Literature DB >> 20141703

Treating major depression: antidepressant algorithms.

Michael E Thase1.   

Abstract

Clinicians currently have a large number of pharmaceutical options available for the treatment of depression, yet not one of these treatments is associated with especially high remission rates. Further complicating the treatment of depression is the fact that the more failed treatment trials a patient undergoes, the lower the odds that remission will be achieved. Therefore, choosing the drug that will be most effective for a particular patient early in the treatment process is essential. Antidepressant treatment algorithms are helpful in this regard. Copyright 2009 Physicians Postgraduate Press, Inc.

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Year:  2009        PMID: 20141703     DOI: 10.4088/JCP.8001tx11c

Source DB:  PubMed          Journal:  J Clin Psychiatry        ISSN: 0160-6689            Impact factor:   4.384


  2 in total

1.  Pharmacological experimental study of the anti-depressant effect of total saikosaponins.

Authors:  Yu Liu; Chunmei Cao; Haijun Ding
Journal:  Afr J Tradit Complement Altern Med       Date:  2014-01-28

2.  AMPA receptor-mTORC1 signaling activation is required for neuroplastic effects of LY341495 in rat hippocampal neurons.

Authors:  Mi Kyoung Seo; Le Thi Hien; Min Kyung Park; Ah Jeong Choi; Dae-Hyun Seog; Seong-Ho Kim; Sung Woo Park; Jung Goo Lee
Journal:  Sci Rep       Date:  2020-01-22       Impact factor: 4.379

  2 in total

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