Validation of a treatment algorithm for major depression in an older Brazilian sample.


Journal Article

OBJECTIVE: The aim of this study was to investigate the effectiveness of a modified version of the Duke Somatic Algorithm Treatment for Geriatric Depression (STAGED) in a Brazilian sample of older patients with major depression. Besides, we aimed to investigate possible baseline predictive factors for remission in this sample. METHODS: Sixty-seven depressed individuals were treated according to STAGED over 24 weeks in a prospective cohort design with follow-up. All patients had criteria for major depression and were at least 60 years of age at baseline enrollment. RESULTS: During this follow-up, 56 patients could be classified in remitted or not remitted group, 42.85% reached remission, and 57.14% did not reach remission. These results are even better than those found in the original study, probably due to the lower baseline depression severity of our sample. When baseline characteristics were compared between remitted and not remitted groups, scores of Mini Mental State Examination and Cambridge Cognitive Examination (CAMCOG) were the only variables with statistical significant difference (p < 0.05) between groups. Logistic regression analysis was carried out to try to predict remission and statistical significance (p < 0.05) was found only for baseline MMSE scores. It may mean that patients with mixed cognitive disorders and mood disorders have a worse course of depression. CONCLUSIONS: This version of STAGED seems to be a useful strategy for treatment of depression in late life. Baseline general cognitive performance might be useful to predict remission of depression in older patients with mild to moderate depression. Further research with different population characteristics should be conducted in order to evaluate its usefulness and feasibility in different settings.

Full Text

Duke Authors

Cited Authors

  • Ribeiz, SRI; Ávila, R; Martins, CB; Moscoso, MAA; Steffens, DC; Bottino, CMC

Published Date

  • June 2013

Published In

Volume / Issue

  • 28 / 6

Start / End Page

  • 647 - 653

PubMed ID

  • 23015472

Pubmed Central ID

  • 23015472

Electronic International Standard Serial Number (EISSN)

  • 1099-1166

Digital Object Identifier (DOI)

  • 10.1002/gps.3876


  • eng

Conference Location

  • England