Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders.

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  • Additional Information
    • Source:
      Publisher: Sage Publications Country of Publication: United States NLM ID: 101213033 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2169-5202 (Electronic) Linking ISSN: 15500594 NLM ISO Abbreviation: Clin EEG Neurosci Subsets: MEDLINE
    • Publication Information:
      Publication: Thoudand Oaks, CA : Sage Publications
      Original Publication: Wheaton, IL : EEG and Clinical Neuroscience Society, c2004-
    • Subject Terms:
      Electroencephalography*/methods ; Substance-Related Disorders*/diagnosis; Male ; Adult ; Humans ; Brain ; Brain Mapping ; Biomarkers
    • Abstract:
      Background: People diagnosed with substance use disorders (SUDs) are at risk for impairment of brain function and structure. However, physicians still do not have any clinical biomarker of brain impairment that helps diagnose or treat these patients when needed. The most common method to study these patients is the classical electroencephalographic (EEG) analyses of absolute and relative powers, but this has limited individual clinical applicability. Other non-classical measures such as frequency band ratios and entropy show promise in these patients. Therefore, there is a need to expand the use of quantitative (q)EEG beyond classical measures in clinical populations. Our aim is to assess a group of classical and non-classical qEEG measures in a population with SUDs. Methods: We selected 56 non-medicated and drug-free adult patients (30 males) diagnosed with SUDs and admitted to Rehabilitation Clinics. According to qualitative EEG findings, patients were divided into four groups. We estimated the absolute and relative powers and calculated the entropy, and the alpha/(delta + theta) ratio. Results: Our findings showed a significant variability of absolute and relative powers among patients with SUDs. We also observed a decrease in the EEG-based entropy index and alpha/(theta + delta) ratio, mainly in posterior regions, in the patients with abnormal qualitative EEG. Conclusions: Our findings support the view that the power spectrum is not a reliable biomarker on an individual level. Thus, we suggest shifting the approach from the power spectrum toward other potential methods and designs that may offer greater clinical possibilities.
      Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
    • Contributed Indexing:
      Keywords: clinical biomarker; electroencephalography; entropy; power spectrum; substance use disorders
    • Accession Number:
      0 (Biomarkers)
    • Publication Date:
      Date Created: 20231018 Date Completed: 20240416 Latest Revision: 20240416
    • Publication Date:
      20240416
    • Accession Number:
      10.1177/15500594231208245
    • Accession Number:
      37849312