Literature DB >> 20964944

Clinical factors that predict cognitive function in patients with major depression.

Safa Elgamal1, Susan Denburg, Michael Marriott, Glenda MacQueen.   

Abstract

OBJECTIVES: To compare the performance of depressed patients to healthy control subjects on discrete cognitive domains derived from factor analysis and to examine the factors that may influence the performance of depressed patients on cognitive domains in a large sample.
METHODS: We compared the cognitive performance of 149 patients with major depression to 104 healthy control subjects using multivariate ANCOVA. We used principal component factor analysis to group the cognitive variables into cognitive domains. Finally, we conducted regression analysis to examine the contribution of predictor factors to the cognitive domains that were impaired in the depressed group.
RESULTS: Verbal memory and speed of processing were impaired in depressed patients, compared with healthy control subjects. Patient IQ, duration of depressive illness, and number of hospitalizations significantly contributed to the performance of patients on verbal memory and speed of processing. The severity of mood symptoms did not correlate with performance on any cognitive domain.
CONCLUSIONS: Understanding the factors that predict cognitive performance of patients with depression may provide an insight into the processes by which depression leads to cognitive dysfunction. Our study showed that premorbid IQ and factors related to burden of illness are strong independent predictors of cognitive dysfunction in patients with major depression.

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Year:  2010        PMID: 20964944     DOI: 10.1177/070674371005501004

Source DB:  PubMed          Journal:  Can J Psychiatry        ISSN: 0706-7437            Impact factor:   4.356


  8 in total

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2.  Predictors of Long-Term Improvement Following Cognitive Remediation in a Sample With Elevated Depressive Symptoms.

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3.  Mediated and moderated effects of neurocognitive impairment on outcomes of treatment for substance dependence and major depression.

Authors:  Matthew J Worley; Susan R Tate; Eric Granholm; Sandra A Brown
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4.  Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression.

Authors:  M Papmeyer; J E Sussmann; J Hall; J McKirdy; A Peel; A Macdonald; S M Lawrie; H C Whalley; A M McIntosh
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Review 5.  A Systematic Review and Meta-Analysis of Cognitive Training in Adults with Major Depressive Disorder.

Authors:  C Woolf; A Lampit; Z Shahnawaz; J Sabates; L M Norrie; D Burke; S L Naismith; L Mowszowski
Journal:  Neuropsychol Rev       Date:  2021-04-28       Impact factor: 7.444

6.  Predictors of Cognitive Improvement during 12 Weeks of Antidepressant Treatment in Patients with Major Depressive Disorder.

Authors:  Jeong-Ok Lee; Ju-Wan Kim; Hee-Ju Kang; Jin-Pyo Hong; Jae-Min Kim
Journal:  Clin Psychopharmacol Neurosci       Date:  2018-11-30       Impact factor: 2.582

7.  Relationship between illness duration, corpus callosum changes, and sustained attention dysfunction in major depressive disorder.

Authors:  Wenming Zhao; Daomin Zhu; Yu Zhang; Cun Zhang; Biao Zhang; Ying Yang; Jiajia Zhu; Yongqiang Yu
Journal:  Quant Imaging Med Surg       Date:  2021-07

8.  Assessment of Attentional Processes in Patients with Anxiety-Depressive Disorders Using Virtual Reality.

Authors:  José A Camacho-Conde; Leire Legarra; Vanesa M Bolinches; Patricia Cano; Mónica Guasch; María Llanos-Torres; Vanessa Serret; Miguel Mejías; Gema Climent
Journal:  J Pers Med       Date:  2021-12-09
  8 in total

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