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This study aimed to identify clinical and cognitive factors associated with increased risk for difficult-to-treat depression (DTD) or treatment-resistant depression (TRD).
A total of 229 adult outpatients with major depression were recruited from the mental health unit at a public hospital. Participants were subdivided into resistant and nonresistant groups according to their Maudsley Staging Model score. Sociodemographic, clinical, and cognitive (objective and subjective measures) variables were compared between groups, and a logistic regression model was used to identify the factors most associated with TRD risk.
TRD group patients present higher verbal memory impairment than the nonresistant group irrespective of pharmacological treatment or depressive symptom severity. Logistic regression analysis showed that low verbal memory scores (odds ratio [OR]: 2.02; 95% confidence interval [CI]: 1.38–2.95) together with high depressive symptom severity (OR: 1.29; CI95%: 1.01–1.65) were associated with TRD risk.
Our findings align with neuroprogression models of depression, in which more severe patients, defined by greater verbal memory impairment and depressive symptoms, develop a more resistant profile as a result of increasingly detrimental neuronal changes. Moreover, our results support a more comprehensive approach in the evaluation and treatment of DTD in order to improve illness course. Longitudinal studies are warranted to confirm the predictive value of verbal memory and depression severity in the development of TRD.
Heterogeneity in cognitive functioning among major depressive disorder (MDD) patients could have been the reason for the small-to-moderate differences reported so far when it is compared to other psychiatric conditions or to healthy controls. Additionally, most of these studies did not take into account clinical and sociodemographic characteristics that could have played a relevant role in cognitive variability. This study aims to identify empirical clusters based on cognitive, clinical and sociodemographic variables in a sample of acute MDD patients.
In a sample of 174 patients with an acute depressive episode, a two-step clustering analysis was applied considering potentially relevant cognitive, clinical and sociodemographic variables as indicators for grouping.
Treatment resistance was the most important factor for clustering, closely followed by cognitive performance. Three empirical subgroups were obtained: cluster 1 was characterized by a sample of non-resistant patients with preserved cognitive functioning (n = 68, 39%); cluster 2 was formed by treatment-resistant patients with selective cognitive deficits (n = 66, 38%) and cluster 3 consisted of resistant (n = 23, 58%) and non-resistant (n = 17, 42%) acute patients with significant deficits in all neurocognitive domains (n = 40, 23%).
The findings provide evidence upon the existence of cognitive heterogeneity across patients in an acute depressive episode. Therefore, assessing cognition becomes an evident necessity for all patients diagnosed with MDD, and although treatment resistant is associated with greater cognitive dysfunction, non-resistant patients can also show significant cognitive deficits. By targeting not only mood but also cognition, patients are more likely to achieve full recovery and prevent new relapses.
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