Clinical factors that predict cognitive function in patients with major depression

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.