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Long-Term Effects of the Treatment of Depressive Female Inpatients in a Naturalistic Study: Is Early Improvement a Valid Predictor of Outcome?

Objectives. To examine the predictive value of early improvement for short- and long-term outcome in the treatment of depressive female inpatients and to explore the influence of comorbid disorders (CD). Methods. Archival data of a naturalistic sample of 277 female inpatients diagnosed with a depres...

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Detalles Bibliográficos
Autores principales: Zuercher-Huerlimann, Elian, grosse Holtforth, Martin, Hermann, Ernst
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4100258/
https://www.ncbi.nlm.nih.gov/pubmed/25061526
http://dx.doi.org/10.1155/2014/780237
Descripción
Sumario:Objectives. To examine the predictive value of early improvement for short- and long-term outcome in the treatment of depressive female inpatients and to explore the influence of comorbid disorders (CD). Methods. Archival data of a naturalistic sample of 277 female inpatients diagnosed with a depressive disorder was analyzed assessing the BDI at baseline, after 20 days and 30 days, posttreatment, and after 3 to 6 months at follow-up. Early improvement, defined as a decrease in the BDI score of at least 30% after 20 and after 30 days, and CD were analyzed using binary logistic regression. Results. Both early improvement definitions were predictive of remission at posttreatment. Early improvement after 30 days showed a sustained treatment effect in the follow-up phase, whereas early improvement after 20 days failed to show a persistent effect regarding remission at follow-up. CD were not significantly related neither at posttreatment nor at follow-up. At no time point CD moderated the prediction by early improvement. Conclusions. We show that early improvement is a valid predictor for short-term remission and at follow-up in an inpatient setting. CD did not predict outcome. Further studies are needed to identify patient subgroups amenable to more tailored treatments.