Using the THINC-integrated tool to compare the characteristics of cognitive dysfunction in patients with unipolar and...

Major depressive disorder (MDD) and bipolar depression (BD-D) are both intricate, enduring, and profound psychiatric conditions characterized primarily by depressive episodes and cognitive dysfunction. However, distinguishing the characteristics and influencing factors of cognitive impairment in unipolar and BD-D is crucial for identification and intervention.

To compare neurocognitive characteristics and investigate associations between cognitive function and clinical features in unipolar and BD-D.

The THINC-integrated tool (THINC-it) as a cognitive assessment tool was applied to 295 individuals: 75 patients with depressive disorders (MDD), 120 individuals with BD-D, and 100 healthy controls. The Hamilton Depression Scale-17 (HAMD), Hamilton Anxiety Scale-14 (HAMA), and Pittsburgh Sleep Quality Index (PSQI) were employed to assess depression, anxiety, and sleep. Neurocognitive function characteristics and the relationships between cognitive impairment and general clinical attributes were analyzed.

There were no statistically significant differences in the overall THINC-it with each objective subscale. However, the subjective subscale (Perceived Deficits Questionnaire for Depression-5-item) showed significant differences between MDD and BD-D (P < 0.001). Linear regression analyses were explored to determine associations. Age, years of education, age at onset, and HAMD were significantly co-associated with the overall THINC-it and each subscale in both MDD and BD-D (P < 0.05). Furthermore, years of education showed a positive correlation with objective cognitive impairment (e.g., Codebreaker, Trails) (P < 0.05). There was a notable difference in that the number of depressive episodes, disease duration, hospitalizations, HAMA, and PSQI were significantly associated with the overall THINC-it with each subscale between MDD and BD-D (P < 0.05).

Although both unipolar and BD-D showed similar objective cognitive impairments, there was a significant difference in subjective cognitive impairment. Our findings suggest that factors like age, years of education, age at onset, and depression severity might not be significantly difference in the influence of cognitive impairment. Furthermore, we found that education was a protective factor for cognitive impairment in both unipolar and BD-D. Our analysis revealed that distinct factors including disease duration, number of depressive episodes, hospitalizations, anxiety levels, and sleep quality influenced cognitive impairment between unipolar and BD-D. Therefore, it was important to investigate the specific characteristics of cognitive impairment and influencing factors to identify differentiating unipolar and BD-D.