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 Table of Contents  
ORIGINAL ARTICLE
Year : 2018  |  Volume : 39  |  Issue : 2  |  Page : 66-72

Cognitive dysfunction profile in a sample of Egyptian patients experiencing major depressive disorder


Department of Neurology and Psychiatry, Faculty of Medicine, Alexandria University, Alexandria, Egypt

Date of Submission07-Sep-2017
Date of Acceptance31-Oct-2017
Date of Web Publication2-May-2018

Correspondence Address:
Hesham A Sheshtawy
Department of Neurology and Psychiatry, Faculty of Medicine, Alexandria University, Alexandria, 21525
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ejpsy.ejpsy_28_17

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  Abstract 


Aim The aim was to study the profile of cognitive dysfunction in a sample of Egyptian patients experiencing major depressive disorder (MDD), during the relapse phase.
Patients and methods Certain cognitive functions (types of attention, short-term memory, processing speed, verbal fluency, and executive functions) were assessed in 30 Egyptian patients diagnosed as having MDD compared with 30 controls.
Results There was no statistically significant difference between MDD group and control group regarding scores of digit forward test. Patients’ mean scores of digit backward test, digit symbol test, and semantic fluency test were significantly lesser than the control group’s mean scores of the same tests. On the contrary, patients’ mean scores of trail making test (A and B) were greater significantly than control group’s mean scores of the same tests.
Age, duration of education, age at illness onset, number of hospitalizations, and Hamilton score were significantly correlated with impairment of some areas of cognitive functions. Sex, employment, duration of illness, number of previous episodes, and receiving antidepressant medications were not related or correlated with cognitive dysfunction. Increase severity of illness, detected by high Hamilton score, and to a lesser extent, number of hospitalization and duration of education were significant independent predictors for poor performance of the tested cognitive fuctions.
Conclusion Selective attention, divided attention, short-term memory, processing speed, verbal fluency, and executive functions are significantly affected in MDD. This can explain the patients’ clinical complaints of difficulty in concentration, easy forgetfulness, and impaired decision making. On the contrary, sustained attention is not affected in patients with MDD. Therefore, the ruminated negative thoughts and memories are manifest complaints in these patients.
Severity of illness is the most important predictive factor for discovering cognitive dysfunction symptoms in patients with MDD. Age and age of illness onset are positively correlated with poor cognitive performance; however, they are dependent predictors.

Keywords: cognitive dysfunction profile, Egyptian patients, major depressive disorder, predictors


How to cite this article:
Abdel Aal MK, Molokhia TK, El Kholy OA, Sheshtawy HA. Cognitive dysfunction profile in a sample of Egyptian patients experiencing major depressive disorder. Egypt J Psychiatr 2018;39:66-72

How to cite this URL:
Abdel Aal MK, Molokhia TK, El Kholy OA, Sheshtawy HA. Cognitive dysfunction profile in a sample of Egyptian patients experiencing major depressive disorder. Egypt J Psychiatr [serial online] 2018 [cited 2018 Nov 18];39:66-72. Available from: http://new.ejpsy.eg.net/text.asp?2018/39/2/66/231698




  Introduction Top


Major depressive disorder (MDD) is a prevalent illness. One of the characteristics of MDD is that it has a relapsing remitting course in most of the patients. Overall, 10–30% of the patients can have an incomplete recovery, with persistent symptoms or dysthymia (Solomon et al., 2000).

Cognitive symptoms are prevalent in MDD. They are increasingly recognized to be important clinical dimensions in MDD (Chakrabarty et al., 2016). They are present in 85–94% of the length of depressive episodes and 39–44% of the length of periods of remission (Mann, 2005; Conradi et al., 2011). Cognitive functions play an important role in functional recovery. What are cognitive functions mostly affected in MDD?


  Aim Top


This work aims at studying the profile of cognitive dysfunction in a sample of Egyptian patients experiencing MDD, during the relapse phase.


  Patients and methods Top


A total of 60 patients were recruited from El-Hadara University Hospital psychiatric wards and outpatient neuropsychiatric clinic in main Alexandria University Hospital in the period from March 2015 to January 2016 (after taking a written consent to participate in the study). They were divided into two groups:
  1. Group I included 30 patients with MDD during relapse phase according to Diagnostic and Statistical Manual of Mental Disorders Text Revision (DSM IV TR) criteria (American Psychiatric Association, 2000).
  2. Group II included 30 healthy controls matched for age, sex, and education.


The sample was collected randomly with the following inclusion and exclusion criteria.

