Literature DB >> 22901834

The diagnosis of depression: current and emerging methods.

Katie M Smith1, Perry F Renshaw, John Bilello.   

Abstract

Depression is one of the leading causes of disability in adolescents and adults, particularly starting from age 15 years and older. Diagnosis of depression has traditionally been made based on clinical criteria, including patient current symptoms and history. This process is widely used but relies on subjective interpretation. To standardize both the data obtained and data interpretation, various interview-based instruments and noninterview methods exist for screening and testing for depression in various clinical settings. This article evaluates the technical basis for and clinical performance of these various instruments and methods to diagnosis depression in clinical settings. Traditional tools include physician-administered or patient self-administered interview tools that have reasonable clinical accuracy depending on the threshold score and may lead to a full diagnostic evaluation for high-risk patients. In addition, older laboratory methods such as the dexamethasone test have contributed to the diagnosis of depression over a long period. Newer diagnostic methods such as genomics, proteomics, and metabolomics are technically sophisticated and objective and are beginning to emerge in psychiatry. Although promising, further evaluation of these methods is needed to fully demonstrate their clinical value and accuracy.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22901834      PMCID: PMC5502713          DOI: 10.1016/j.comppsych.2012.06.006

Source DB:  PubMed          Journal:  Compr Psychiatry        ISSN: 0010-440X            Impact factor:   3.735


  33 in total

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2.  2-D DIGE analysis of liver and red blood cells provides further evidence for oxidative stress in schizophrenia.

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Journal:  J Proteome Res       Date:  2007-01       Impact factor: 4.466

3.  Stimulated gene expression profiles as a blood marker of major depressive disorder.

Authors:  Sabine Spijker; Jeroen S Van Zanten; Simone De Jong; Brenda W J H Penninx; Richard van Dyck; Frans G Zitman; Jan H Smit; Bauke Ylstra; August B Smit; Witte J G Hoogendijk
Journal:  Biol Psychiatry       Date:  2010-05-14       Impact factor: 13.382

Review 4.  Endocrine disturbances in depression.

Authors:  M A Tichomirowa; M E Keck; H J Schneider; M Paez-Pereda; U Renner; F Holsboer; G K Stalla
Journal:  J Endocrinol Invest       Date:  2005-01       Impact factor: 4.256

5.  Assessment of a multi-assay, serum-based biological diagnostic test for major depressive disorder: a pilot and replication study.

Authors:  G I Papakostas; R C Shelton; G Kinrys; M E Henry; B R Bakow; S H Lipkin; B Pi; L Thurmond; J A Bilello
Journal:  Mol Psychiatry       Date:  2011-12-13       Impact factor: 15.992

6.  Identification of glyoxalase-I as a protein marker in a mouse model of extremes in trait anxiety.

Authors:  Simone A Krömer; Melanie S Kessler; Dale Milfay; Isabel N Birg; Mirjam Bunck; Ludwig Czibere; Markus Panhuysen; Benno Pütz; Jan M Deussing; Florian Holsboer; Rainer Landgraf; Christoph W Turck
Journal:  J Neurosci       Date:  2005-04-27       Impact factor: 6.167

Review 7.  Major depressive disorder in older adolescents: prevalence, risk factors, and clinical implications.

Authors:  P M Lewinsohn; P Rohde; J R Seeley
Journal:  Clin Psychol Rev       Date:  1998-11

Review 8.  The molecular neurobiology of depression.

Authors:  Richard C Shelton
Journal:  Psychiatr Clin North Am       Date:  2007-03

9.  A detailed examination of cytokine abnormalities in Major Depressive Disorder.

Authors:  N M Simon; K McNamara; C W Chow; R S Maser; G I Papakostas; M H Pollack; A A Nierenberg; M Fava; K K Wong
Journal:  Eur Neuropsychopharmacol       Date:  2007-08-03       Impact factor: 4.600

10.  Revisiting the Dexamethasone Suppression Test in unipolar major depression: an exploratory study.

Authors:  Konstantinos N Fountoulakis; Xenia Gonda; Zoltan Rihmer; Costas Fokas; Apostolos Iacovides
Journal:  Ann Gen Psychiatry       Date:  2008-11-13       Impact factor: 3.455

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  8 in total

1.  Depression in Sub-Saharan Africa.

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Journal:  IBRO Neurosci Rep       Date:  2022-03-17

2.  BNCPL: Brain-Network-based Convolutional Prototype Learning for Discriminating Depressive Disorders.

Authors:  Dongmei Zhi; Vince D Calhoun; Chuanyue Wang; Xianbin Li; Xiaohong Ma; Luxian Lv; Weizheng Yan; Dongren Yao; Shile Qi; Rongtao Jiang; Jianlong Zhao; Xiao Yang; Zheng Lin; Yujin Zhang; Young Chul Chung; Chuanjun Zhuo; Jing Sui
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2021-11

3.  Reduced cerebrospinal fluid ethanolamine concentration in major depressive disorder.

Authors:  Shintaro Ogawa; Kotaro Hattori; Daimei Sasayama; Yuki Yokota; Ryo Matsumura; Junko Matsuo; Miho Ota; Hiroaki Hori; Toshiya Teraishi; Sumiko Yoshida; Takamasa Noda; Yoshiaki Ohashi; Hajime Sato; Teruhiko Higuchi; Nobutaka Motohashi; Hiroshi Kunugi
Journal:  Sci Rep       Date:  2015-01-15       Impact factor: 4.379

4.  Psychosocial, physical, and autonomic correlates of depression in korean adults: results from a county-based depression screening study.

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Journal:  Psychiatry Investig       Date:  2014-10-20       Impact factor: 2.505

Review 5.  Mass spectrometry for the detection of potential psychiatric biomarkers.

Authors:  Armand G Ngounou Wetie; Izabela Sokolowska; Kelly Wormwood; Katherine Beglinger; Tanja Maria Michel; Johannes Thome; Costel C Darie; Alisa G Woods
Journal:  J Mol Psychiatry       Date:  2013-06-05

6.  WaaS architecture-driven depressive mood status quantitative analysis based on forehead EEG and self-rating tool.

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Journal:  Brain Inform       Date:  2018-12-05

7.  Lysophosphatidic acid levels in cerebrospinal fluid and plasma samples in patients with major depressive disorder.

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Journal:  Heliyon       Date:  2019-05-16

8.  Deep-Asymmetry: Asymmetry Matrix Image for Deep Learning Method in Pre-Screening Depression.

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Journal:  Sensors (Basel)       Date:  2020-11-15       Impact factor: 3.576

  8 in total

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