Duration of untreated illness and depression severity are associated with cognitive impairment in mood disorders
Bibliographic record
Abstract
Introduction: In this study we estimated the rate and the trajectory of cognitive impairment in a naturalistic sample of outpatients with major depressive disorder (MDD) and bipolar disorder (BD) and its correlation with different variables.Materials and methods: An overall sample of 109 outpatients with MDD or BD was assessed for multiple clinical variables, including duration of untreated illness (DUI), and tested using the Montreal Cognitive Assessment (MoCA) during Major Depressive Episodes (MDE) and after remission. Correlations between MoCA scores and the clinical variables were then computed.Results: About 50% of patients with MDD and BD showed mild cognitive impairment during MDE. Improvement of cognitive function between depression and remission was significant, even though residual symptoms were observed especially in the most impaired patients. Of note, cognitive performance during depression was negatively associated with depression severity and DUI.Discussion: Present findings confirm available evidence about patterns of cognitive impairment in mood disorders, in terms of prevalence and persistence beyond remission in most severe cases. Moreover, a longer DUI was associated with worse cognitive performance during depression, and consequently with poorer outcome, underlining the importance of prompt treatment of these disorders also in light of a cognitive perspective.KeypointsAlthough distinct entities, unipolar and bipolar depression determine similar patterns of cognitive impairment in terms of severity and types of altered domains.Depression (but not anxiety) severity is associated with cognitive performance in depression.Prolonged duration of untreated illness is associated with more severe cognitive impairment during depression, particularly but not specifically in bipolar disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".