p300 latency as an indicator of severity in major depressive disorder
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ID: 183654
2015
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Abstract
Background: Depression is the most common mental health problem across all the age groups. Still diagnostic techniques and laboratory tests are awaited to confirm it. Some studies focus on P300 latency to aid in the diagnosis of depression. Hence, this study was conducted to know whether P300 latency is an indicator of major depressive disorder (MDD). Methods: This study was conducted both on patients admitted in the hospital and those attending outdoor clinic giving written informed consent and fulfilling inclusion/exclusion criteria from the Department of Psychiatry, S.N. Medical College and Hospital, Agra. The sample consisted of 30 consecutive patients suffering from MDD as per the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria and 30 subjects as normal control. Sociodemographic and clinical history proforma, Hamilton Rating Scale for Depression (Ham-D), and P300 were administered on all 60 subjects. Data were analyzed using mean, standard deviation, and t-test. Results: Significant difference (P < 0.0001) has been found in HAM-D mean scores of depressed and nondepressed control group subjects. The mean score of depressed group was significantly high (18.066) compared to nondepressed control group (4.833). Significant difference (P < 0.0001) between the mean of P300 latency in depressed and nondepressed control subjects was also found. Mean score of P300 latency in depressed group was significantly high (346.918 ± 19.515) compared to the nondepressed control subjects (303.741 ± 6.378). There was a significant difference in the mean of P300 latency between mild and severe (P < 0.0001), mild and very severe (P < 0.0003), as well as moderate and severe (P < 0.0001) level of depression. Conclusions: P300 latency may be used as an indicator of MDD and it is directly proportional to the severity of MDD.
| Reference Key |
tripathi2015industrialp300
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| Authors | ;Shailendra Mohan Tripathi;Neeti Mishra;Rakesh Kumar Tripathi;K C Gurnani |
| Journal | trends in neurosciences |
| Year | 2015 |
| DOI |
10.4103/0972-6748.181726
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