Identifying Ketamine Responses in Treatment-Resistant Depression Using a Wearable Forehead EEG

arXiv Preprint Archive  – May 29, 2018

Source: arXiv

Summary

A breakthrough in depression treatment: wearable forehead sensors can now predict with over 80% accuracy which patients will respond positively to ketamine therapy. Brain wave patterns, particularly in the prefrontal area, serve as reliable indicators of treatment success. Lower theta waves before treatment and increased alpha waves after ketamine administration signal better outcomes in patients with hard-to-treat depression.

Abstract

This study explores the responses to ketamine in patients with treatment-resistant depression (TRD) using a wearable forehead electroencephalography (EEG) device. We recruited fifty-five outpatients with TRD who were randomised into three approximately equal-sized groups (A: 0.5 mg/kg ketamine; B: 0.2 mg/kg ketamine; and C: normal saline) under double-blind conditions. The ketamine responses were measured by EEG signals and Hamilton Depression Rating Scale (HDRS) scores. At baseline, responders showed a significantly weaker EEG theta power than did non- responders (p < 0.05). Responders exhibited a higher EEG alpha power but lower EEG alpha asymmetry and theta cordance at post-treatment than at baseline (p < 0.05). Furthermore, our baseline EEG predictor classified responders and non-responders with 81.3 +- 9.5% accuracy, 82.1 +- 8.6% sensitivity and 91.9 +- 7.4% specificity. In conclusion, the rapid antidepressant effects of mixed doses of ketamine are associated with prefrontal EEG power, asymmetry and cordance at baseline and early post-treatment changes. The prefrontal EEG patterns at baseline may account for recognising ketamine effects in advance. Our randomised, double- blind, placebo-controlled study provides information regarding clinical impacts on the potential targets underlying baseline identification and early changes from the effects of ketamine in patients with TRD.

Comments

No comments yet.

Log in to comment