Inclusion criteria

The following were the inclusion criteria:
  1. Age: 18–50 years.
  2. Both sexes.
  3. Informed and written consent of all the participants in the study.


Exclusion criteria

The following were the exclusion criteria:
  1. Refusal to participate in the study.
  2. Other psychiatric disorders, e.g. comorbid substance-use disorder and anxiety disorder.
  3. Mental retardation or significant cognitive impairment.
  4. History of head trauma.
  5. History of substance dependence in the past year.
  6. History of electroconvulsive therapy in the past year.
  7. Chronic physical or neurological debilitating disorders especially those affecting cognition, e.g. endocrine disorders and Parkinson’s disease.


The following was done for the patients and control groups:
  1. A predesigned structured interview questionnaire was used to collect the following data:
    1. Sociodemographic data such as age, sex, residence, educational level, marital status, and occupation and income.
    2. Medical and psychiatric history.
    3. Family history of psychiatric illness and substance use.
  2. Clinical evaluation.
    • Thorough psychiatric examination was done for both groups using semistructured interview using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM IV TR) criteria for diagnosis of MDD (American Psychiatric Association, 2000).
  3. Hamilton depression rating-17-item version (Hamilton, 1967).
  4. Cognitive function assessment will be done using the following psychometric tests:
    1. Digit span test (Brebionet al., 2009; Koenigset al., 2009; Naismithet al., 2010).
      • The forward digit span tests are used to measure short-term memory and general attention. The backward digit span tests are used to measure verbal working memory.
    2. Digit symbol test (Brebionet al., 2009; Naismithet al., 2010).
      • It was used for examination of short-term memory and processing speed.
  5. Semantic verbal fluency test: animal naming (Chenet al., 2000).
    • It was used for examination of verbal fluency, short-term memory, and information processing speed.
  6. Trail making test (A and B) (Reitan, 1955).
    • It was used for examination of selective and divided attention.


Statistical analysis (Kotz et al., 2006)

were fed to the computer and analyzed using IBM SPSS software package version 20.0 (SPSS Inc., Chicago, Illinois, USA) (Kirkpatrick and Feeney, 2013). Qualitative data were described using number and percentage. Quantitative data were described using range (minimum and maximum), mean, SD, and median. Comparison between different groups regarding categorical variables was tested using χ2-test. When more than 20% of the cells have expected count less than 5, correction for χ2 was conducted using Fisher’s exact test or Monte Carlo correction. The distributions of quantitative variables were tested for normality using Kolmogorov–Smirnov test, Shapiro–Wilk test, and D’Agstino test; moreover, histogram and quantile–quantile plot were used for vision test. If normal data distribution is revealed, parametric tests were applied. If the data were abnormally distributed, nonparametric tests were used. For normally distributed data, comparisons between the two studied groups were analyzed using Student’s t-test. For abnormally distributed data, comparisons between two independent populations were done using Mann–Whitney test, whereas Kruskal–Wallis test was used to compare between different groups, and pairwise comparison was assessed using Mann–Whitney test. Correlations between two quantitative variables were assessed using Pearson’s or Spearman’s coefficients regarding normality of the data. Multivariate liner regression was assessed. Significance of the obtained results was judged at the 5% level.


  Results Top


  1. The demographic characteristics, clinical characteristics, and psychometric results are present in [Table 1],[Table 2],[Table 3].
    • Psychotic features (either present currently or previously) were not detected in the studied patients.
    • Regarding the digit forward test, there was no statistically significant difference between the major depression patients’ group (6.17±1.18) and control group (6.87±0.90) (P=0.072). Regarding the digit backward test, the mean of patients’ group (5.40±1.16) was significantly lesser than that of control group (6.20±0.89) (P=0.032). Moreover, the mean of digit symbol test for patients’ group (37.17±9.90) was significantly lesser than that of control group (47.33±7.35) (P<0.001). Regarding verbal fluency test, the mean of the patients’ group (13.17±2.57) was significantly lesser than that of control group (15.33±1.79) (P<0.001). On the contrary, the means of trail making test A and B for patients’ group (55.17±17.59 and 121.20±24.52, respectively) were significantly greater than that of control group (40.53±15.50 and 106.53±26.11, respectively) (P=0.002 and 0.36, respectively)
    Table 1 The demographic characteristics of patients with major depression and the control groups

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    Table 2 Clinical characteristics

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    Table 3 Psychometric results

