Literature DB >> 19798766

Major depression: the importance of clinical characteristics and treatment response to prognosis.

Wayne Katon1, Jürgen Unützer, Joan Russo.   

Abstract

BACKGROUND: This article analyzed data from the intervention arm of a large treatment trial to demonstrate the importance of clinical severity, course, comorbidity, and treatment response in patient prognosis.
METHODS: This is a secondary analysis of data from a large primary care-based geriatric depression treatment trial that analyzes outcomes from the measurement-based stepped-care intervention arm (N=871 patients) to determine: whether increasing severity levels of depression at baseline were linked with other factors associated with poor depression outcomes such as double depression, anxiety, medical disorders, and high levels of neuroticism and pain; and whether patients with increasing levels of depressive severity would have more intervention visits and treatment trials based on a stepped-care algorithm, but would be less likely to reach remission and have a greater likelihood of re-emerging depression in the year after intervention.
RESULTS: Increasing levels of depression severity were a robust predictor of lack of remission and were associated with other clinical variables that have been associated with lack of remission in earlier studies such as double depression, anxiety, medical comorbidity, high neuroticism levels, and chronic pain. Patients with higher levels of severity received significantly more intervention visits, more months of antidepressant treatment and more antidepressant trials, but had fewer depression-free days during the 12-month intervention and in the postintervention year.
CONCLUSION: Patients with higher levels of depression severity had worse clinical outcomes despite receiving greater intensity of treatment. A new classification of depression is proposed based on clinical severity, course of illness and treatment experience.

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Year:  2010        PMID: 19798766     DOI: 10.1002/da.20613

Source DB:  PubMed          Journal:  Depress Anxiety        ISSN: 1091-4269            Impact factor:   6.505


  32 in total

1.  Magnetic resonance imaging predictors of treatment response in late-life depression.

Authors:  Howard J Aizenstein; Alexander Khalaf; Sarah E Walker; Carmen Andreescu
Journal:  J Geriatr Psychiatry Neurol       Date:  2013-12-30       Impact factor: 2.680

2.  Are patient characteristics associated with quality of depression care and outcomes in collaborative care programs for depression?

Authors:  Amy M Bauer; Vanessa Azzone; Laurie Alexander; Howard H Goldman; Jürgen Unützer; Richard G Frank
Journal:  Gen Hosp Psychiatry       Date:  2011-10-21       Impact factor: 3.238

3.  Implementation of collaborative depression management at community-based primary care clinics: an evaluation.

Authors:  Amy M Bauer; Vanessa Azzone; Howard H Goldman; Laurie Alexander; Jürgen Unützer; Brenda Coleman-Beattie; Richard G Frank
Journal:  Psychiatr Serv       Date:  2011-09       Impact factor: 3.084

4.  An Evaluation of IMPACT for the Treatment of Late-Life Depression in a Public Mental Health System.

Authors:  Michael J Penkunas; Stephen Hahn-Smith
Journal:  J Behav Health Serv Res       Date:  2015-07       Impact factor: 1.505

5.  The severity of psychiatric disorders.

Authors:  Mark Zimmerman; Theresa A Morgan; Kasey Stanton
Journal:  World Psychiatry       Date:  2018-10       Impact factor: 49.548

6.  Self-rated health and long-term prognosis of depression.

Authors:  Gilles Ambresin; Patty Chondros; Christopher Dowrick; Helen Herrman; Jane M Gunn
Journal:  Ann Fam Med       Date:  2014 Jan-Feb       Impact factor: 5.166

7.  Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

Authors:  Meenal J Patel; Carmen Andreescu; Julie C Price; Kathryn L Edelman; Charles F Reynolds; Howard J Aizenstein
Journal:  Int J Geriatr Psychiatry       Date:  2015-02-17       Impact factor: 3.485

8.  General and comparative efficacy and effectiveness of antidepressants in the acute treatment of depressive disorders: a report by the WPA section of pharmacopsychiatry.

Authors:  Thomas C Baghai; Pierre Blier; David S Baldwin; Michael Bauer; Guy M Goodwin; Kostas N Fountoulakis; Siegfried Kasper; Brian E Leonard; Ulrik F Malt; Dan Stein; Marcio Versiani; Hans-Jürgen Möller
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2011-11       Impact factor: 5.270

9.  Resilience predicts remission in antidepressant treatment of geriatric depression.

Authors:  Kelsey T Laird; Helen Lavretsky; Natalie St Cyr; Prabha Siddarth
Journal:  Int J Geriatr Psychiatry       Date:  2018-07-23       Impact factor: 3.485

10.  Examining the relationship between depression and asthma exacerbations in a prospective follow-up study.

Authors:  Brian K Ahmedani; Edward L Peterson; Karen E Wells; L Keoki Williams
Journal:  Psychosom Med       Date:  2013-02-25       Impact factor: 4.312

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