Literature DB >> 25305428

Risk factors for treatment resistance in unipolar depression: a systematic review.

D Bennabi1, B Aouizerate2, W El-Hage2, O Doumy2, F Moliere2, P Courtet2, I Nieto2, F Bellivier2, M Bubrovsky2, G Vaiva2, J Holztmann2, T Bougerol2, R Richieri2, C Lancon2, V Camus2, G Saba2, F Haesbaert2, T d'Amato2, T Charpeaud2, P M Llorca2, M Leboyer2, E Haffen2.   

Abstract

BACKGROUND: Treatment resistant depression is a complex disorder and an important source of morbidity and mortality. Identification of risk factors of resistance may be useful to improve early recognition as well as treatment selection and prediction of outcome in patients with depression.
METHODS: The aim of this paper was to review the current status of knowledge regarding risk factors of treatment resistance in unipolar depression, in patients who failed to respond to at least two successive and adequate antidepressant treatments.
RESULTS: Systematic literature search yielded 8 publications exploring clinical and biological factors. Specific psychiatric comorbidities, psychosocial factors, clinical characteristics of the depressive episode and biological markers emerge as possible risk factor for treatment resistant depression. LIMITATIONS: Due to the lack of objective definition and diagnostic criteria for treatment resistant depression, and the paucity of reports on risk factors, our review only summarized a small number of studies.
CONCLUSION: Future investigations of risk factors should help to improve the understanding of the mechanisms underlying resistance in mood disorders and contribute to improve their therapeutic management.
Copyright © 2014. Published by Elsevier B.V.

Entities:  

Keywords:  Treatment resistance-depression-risk factors

Mesh:

Substances:

Year:  2014        PMID: 25305428     DOI: 10.1016/j.jad.2014.09.020

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  42 in total

1.  Factor structure and longitudinal measurement invariance of PHQ-9 for specialist mental health care patients with persistent major depressive disorder: Exploratory Structural Equation Modelling.

Authors:  Boliang Guo; Catherine Kaylor-Hughes; Anne Garland; Neil Nixon; Tim Sweeney; Sandra Simpson; Tim Dalgleish; Rajini Ramana; Min Yang; Richard Morriss
Journal:  J Affect Disord       Date:  2017-05-08       Impact factor: 4.839

Review 2.  Apps for Depression: Are They Ready to Work?

Authors:  Alejandro Porras-Segovia; Isaac Díaz-Oliván; Luis Gutiérrez-Rojas; Henry Dunne; Manon Moreno; Enrique Baca-García
Journal:  Curr Psychiatry Rep       Date:  2020-02-05       Impact factor: 5.285

3.  A rest-activity biomarker to predict response to SSRIs in major depressive disorder.

Authors:  W Vaughn McCall
Journal:  J Psychiatr Res       Date:  2015-03-06       Impact factor: 4.791

4.  Collaborative care for depression symptoms in an outpatient cardiology setting: A randomized clinical trial.

Authors:  Robert M Carney; Kenneth E Freedland; Brian C Steinmeyer; Eugene H Rubin; Gregory Ewald
Journal:  Int J Cardiol       Date:  2016-06-14       Impact factor: 4.164

Review 5.  Antidepressant pharmacotherapy in old-age depression-a review and clinical approach.

Authors:  Nathalie Pruckner; Vjera Holthoff-Detto
Journal:  Eur J Clin Pharmacol       Date:  2017-03-10       Impact factor: 2.953

6.  Reward-Related Ventral Striatum Activity Buffers against the Experience of Depressive Symptoms Associated with Sleep Disturbances.

Authors:  Reut Avinun; Adam Nevo; Annchen R Knodt; Maxwell L Elliott; Spenser R Radtke; Bartholomew D Brigidi; Ahmad R Hariri
Journal:  J Neurosci       Date:  2017-09-18       Impact factor: 6.167

7.  Predicting treatment outcome in depression: an introduction into current concepts and challenges.

Authors:  Nicolas Rost; Elisabeth B Binder; Tanja M Brückl
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2022-05-19       Impact factor: 5.270

Review 8.  The Microbiota-Gut-Brain Axis in Depression: The Potential Pathophysiological Mechanisms and Microbiota Combined Antidepression Effect.

Authors:  Fangyuan Zhu; Huaijun Tu; Tingtao Chen
Journal:  Nutrients       Date:  2022-05-16       Impact factor: 6.706

9.  Using a machine learning approach to investigate factors associated with treatment-resistant depression among adults with chronic non-cancer pain conditions and major depressive disorder.

Authors:  Drishti Shah; Wanhong Zheng; Lindsay Allen; Wenhui Wei; Traci LeMasters; Suresh Madhavan; Usha Sambamoorthi
Journal:  Curr Med Res Opin       Date:  2021-03-24       Impact factor: 2.580

10.  Predictors of Response to Web-Based Cognitive Behavioral Therapy With High-Intensity Face-to-Face Therapist Guidance for Depression: A Bayesian Analysis.

Authors:  Ragnhild Sørensen Høifødt; Matthias Mittner; Kjersti Lillevoll; Susanne Kvam Katla; Nils Kolstrup; Martin Eisemann; Oddgeir Friborg; Knut Waterloo
Journal:  J Med Internet Res       Date:  2015-09-02       Impact factor: 5.428

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