Hostname: page-component-5c6d5d7d68-lvtdw Total loading time: 0 Render date: 2024-08-27T12:19:24.759Z Has data issue: false hasContentIssue false
  • English
  • Français

Endogenous phenotype of diagnostic transition from major depressive disorder to bipolar disorder: a prospective cohort study

Published online by Cambridge University Press:  27 August 2024

S. Shim
S. Shim*
Affiliation:
psychiatry, soonchunhyang university cheonan hospital, cheonan, Korea, Republic Of

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Introduction

This study investigated sensor-level electroencephalography (EEG) power and related source-level cortical activity using resting-state EEG in patients with MDD and BD.

Objectives

This study aims to comparing bipolar disorder (BD) and major depressive disorder (MDD) to understand neuropathology of these disorders.

Methods

A total of 68 patients with MDD were enrolled and recorded EEG. Among patients with MDD, 17 patients with MDD converted to BD during the study periods. Clinical symptoms and EEG measures were compared between two groups. This study applied machine learning to differentiate the two groups using sensor and source-level features

Results

At the sensor level, patients with BD showed higher power of AF3 channel in the theta beta band(p=0.011) and FC5 channel in the low alpha band(p=0.014), compared to MDD. At the source-level, compared to MDD, patients with BD showed higher activity in the right anterior cingulate(p=0.011) and left parahippocampal gyrus(p=0.035). The best classification performance for MDD and BD showed an accuracy of 80.88%, a sensitivity of 76.47%, and a specificity of 82.35% based on theta and low alpha band power and activity features.

Conclusions

Our findings might suggest different theta and low alpha band activity between patients with BD and MDD might serve clinically as a candidate neuromarker for differentiating two distinct mood disorders.

Disclosure of Interest

None Declared

Type
Abstract
Information
European Psychiatry , Volume 67 , Special Issue S1: Abstracts of the 32nd European Congress of Psychiatry , April 2024 , pp. S326
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of European Psychiatric Association
Submit a response

Comments

No Comments have been published for this article.