Factors associated with objective and subjective cognitive impairment in Chinese patients with acute major depressive disorder

重性抑郁障碍 警觉 焦虑 萧条(经济学) 认知 心理学 医学 精神科 经济 宏观经济学
作者
Na Zhu,Jie Tong,Pei Yu,Jie Zhang,Xirong Sun
出处
期刊:BMC Psychiatry [BioMed Central]
卷期号:23 (1) 被引量:3
标识
DOI:10.1186/s12888-023-04857-y
摘要

Abstract Background Patients diagnosed withmajor depressive disorder (MDD) usually experience impaired cognitive functioning, which might negatively impact their clinical and functional outcomes. This study aimed to investigate the association of specific clinical factors with cognitive dysfunction in a group of MDD patients. Methods A total of 75 subjects diagnosed with recurrent MDD were evaluated during the acute stage. Their cognitive functions were assessed using the THINC-integrated tool (THINC-it) for attention/alertness, processing speed, executive function, and working memory. Clinical psychiatric evaluations, such as the Hamilton Anxiety Scale (HAM-A), the Young Mania Rating Scale (YMRS), the Hamilton Depression Scale (HAM-D), and the Pittsburgh Sleep Quality Index(PSQI), were used to assess patients’ levels of anxiety, depression and sleeping problems. The investigated clinical variables were age, years of education, age at onset, number of depressive episodes, disease duration, presence of depressive and anxiety symptoms, sleep problems, and number of hospitalizations. Results The results revealed that significant differences were observed between the two groups in the THINC-it total scores, Spotter, Codebreaker, Trails, and PDQ-5-D scores ( P < 0.001). The THINC-it total scores, Spotter, Codebreaker, Trails, and Symbol Check were significantly associated with age and age at onset( P < 0.01). In addition, regression analysis found that years of education was positively associated with the Codebreaker total scores ( P < 0.05). the THINC-it total scores, Symbol Check, Trails, and Codebreaker were correlated with the HAM-D total scores( P < 0.05). Additionally, the THINC-it total scores, Symbol Check, PDQ-5-D and Codebreaker significantly correlated with the PSQI total scores ( P < 0.05). Conclusion We found a significant statistical association between almost all cognitive domains and different clinical aspects in depressive disorder, such asage, age at onset, severity of depression, years of education, and sleep problems. Additionally, education was shown to be a protective factor against processing speed impairments. Special considerations of these factors might help outline better management strategies to improve cognitive functions in MDD patients.
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