EEG wakefulness regulation in transdiagnostic patients after a recent suicide attempt

Rüesch, Annia; Ip, Cheng-Teng; Bankwitz, Anna; Villar de Araujo, Tania; Hörmann, Christoph; Adank, Atalìa; Schoretsanitis, Georgios; Kleim, Birgit; Olbrich, Sebastian

doi:10.1016/j.clinph.2023.08.018

Cited by 1 publication

(2 citation statements)

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“…Each 1 s epoch was automatically classified into the following arousal states using the algorithm-based Vigilance Algorithm Leipzig (VIGALL 2.0), resulting in a vigilance time-course: stage 0 (highest arousal), A1, A2, A3, B1, B2/3, C (lowest arousal, sleep onset, classified visually by sleep grapho-elements from an experienced rater). In the current analysis, as well as in prior studie [24,25,48], the prevalence of stages A2 and A3 has been relatively low. Therefore, we adopted the conventional practice of combining the two A stages (A2/3) [24,25,48].…”

Section: Eeg Processing and Classification Of Eeg-vigilancesupporting

confidence: 46%

“…In the current analysis, as well as in prior studie [24,25,48], the prevalence of stages A2 and A3 has been relatively low. Therefore, we adopted the conventional practice of combining the two A stages (A2/3) [24,25,48]. Since no subject showed stage C segments after visual inspection, the preprocessing resulted in five different vigilance stages (0, A1, A2/3, B1, B2/3).…”

Section: Eeg Processing and Classification Of Eeg-vigilancesupporting

confidence: 46%

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EEG-vigilance regulation is associated with and predicts ketamine response in major depressive disorder

Ip,

de Bardeci,

Kronenberg

et al. 2024

Transl Psychiatry

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Ketamine offers promising new therapeutic options for difficult-to-treat depression. The efficacy of treatment response, including ketamine, has been intricately linked to EEG measures of vigilance. This research investigated the interplay between intravenous ketamine and alterations in brain arousal, quantified through EEG vigilance assessments in two distinct cohorts of depressed patients (original dataset: n = 24; testing dataset: n = 24). Clinical response was defined as a decrease from baseline of >33% on the Montgomery–Åsberg Depression Rating Scale (MADRS) 24 h after infusion. EEG recordings were obtained pre-, start-, end- and 24 h post- infusion, and the resting EEG was automatically scored using the Vigilance Algorithm Leipzig (VIGALL). Relative to placebo (sodium chloride 0.9%), ketamine increased the amount of low-vigilance stage B1 at end-infusion. This increase in B1 was positively related to serum concentrations of ketamine, but not to norketamine, and was independent of clinical response. In contrast, treatment responders showed a distinct EEG pattern characterized by a decrease in high-vigilance stage A1 and an increase in low-vigilance B2/3, regardless of whether placebo or ketamine had been given. Furthermore, pretreatment EEG differed between responders and non-responders with responders showing a higher percentage of stage A1 (53% vs. 21%). The logistic regression fitted on the percent of A1 stages was able to predict treatment outcomes in the testing dataset with an area under the ROC curve of 0.7. Ketamine affects EEG vigilance in a distinct pattern observed only in responders. Consequently, the percentage of pretreatment stage A1 shows significant potential as a predictive biomarker of treatment response.Clinical Trials Registration:https://www.clinicaltrialsregister.eu/ctr-search/trial/2013-000952-17/CZRegistration number: EudraCT Number: 2013-000952-17.

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