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  2. Correlations between studied cognitive functions and demographic characteristics, clinical characteristics, and Hamilton score:
    • Regarding age, there was a statistically significant negative correlation between performance on the verbal fluency test and age (r=−0.421, P=0.020). On the contrary, there was a statistically significant positive correlation between performance on trail making A test and age (r=0.391, P=0.033).
    • Regarding duration of education, there was a statistically significant negative correlation between duration of education and performance on trail making B (r=−0.436, P=0.016).
    • There was no statistically significant relation between sex and employment and different studied cognitive functions.
    • Regarding age at illness onset, there was a statistically significant negative correlation between age at illness onset and digit span backward (r=−0.413, P=0.023) and the verbal fluency test (r=−0.370, P=0.044).
    • Regarding number of hospitalizations, there was a statistically significant negative correlation between number of hospitalizations and performance on the verbal fluency test (r=−0.493, P=0.006), whereas there was a statistically significant positive correlation between number of hospitalizations and performance on the trail making A (r=0.422, P=0.020).
    • There was no statistically significant correlation between duration of illness, number of previous episodes, and receiving antidepressant medications and performance on studied cognitive functions.
    • Regarding Hamilton score, there was a statistically significant negative correlation between Hamilton score and performance on digit span forward (r=−0.573, P>0.001), digit span backward (r=−0.638, P>0.001), the digit symbol substitution test (DSST) (r=−0.456, P>0.001), and the verbal fluency test (r=−0.470, P>0.001) whereas there was a statistically significant positive correlation between number Hamilton score and performance on the trail making A (r=0.489, P>0.001) and trail making B (r=0.567, P>0.001).
  3. Linear regression of different studied variables shows the following:
    1. Digit span forward: Hamilton score (t=3.702*, P=0.001) was only significant predictor for poor performance.
    2. Digit span backward: Hamilton score (t=3.447*, P=0.002) was only significant predictor for poor performance.
    3. Digit symbol test: Hamilton score (t=2.116*, P=0.044) was only significant predictor for poor performance.
    4. Verbal fluency test: Hamilton score (t=2.575*, P=0.016) was only significant predictor for poor performance.
    5. Trail making A test: number of hospitalizations (t=2.583*, P=0.016) and Hamilton score (t=2.640*, P=0.014) were significant predictors for poor performance.
    6. Trail making B test: duration of education (t=2.564*, P=0.016) was only significant predictor for poor performance.



  Discussion Top


Cognitive function of major depression patients’ group showed significantly poorer performance than that of control group regarding working memory assessed using the backward digit span (P=0.032), processing speed assessed using the digit symbol test (P<0.001) and trail making A (P=0.002), verbal fluency assessed using verbal fluency (animal naming) test (P=0.014), executive functions assessed using trail making B (P=0.036), and verbal fluency (P=0.014). On the contrary, no significant impairment was seen regarding attention and short-term memory assessed using forward digit span.

These findings can give us an idea that sustained attention is not markedly affected in patients with MDD. On the contrary, selective attention, divided attention, short-term memory, processing speed, and executive functions are the responsible domains behind the clinical complaints of the patients. Therefore, patients with MDD can ruminate bad thoughts for a prolonged period, as their sustained attention is not affected. When trying to pay attention to another topics, other than ruminated thoughts, patients with MDD can experience marked difficulty, as divided attention and selective attention as well as other cognitive domains are truly affected. Moreover, the affected cognitive domains can explain the patients’ clinical complaints of difficulty in concentration, easy forgetfulness, and impaired decision making.

Sarhan et al. (2015) studied cognitive impairment in 50 undergraduate depressed patients in Cairo University in comparison with 50 nondepressed students. They found that depressed University students experience cognitive impairment more than their nondepressed colleagues (Sarhan et al., 2015). This was in agreement with the results of the current study.

Moreover, in agreement with the results of the current study, Stordal et al. (2004) studied 45 patients with moderate to severe recurrent MDD in comparison with 50 healthy controls. The participants were administered a set of neuropsychological tests that assesses subcomponents of executive functions like verbal fluency test, digit span backward, and Wisconsin card sorting test. The results were consistent with the current study where depressed patients show mild impairment across a wide range of executive functions like working memory and verbal fluency.

Furthermore, Austin et al. (1992) studied several domains of cognitive function in 40 patients with major depression compared with 30 healthy participants matched for age and education. The study showed that the patient groups had neuropsychological impairment regarding processing speed assessed by the digit symbol test and executive functions assessed by trial making test in comparison with the healthy participants, which was consistent with the current study.

