Literature DB >> 7578656

All-night EEG spectral analysis as a tool for the prediction of clinical response to antidepressant treatment.

R Luthringer1, R Minot, M Toussaint, F Calvi-Gries, N Schaltenbrand, J P Macher.   

Abstract

Earlier investigations have suggested that variables derived from quantified electroencephalographic (EEG) sleep analysis might predict good clinical response in an early phase of antidepressant treatment. In this report we evaluate the predictive value of all-night sleep EEG spectral analysis during the washout period before treatment. We compared the spectral EEG sleep profiles of major depressed inpatients divided into two groups according to an improvement > or = 50% on the Hamilton Rating Scale for Depression. Findings in this population demonstrate the presence of specific characteristics of the responder group compared with the nonresponder group. Delta band relative power was increased in the former group, while theta, alpha, and beta relative power were decreased. All the bands showed decrease in absolute power in the responder group. These results can be interpreted as enhanced sleep intensity in the responder group. All-night sleep EEG spectral variables are valid baseline markers of the functional differences between treatment responders and nonresponders and thus might permit prediction of clinical outcome.

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Year:  1995        PMID: 7578656     DOI: 10.1016/0006-3223(94)00246-Y

Source DB:  PubMed          Journal:  Biol Psychiatry        ISSN: 0006-3223            Impact factor:   13.382


  4 in total

Review 1.  Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years.

Authors:  G Voegeli; M L Cléry-Melin; N Ramoz; P Gorwood
Journal:  Drugs       Date:  2017-12       Impact factor: 9.546

2.  Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Authors:  Alik S Widge; M Taha Bilge; Rebecca Montana; Weilynn Chang; Carolyn I Rodriguez; Thilo Deckersbach; Linda L Carpenter; Ned H Kalin; Charles B Nemeroff
Journal:  Am J Psychiatry       Date:  2018-10-03       Impact factor: 18.112

3.  Spectral EEG sleep profiles as a tool for prediction of clinical response to antidepressant treatment.

Authors:  Jean-Paul Macher; Rémy Luthringer; Luc Staner
Journal:  Dialogues Clin Neurosci       Date:  2004-03       Impact factor: 5.986

Review 4.  Contribution of sleep research to the development of new antidepressants.

Authors:  Olivier Le Bon
Journal:  Dialogues Clin Neurosci       Date:  2005       Impact factor: 5.986

  4 in total

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