respiratory disease. In the respiratory inter-breath interval analysis, the receiver operating characteristic (ROC) curve provided evidence that the extension of the Poincaré plot holds a greater advantage in the classification of asthmatic patients, over the traditional Poincaré plot. Lastly, the analysis of body temperature from patients using the extended Poincaré plot helped identify inpatients from outpatients with cirrhosis. Through these analyses, the extended Poincaré plot provided unique and additional information which could potentially make a difference in clinical practice. Conclusively, the potential use of our work lies in its possible application of predicting mortality for the organ allocation procedure in patients with cirrhosis and non-invasively distinguish between atopic and non-atopic asthma.

Project description:ObjectivesTo explore the role of the Poincaré plot derived from a 24-hour Holter recording in distinguishing vasovagal syncope (VVS) from postural tachycardia syndrome (POTS) in pediatric patients.Materials and methodsPediatric patients with VVS or POTS, hospitalized in Peking University First Hospital between January 2012 and December 2018, were included in a derivation study. The transverse axis (T), longitudinal axis (L), T/L ratio, product T × L, distance between the origin and the proximal end of the longitudinal axis (pro-D), and distance between the origin and distal end of the longitudinal axis (dis-D) of the Poincaré plot were compared between the VVS and POTS groups, and the differential diagnostic performance of the above-mentioned graphic parameters was evaluated using receiver operating characteristic curve analysis. A validation study was conducted in pediatric patients hospitalized between January 2019 and December 2020.ResultsIn school-aged children, the T, L, T/L, T × L, and dis-D values of patients with VVS were greater than those of patients with POTS; in adolescents, the T, T/L, T × L, and pro-D values of patients with VVS were greater than those of patients with POTS. Using a T/L cut-off value of 0.3 to distinguish between the two diseases, the sensitivity and specificity were 91.0 and 90.5%, respectively, for the total participants; 91.6 and 88.9%, respectively, for the school-aged children; and 82.1 and 95.7%, respectively, for the adolescents. In the validation study, a T/L cut-off value of 0.3 yielded an accuracy, sensitivity, and specificity of 81.8, 87.2, and 77.6%, respectively, in the total participants; 76.5, 82.6, and 71.4%, respectively, in the school-aged children; and 89.2, 93.8, and 85.7%, respectively, in the adolescents, in distinguishing VVS from POTS validated by clinical diagnosis.ConclusionsThe graphic parameters of the Poincaré plot are significantly different between VVS and POTS in pediatric patients, and the T/L of the Poincaré plot may be a useful measure to help differentiate VVS from POTS in children and adolescents.

Project description:BackgroundPhase lag entropy (PLE) is a novel anesthetic depth indicator that uses four-channel electroencephalography (EEG) to measure the temporal pattern diversity in the phase relationship of frequency signals in the brain. The purpose of the study was to evaluate the anesthetic depth monitoring using PLE and to evaluate the correlation between PLE and bispectral index (BIS) values during propofol anesthesia.MethodsIn thirty-five adult patients undergoing elective surgery, anesthesia was induced with propofol using target-controlled infusion (the Schneider model). We recorded the PLE value, raw EEG, BIS value, and hemodynamic data when the target effect-site concentration (Ce) of propofol reached 2, 3, 4, 5, and 6??g/ml before intubation and 6, 5, 4, 3, 2??g/ml after intubation and injection of muscle relaxant. We analyzed whether PLE and raw EEG data from the PLE monitor reflected the anesthetic depth as the Ce of propofol changed, and whether PLE values were comparable to BIS values.ResultsPLE values were inversely correlated to changes in propofol Ce (propofol Ce from 0 to 6.0??g/ml, r2?=?-?0.83; propofol Ce from 6.0 to 2.0??g/ml, r2?=?-?0.46). In the spectral analysis of EEG acquired from the PLE monitor, the persistence spectrogram revealed a wide distribution of power at loss of consciousness (LOC) and recovery of consciousness (ROC), with a narrow distribution during unconsciousness. The power spectrogram showed the typical pattern seen in propofol anesthesia with slow alpha frequency band oscillation. The PLE value demonstrated a strong correlation with the BIS value during the change in propofol Ce from 0 to 6.0??g/ml (r2?=?0.84). PLE and BIS values were similar at LOC (62.3 vs. 61.8) (P?>?0.05), but PLE values were smaller than BIS values at ROC (64.4 vs 75.7) (P?<?0.05).ConclusionsThe PLE value is a useful anesthetic depth indicator, similar to the BIS value, during propofol anesthesia. Spectral analysis of EEG acquired from the PLE monitor demonstrated the typical patterns seen in propofol anesthesia.Trial registrationThis clinical trial was retrospectively registered at ClinicalTrials.gov at October 2017 (NCT03299621).

Project description:BACKGROUND:Recent literature suggests a significant association between blood pressure variability (BPV) and postoperative outcomes after cardiac surgery. However, its outcome prediction ability remains unclear. Current prediction models use static preoperative patient factors. We explored the ability of Poincaré plots and coefficient of variation (CV) by measuring intraoperative BPV in predicting adverse outcomes. METHODS:In this retrospective, observational, cohort study, 3687 adult patients (>?18?years) undergoing cardiac surgery requiring cardio-pulmonary bypass from 2008 to 2014 were included. Blood pressure variability was computed by Poincare plots and CV. Standard descriptors (SD) SD1, SD2 were measured with Poincare plots by ellipse fitting technique. The outcomes analyzed were the 30-day mortality and postoperative renal failure. Logistic regression models adjusted for preoperative and surgical factors were constructed to evaluate the association between BPV parameters and outcomes. C-statistics were used to analyse the predictive ability. RESULTS:Analysis found that, 99 (2.7%) patients died within 30?days and 105 (2.8%) patients suffered from in-hospital renal failure. Logistic regression models including BPV parameters (standard descriptors from Poincare plots and CV) performed poorly in predicting postoperative 30-day mortality and renal failure [Concordance(C)-Statistic around 0.5]. They did not add any significant value to the standard STS risk score [C-statistic: STS alone 0.7, STS?+?BPV parmeters 0.7]. CONCLUSIONS:In conclusion, BP variability computed from Poincare plots and CV were not predictive of mortality and renal failure in cardiac surgical patients. Patient comorbid conditions and other preoperative factors are still the gold standard for outcome prediction. Future directions include analysis of dynamic parameters such as complexity of physiological signals in identifying high risk patients and tailoring management accordingly.

Project description:Highlights? Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.? Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.? Approximate Entropy and Sample Entropy performed best in detecting burst suppression.ObjectiveEntropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents.MethodsTwelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared.ResultsAll the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R (2)) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation efficiency compared with MDFA.ConclusionEach entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure. Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.

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Poincare Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia.

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Poincaré Plot Area of Gamma-Band EEG as a Measure of Emergence From Inhalational General Anesthesia.

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