Abstract

Background: Patients with major depressive disorder (MDD) often present with co-occurring anxiety symptoms. The network method provides a novel view on understanding the co-occurrence of depressive and anxiety symptoms. Thus, the purpose of our study was to explore it by applying network analysis methods.Methods: We used electronic medical records from West China Hospital in China. In total, 3,424 patients who met the criteria for MDD were included. R-studio 3.6 was used to estimate the network structure. First, we estimated the network structure of depression and anxiety symptoms using the graphic LASSO algorithm. Then, we estimated the centrality indices of nodes to determine which symptoms are more central in the network. We then estimated the bridge centrality indices using the bridge function via the R package networktools.Results: Some strong connections were found like “easy to wake up,” “wake up early,” and “difficulty falling asleep,” “suicidal thoughts,” and “hopelessness.” “Depressed mood,” “somatic anxiety,” “hopelessness,” “anxiety mood,” and “tension” have the higher centrality indices. Results revealed eight bridge symptoms (e.g., concentration/memory difficulty, gastrointestinal symptoms) in the co-occurrence network structure.Conclusions: This research suggests that the described approach in mapping the presence of anxiety symptoms in individuals with major depression might potentially increase diagnostic precision and help choose more targeted interventions and potentially reduce the occurrence of treatment resistance.

Highlights

  • Major depressive disorder (MDD) is a debilitating psychiatric condition characterized by depressed mood, decreased energy level, and lack of interest in pleasurable activities [1]

  • Gaspersz’s study showed that 40–60% of patients with MDD have anxiety symptoms [3]. Another survey suggested that 50% of individuals with MDD meet the diagnostic criteria for anxiety disorders [4, 5]

  • We identified MDD patients through recorded primary diagnosis at discharge and based on the International Classification of Disease, Tenth Revision (Clinical Modification Codes F32, single episode major depressive disorder and F33, recurrent major depressive disorder), which has been described in another study [35]

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Summary

Introduction

Major depressive disorder (MDD) is a debilitating psychiatric condition characterized by depressed mood, decreased energy level, and lack of interest in pleasurable activities [1]. It has a significant burden on both individuals and society and is related to psychological impairments and health dysfunction. Gaspersz’s study showed that 40–60% of patients with MDD have anxiety symptoms [3]. Another survey suggested that 50% of individuals with MDD meet the diagnostic criteria for anxiety disorders [4, 5]. Patients with major depressive disorder (MDD) often present with co-occurring anxiety symptoms. The purpose of our study was to explore it by applying network analysis methods

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