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Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia.

ABSTRACT: Precise cerebral dynamics of action of the anesthetics are a challenge for neuroscientists. This explains why there is no gold standard for monitoring the Depth of Anesthesia (DoA) and why experimental studies may use several electroencephalogram (EEG) channels, ranging from 2 to 128 EEG-channels. Our study aimed at finding the scalp area providing valuable information about brain activity under general anesthesia (GA) to select the more optimal EEG channel to characterized the DoA. We included 30 patients undergoing elective, minor surgery under GA and used a 32-channel EEG to record their electrical brain activity. In addition, we recorded their physiological parameters and the BIS monitor. Each individual EEG channel data were processed to test their ability to differentiate awake from asleep states. Due to strict quality criteria adopted for the EEG data and the difficulties of the real-life setting of the study, only 8 patients recordings were taken into consideration in the final analysis. Using 2 classification algorithms, we identified the optimal channels to discriminate between asleep and awake states: the frontal and temporal F8 and T7 were retrieved as being the two bests channels to monitor DoA. Then, using only data from the F8 channel, we tried to minimize the number of features required to discriminate between the awake and asleep state. The best algorithm turned out to be the Gaussian Naïve Bayes (GNB) requiring only 5 features (Area Under the ROC Curve - AUC- of 0.93 ± 0.04). This finding may pave the way to improve the assessment of DoA by combining one EEG channel recordings with a multimodal physiological monitoring of the brain state under GA. Further work is needed to see if these results may be valid to asses the depth of sedation in ICU.

SUBMITTER: Dubost C

PROVIDER: S-EPMC6779712 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia.

Dubost Clement C Humbert Pierre P Benizri Arno A Tourtier Jean-Pierre JP Vayatis Nicolas N Vidal Pierre-Paul PP

Frontiers in computational neuroscience 20191001

Precise cerebral dynamics of action of the anesthetics are a challenge for neuroscientists. This explains why there is no gold standard for monitoring the Depth of Anesthesia (DoA) and why experimental studies may use several electroencephalogram (EEG) channels, ranging from 2 to 128 EEG-channels. Our study aimed at finding the scalp area providing valuable information about brain activity under general anesthesia (GA) to select the more optimal EEG channel to characterized the DoA. We included ...[more]

PMID: 31632257

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Project description:Delirium after surgery or Postoperative delirium (POD) is an underdiagnosed entity, despite its severity and high incidence. Patients with delirium require a longer hospital stay and present more postoperative complications, which also increases hospital costs. Given its importance and the lack of specific treatment, multifactorial preventive strategies are evidenced based. Our hypothesis is that using general anaesthesia and avoiding the maximum time in excessively deep anaesthetic planes through BIS neuromonitoring device will reduce the incidence of postoperative delirium in patients over the age of 65 and their hospitalization stay. Patients were randomly assigned to two groups: The visible BIS group and the hidden BIS neuromonitoring group. In the visible BIS group, the depth of anaesthesia was sustained between 40 and 60, while in the other group the depth of anaesthesia was guided by hemodynamic parameters and the Minimum Alveolar Concentration value. Patients were assessed three times a day by research staff fully trained during the 72 h after the surgery to determine the presence of POD, and there was follow-up at 30 days. Patients who developed delirium (n = 69) was significantly lower in the visible BIS group (n = 27; 39.1%) than in the hidden BIS group (n = 42, 60.9%; p = 0.043). There were no differences between the subtypes of delirium in the two groups. Patients in the hidden BIS group were kept for 26.6 ± 14.0 min in BIS values < 40 versus 11.6 ± 10.9 min (p < 0.001) for the patients in the visible BIS group. The hospital stay was lower in the visible BIS group 6.56 ± 6.14 days versus the 9.30 ± 7.11 days (p < 0.001) for the hidden BIS group, as well as mortality; hidden BIS 5.80% versus visible BIS 0% (p = 0.01). A BIS-guided depth of anaesthesia is associated with a lower incidence of delirium. Patients with intraoperative neuromonitoring stayed for a shorter time in excessively deep anaesthetic planes and presented a reduction in hospital stay and mortality.

Project description:BackgroundPreexisting factors such as age and cognitive performance can influence the electroencephalogram (EEG) during general anesthesia. Specifically, spectral EEG power is lower in elderly, compared to younger, subjects. Here, the authors investigate age-related changes in EEG architecture in patients undergoing general anesthesia through a detailed examination of spectral and entropic measures.MethodsThe authors retrospectively studied 180 frontal EEG recordings from patients undergoing general anesthesia, induced with propofol/fentanyl and maintained by sevoflurane at the Waikato Hospital in Hamilton, New Zealand. The authors calculated power spectral density and normalized power spectral density, the entropic measures approximate and permutation entropy, as well as the beta ratio and spectral entropy as exemplary parameters used in current monitoring systems from segments of EEG obtained before the onset of surgery (i.e., with no noxious stimulation).ResultsThe oldest quartile of patients had significantly lower 1/f characteristics (P < 0.001; area under the receiver operating characteristics curve, 0.84 [0.76 0.92]), indicative of a more uniform distribution of spectral power. Analysis of the normalized power spectral density revealed no significant impact of age on relative alpha (P = 0.693; area under the receiver operating characteristics curve, 0.52 [0.41 0.63]) and a significant but weak effect on relative beta power (P = 0.041; area under the receiver operating characteristics curve, 0.62 [0.52 0.73]). Using entropic parameters, the authors found a significant age-related change toward a more irregular and unpredictable EEG (permutation entropy: P < 0.001, area under the receiver operating characteristics curve, 0.81 [0.71 0.90]; approximate entropy: P < 0.001; area under the receiver operating characteristics curve, 0.76 [0.66 0.85]). With approximate entropy, the authors could also detect an age-induced change in alpha-band activity (P = 0.002; area under the receiver operating characteristics curve, 0.69 [0.60 78]).ConclusionsLike the sleep literature, spectral and entropic EEG features under general anesthesia change with age revealing a shift toward a faster, more irregular, oscillatory composition of the EEG in older patients. Age-related changes in neurophysiological activity may underlie these findings however the contribution of age-related changes in filtering properties or the signal to noise ratio must also be considered. Regardless, most current EEG technology used to guide anesthetic management focus on spectral features, and improvements to these devices might involve integration of entropic features of the raw EEG.

