Bispectral EEG (BSEEG) to assess arousal after electro-convulsive therapy (ECT)

Zarei, Kasra; Sparr, Nicholas A; Trapp, Nicholas T.; Neuhaus, Elena D; Cromwell, John W.; Boes, Aaron D.; Shinozaki, Gen

doi:10.1016/j.psychres.2020.112811

Cited by 6 publications

(5 citation statements)

References 47 publications

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“…As raw EEG recordings were digitally converted into power spectral density to calculate BSEEG scores in our previous studies ( 9, 25, 26 ), animal EEG recordings were analyzed using a similar algorithm to the human study. We used the software SleepPro (Sirenia EEG system; Pinnacle Technology, Inc., Lawrence, KS) to export raw data after Fast Fourier Transformation.…”

Section: Methodsmentioning

confidence: 99%

The bispectral EEG (BSEEG) method quantifies post-operative delirium-like states in young and aged mice after head mount implantation surgery

Nishiguchi,

Shibata,

Yamanishi

et al. 2024

Preprint

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Delirium, a syndrome characterized by an acute change in attention, awareness, and cognition, is commonly observed in older adults and has multiple potential triggers, including illness, drug, trauma, and surgery. There are few quantitative monitoring methods in clinical settings. We developed the bispectral electroencephalography (BSEEG) method in clinical research that can detect the presence of and quantify the severity of delirium using a novel algorithm. In the pre-clinical model, we reported that the BSEEG method can capture a delirium-like state in mice following LPS administration. However, its application to post-operative delirium (POD) has not yet been validated in animal experiments. Therefore, this study aimed to create a POD model mouse with the BSEEG method by monitoring BSEEG scores after EEG head-mount implantation surgery throughout the recovery phase. We compared the BSEEG scores of C57BL/6J young (2-3 months old) with aged (18-19 months old) mice for quantitative evaluation of the delirium-like state after the surgery. Postoperatively, both groups showed increased BSEEG scores and a loss of regular diurnal changes in BSEEG scores every daytime and night. In young mice, BSEEG scores and regular diurnal changes recovered relatively quickly to baseline by around postoperative day 3. On the other hand, aged mice had prolonged increases in postoperative BSEEG scores and it reached steady state only after around postoperative day 8. This study suggests the BSEEG method can be utilized to quantitatively evaluate POD and also assess the effect of aging on recovery from POD in pre-clinical model.

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Section: Methodsmentioning

confidence: 99%

The bispectral EEG (BSEEG) method quantifies post-operative delirium-like states in young and aged mice after head mount implantation surgery

Nishiguchi,

Shibata,

Yamanishi

et al. 2024

Preprint

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“…For our second cohort, a different EEG device (ZA, ProAssist, Osaka, Japan) was used and the sampling rate of this device was 128 Hz. We applied our newly developed algorithm of BSEEG from EEG signals obtained from the forehead of the study participants 29 , 30 , 40 , 44 . Signals were obtained from Fp1-A1 and Fp2-A2 from the 1st cohort.…”

Section: Methodsmentioning

confidence: 99%

“…Signals were obtained from Fp1-A1 only from the 2nd cohort. The BSEEG score was calculated as a power spectral density (PSD) ratio between low frequency (3 Hz) to high frequency (10 Hz) as described previously 29 , 40 , 44 . In other words, PSD of low frequency (3 Hz) divided by PSD of high frequency (10 Hz) was BSEEG score.…”

Section: Methodsmentioning

confidence: 99%

Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Yamanashi

Kajitani

Iwata

et al. 2021

Sci Rep

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Current methods for screening and detecting delirium are not practical in clinical settings. We previously showed that a simplified EEG with bispectral electroencephalography (BSEEG) algorithm can detect delirium in elderly inpatients. In this study, we performed a post-hoc BSEEG data analysis using larger sample size and performed topological data analysis to improve the BSEEG method. Data from 274 subjects included in the previous study were analyzed as a 1st cohort. Subjects were enrolled at the University of Iowa Hospitals and Clinics (UIHC) between January 30, 2016, and October 30, 2017. A second cohort with 265 subjects was recruited between January 16, 2019, and August 19, 2019. The BSEEG score was calculated as a power ratio between low frequency to high frequency using our newly developed algorithm. Additionally, Topological data analysis (TDA) score was calculated by applying TDA to our EEG data. The BSEEG score and TDA score were compared between those patients with delirium and without delirium. Among the 274 subjects from the first cohort, 102 were categorized as delirious. Among the 206 subjects from the second cohort, 42 were categorized as delirious. The areas under the curve (AUCs) based on BSEEG score were 0.72 (1st cohort, Fp1-A1), 0.76 (1st cohort, Fp2-A2), and 0.67 (2nd cohort). AUCs from TDA were much higher at 0.82 (1st cohort, Fp1-A1), 0.84 (1st cohort, Fp2-A2), and 0.78 (2nd cohort). When sensitivity was set to be 0.80, the TDA drastically improved specificity to 0.66 (1st cohort, Fp1-A1), 0.72 (1st cohort, Fp2-A2), and 0.62 (2nd cohort), compared to 0.48 (1st cohort, Fp1-A1), 0.54 (1st cohort, Fp2-A2), and 0.46 (2nd cohort) with BSEEG. BSEEG has the potential to detect delirium, and TDA is helpful to improve the performance.

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“…Raw EEG signals were processed and BSEEG score was calculated as a power ratio of low frequency (3 Hz) to high frequency (10 Hz) as described previously. [12][13][14]20 Further details are described in the supplementary material.…”

Section: Bseeg Data Collection and Score Calculationmentioning

confidence: 99%

Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality

Yamanashi¹,

Crutchley²,

Wahba³

et al. 2021

Br J Psychiatry

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Background We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes. Aims To improve the BSEEG method by introducing a new EEG device. Method In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed. Results We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality. Conclusions We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

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Bispectral EEG (BSEEG) to assess arousal after electro-convulsive therapy (ECT)

Cited by 6 publications

References 47 publications

The bispectral EEG (BSEEG) method quantifies post-operative delirium-like states in young and aged mice after head mount implantation surgery

The bispectral EEG (BSEEG) method quantifies post-operative delirium-like states in young and aged mice after head mount implantation surgery

Topological data analysis (TDA) enhances bispectral EEG (BSEEG) algorithm for detection of delirium

Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality

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