- 作者：V¨ªctor Navarro ; Alex ; re Gonz¨¢lez ; Joana Guarch ; Rafael Penad¨¦s ; Merc¨¨ Torra ; Lourdes Fa?an¨¢s ; B¨¢rbara Arias ; Montserrat Serra ; Luis Pintor ; Crist¨®bal Gast¨®
- 关键词：Unipolar depression ; Remission ; Outcome predictors ; Clinical characteristics
- 刊名：Journal of Affective Disorders
- 出版年：2013
- 出版时间：5 September, 2013
- 年：2013
- 卷：150
- 期：2
- 页码：209-215
- 全文大小：398 K
Background
To evaluate, in patients affected by an acute major depressive episode, what predictive value certain baseline psychopathological characteristics have with regard to expected therapeutic remission following biological antidepressant treatment (pharmacological/electroconvulsive; non-psychological).Methods
Six predefined psychopathological characteristics in acute major depressive episode were evaluated using a logistic regression model through a protocolised antidepressant treatment to assess their predictive value with regard to expected remission rate.
Results
The final study sample consisted of 129 subjects affected by an acute major depressive episode. From the baseline evaluation of the anguish/restlessness, reduced emotional reactivity, reduced attention, reduced motor response, feeling of worthlessness, and mood characteristics items, it was possible to correctly classify 88.1 % of the sample as remitter/non-remitter with sensitivity of 0.77 and specificity of 0.96. Addition of the 17-item HRSD baseline variable to the regression model increased the capacity for correct classification of the baseline sample by only 0.09 % .
Limitations
Protocolised antidepressant treatment was used. The results of this study may not be generalisable to pharmacological treatments not included in this protocol.
Conclusions
The results of this study suggest that certain baseline psychopathological characteristics (and perhaps other clinical variables too) of the acute major depressive episode may be of great use in establishing patient subgroups according to expected clinical remission to the administration of biological antidepressant treatment. This could have considerable consequences for individualised therapeutic decision-making and for future researches (clinical trials included).