Related Experiment Video
Updated: Feb 4, 2026

MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
Published on: August 11, 2015
Clinical factors predicting treatment resistant depression: affirmative results from the European multicenter study
A Kautzky1, M Dold1, L Bartova1
1Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
Objectives:
Clinical variables were investigated in the 'treatment resistant depression (TRD)- III' sample to replicate earlier findings by the European research consortium 'Group for the Study of Resistant Depression' (GSRD) and enable cross-sample prediction of treatment outcome in TRD.
Experimental Procedures:
TRD was defined by a Montgomery and Åsberg Depression Rating Scale (MADRS) score ≥22 after at least two antidepressive trials. Response was defined by a decline in MADRS score by ≥50% and below a threshold of 22. Logistic regression was applied to replicate predictors for TRD among 16 clinical variables in 916 patients. Elastic net regression was applied for prediction of treatment outcome.
Results:
Symptom severity (odds ratio (OR) = 3.31), psychotic symptoms (OR = 2.52), suicidal risk (OR = 1.74), generalized anxiety disorder (OR = 1.68), inpatient status (OR = 1.65), higher number of antidepressants administered previously (OR = 1.23), and lifetime depressive episodes (OR = 1.15) as well as longer duration of the current episode (OR = 1.022) increased the risk of TRD. Prediction of TRD reached an accuracy of 0.86 in the independent validation set, TRD-I.
Conclusion:
Symptom severity, suicidal risk, higher number of lifetime depressive episodes, and comorbid anxiety disorder were replicated as the most prominent risk factors for TRD. Significant predictors in TRD-III enabled robust prediction of treatment outcome in TRD-I.
More Related Videos
04:29Vagus Nerve Stimulation As an Adjunctive Neurostimulation Tool in Treatment-resistant Depression
Published on: January 7, 2019
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Related Concept Videos
Treatment Resistant Cancers
Long-term Depression
Long-term Depression
Calcium Ion Concentration Mechanism
If over...
Freezing Point Depression and Boiling Point Elevation
The boiling point of a liquid is the temperature at which its vapor pressure is equal to ambient atmospheric pressure. Since the vapor pressure of a solution is lowered due to the presence of nonvolatile solutes, it stands to reason that the solution’s boiling point will subsequently be increased. Vapor pressure increases with temperature, and so a solution will require a higher temperature than will pure solvent to achieve any given vapor pressure, including one...
Depressants
Alcohol is a common depressant that can induce a sense of relaxation and reduced inhibition at low doses. Contrary to its occasional...
Electrolytes: van't Hoff Factor
The colligative properties of a solution depend only on the number, not on the identity, of solute species dissolved. The concentration terms in the equations for various colligative properties (freezing point depression, boiling point elevation, osmotic pressure) pertain to all solute species present in the solution. Nonelectrolytes dissolve physically without dissociation or any other accompanying process. Each molecule that dissolves yields one...