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Prediction of electroconvulsive therapy outcome: A network analysis approach
Tessa F Blanken1, Rob Kok2, Jasmien Obbels3
1Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.
Acta Psychiatrica Scandinavica
|November 12, 2024
Summary
Network analysis reveals key depression symptoms predicting electroconvulsive therapy (ECT) remission. Suicidal ideation predicts worse outcomes, while psychomotor retardation and hypochondriasis predict better outcomes in major depressive disorder treatment.
Area of Science:
- Neuroscience
- Psychiatry
- Computational Psychiatry
Background:
- Electroconvulsive therapy (ECT) is an effective treatment for major depressive disorder.
- Individual response to ECT varies significantly and is difficult to predict.
- Symptom heterogeneity may contribute to variable treatment outcomes.
Purpose of the Study:
- To predict remission from major depressive disorder using baseline symptom data.
- To account for inter-symptom associations using a network analysis approach.
- To identify specific baseline depression symptoms that uniquely predict ECT treatment outcomes.
Main Methods:
- Combined individual patient data from two randomized controlled trials (N=161).
- Employed a Mixed Graphical Model to analyze symptom relationships.
- Identified baseline symptoms predicting remission (defined as HRSD≤7 or MADRS<10).
Main Results:
- Three baseline symptoms uniquely predicted remission.
- Suicidality negatively predicted remission (OR=0.75).
- Psychomotor retardation (OR=1.21) and hypochondriasis (OR=1.31) positively predicted remission.
- No significant study heterogeneity or moderation effects were found.
Conclusions:
- Network analysis identified specific symptoms influencing ECT treatment success in major depressive disorder.
- Suicidal ideation is associated with poorer treatment outcomes.
- Psychomotor retardation and hypochondriasis are associated with better treatment outcomes, suggesting potential therapeutic targets.