Project description:BackgroundThe oculocardiac reflex (OCR), bradycardia that occurs during strabismus surgery is a type of trigemino-cardiac reflex (TCR) is blocked by anticholinergics and enhanced by opioids and dexmedetomidine. Two recent studies suggest that deeper inhalational anesthesia monitored by BIS protects against OCR; we wondered if our data correlated similarly.MethodsIn an ongoing, prospective study of OCR/TCR elicited by 10-s, 200 g square-wave traction on extraocular muscles (EOM) from 2009 to 2013, anesthetic depth was estimated in cohorts using either BIS or Narcotrend monitors. The depth of anesthesia was deliberately varied between first and second EOM tested.ResultsFrom 1992 through 2013, 2833 cases of OCR during strabismus surgery were monitored. Excluding re-operations and cases with anticholinergic, OCR from first EOM traction averaged - 20.2 ± 21.8% (S.D.) with a range from - 95 to + 25% in patients aged 0.2 to 90 (median 6.5) years. We did not find correlation between %OCR and brain wave for 97 patients with BIS monitoring and 91 with Narcotrend. With intra-patient controls between first and second muscle, the difference in brain wave did not correlate with difference in %OCR for BIS (r = 0.0002, 95% C. I -0.0002, 0.002, p = 0.30) or for Narcotrend (r = - 0.001, 95% C. I -0.004, 0.001, p = 0.32). Secondary multi-variable analysis demonstrated significant association on %OCR particularly with BIS monitor, opioid, propofol and nitrous oxide concentration in the second EOM tensioned. Sevoflurane concentration correlated better with BIS monitor in second and third EOM tension. %OCR correlated with younger age (p < 0.01). OCR with rapid onset was more profound than those with gradual onset (difference in means 18, 95% C. I 10, 26%).ConclusionsWe were unable to confirm a direct correlation between brain wave monitor and OCR when using multifactorial anesthetic agents. The discrepency with other studies probably reflects direct impact of inhalational agent concentration and less deliberate quantification of EOM tension. We found no level of BIS or Entropy EEG monitoring that uniformly prevents OCR.Trial registryNCT03663413.Datahttp://www.abcd-vision.org/OCR/OCR%20Brainwave%20de-identified.pdf .

Project description:Background: Patients undergoing carotid endarterectomy (CEA) for severe carotid stenosis are vulnerable to postoperative delirium, a complication frequently associated with poor outcome. This study investigated the impact of processed electroencephalogram (EEG)-guided anesthesia management on the incidence of postoperative delirium in patients undergoing CEA. Methods: This single-center, prospective, randomized clinical trial on 255 patients receiving CEA under general anesthesia compared the outcomes of patient state index (PSI) monitoring [SEDLine Brain Function Monitor (Masimo, Inc, Irvine, CA)] (standard group, n = 128) with PSI combined with density spectral array(DSA) -guided monitoring (intervention group, n = 127) to reduce the risk of intraoperative EEG burst suppression. All patients were monitored by continuous transcranial Doppler ultrasound (TCD) and near-infrared spectroscopy (NIRS) to avoid perioperative cerebral hypoperfusion or hyperperfusion. According to the surgical process, EEG suppression time was calculated separately for three stages: S1 (from anesthesia induction to carotid artery clamping), S2 (from clamping to declamping), and S3 (from declamping to the end of surgery). The primary outcome was incidence of postoperative delirium according to the Confusion Assessment Method algorithm during the first 3 days post-surgery, and secondary outcomes were other neurologic complications and length of hospital stay. Results: There were no episodes of cerebral hypoperfusion or hyperperfusion according to TCD and NIRS monitoring in either group during surgery. The incidence of postoperative delirium within 3 days post-surgery was significantly lower in the intervention group than the standard group (7.87 vs. 28.91%, P < 0.01). In the intervention group, the total EEG suppression time and the EEG suppression time during S2 and S3 were shorter (Total, 0 "0" vs. 0 "1.17" min, P = 0.04; S2, 0 "0" vs. 0 "0.1" min, P < 0.01; S3, 0 "0" vs. 0 "0" min, P = 0.02). There were no group differences in incidence of neurologic complications and length of postoperative hospital stay. Conclusion: Processed electroencephalogram-guided general anesthesia management, consisting of PSI combined with DSA monitoring, can significantly reduce the risk of postoperative delirium in patients undergoing CEA. Patients, especially those exhibiting hemodynamic fluctuations or receiving surgical procedures that disrupt cerebral perfusion, may benefit from the monitoring of multiple EEG parameters during surgery. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03622515.

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Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia.

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Selection of the Best Electroencephalogram Channel to Predict the Depth of Anesthesia.

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