In partial agreement with the present study, Porter et al. (2003) studied 44 drug-free patients with major depression compared with 44 matched healthy control. The participants were administrated a set of neuropsychological tests that assessed attention and processing speed and executive functions. The study showed significant cognitive disturbance in attention and executive functions. In contrast to the present study, they showed nonsignificant cognitive disturbance in processing speed. The difference may be because of different sample size, state of illness, and or medication used.

Age was significantly negatively correlated with verbal fluency test, and significantly positively correlated with trail making A test. This may denote that the older the age of the patient, the worst the performance in semantic naming and selective attention.

Duration of education showed significant negative correlations with trail making B. This may denote that duration of education has a protective effect on executive functions.

Age at illness onset had significant negative correlation with their performance on the backward digit span and verbal fluency test. This may denote that the older the age at illness onset, the worst the performance of short-term memory and semantic naming.

Inconsistent with the current study results, Grant et al. (2001) studied cognitive functions in 123 patients with MDD without psychotic features and found that there is a significant correlation between age at illness onset and performance on neuropsychological tests measuring attention and psychomotor speed and executive functions.

The number of previous hospitalizations of patients with major depression showed significant negative correlations with the verbal fluency test. On the contrary, there was a postive correlation between number of previous hosptilization of patients with major depression and trail making test A.

Regarding severity of illness rated by Hamilton depression rating, there was a significant negative correlation between peroformance of patients with major depression on forward digit span, backward digit span, the digit symbol test, the verbal fluency test, and Hamilton score. On the contrary, there was a significant positive correlation between performance of patients with major depression on trail making test A and hamilton score. This means that the more the depression is severe, the more the cognition is dysfunctioned.

Consistent with current study results, Ravnkilde et al. (2002) who studied cognitive functions in 40 severely depressed hospitalized patients found that there is significant correlation between Hamilton score and trail making either A or B test and digit symbol subtest of Wechsler Adult Intelligence Scale –Revised (WAIS-R).

In consistent with the current study results, Naismith et al. (2003) found that increasing severity of depression, as measured by the Hamilton, was associated with significantly lower scores for semantic fluency.

Regarding antidepressant used and cognitive function, there was no significant correlation between performance of patients with major depression on different cognitive psychometric tests and antidepressant used.

In consistent with current study results, Ravnkilde et al. (2002) who studied cognitive functions in 40 severely depressed hospitalized patients found that that there is no significant difference between depressed patients who received antidepressant and depressed patients who did not receive antidepressant (Grant et al., 2001).

So, collectively, the current study showed that age, duration of education, age at illness onset, number of hospitalizations, and Hamilton score were significantly correlated with impairment of some areas of cognitive functions. On the contrary, sex, employment, duration of illness, number of previous episodes, and receiving antidepressant medications were not related or correlated with cognitive dysfunction.

Linear regression analysis of different studied variables was done to identify the independent factors affecting cognitive dysfunction. Hamilton score was the significant predictor of poor performance in forward digit span, backward digit span, the digit symbol test, the verbal fluency test, and trail making A. Education was a signifcant predictor of performance on trial making B test. Number of hosptilization was significant predictor of performance on trail making A test.

This means that the current study supports that severity of illness is the most important predictive factor for discovering cognitive dysfunction symptoms in patients with MDD. Sarhan et al. (2015) and Papazacharios and Nardini (2012) found different results in their studies. They found that there was no correlation between severity of illness and tested cognitive functions. The difference can be related to the type of tested cognitive functions. Cognitve functions can be ‘hot, i.e. affective laden’ or ‘cold, i.e. nonaffective laden’ (Gonda et al., 2015). Mostly, testedcognitive functions by Sarhan et al. (2015), Naismith et al. (2003), and Papazacharios and Nardini (2012) were ‘cold’. Therefore, cognitive dysfuction was not correlated with severity of depression. The current study tested ‘hot’ cognition. Therefore, cognitive dysfunction was correlated with severity of depression.


  Conclusion Top


  1. Patients experiencing MDD have significant impairment in selective attention, divided attention, short-term memory, processing speed, and executive functions. On the contrary, these patients have no marked impairment in sustained attention.
  2. Sex, employment, duration of illness, number of previous episodes, and receiving antidepressants are NOT correlated with cognitive dysfunction in patients with MDD.
  3. Increase severity of illness, detected by high Hmilton score, and to a lesser extent, number of hospitalization and duration of education were significant independent predictors of poor performance of the tested cognitive fuctions.
  4. Age and age at illness onset were positively correlated with poor cognitive performance. However, they were dependent on other predictors (illness severity, number of hospitalization, and education duration).


Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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    Tables

  [Table 1], [Table 2], [Table 3]



 

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