Multidimensional cognitive impairment in unipolar and bipolar depression and the moderator effect of adverse childhood experiences
Bibliographic record
Abstract
AIM: Studies have demonstrated neuropsychological deficits across a variety of cognitive domains in depression. These deficits are observable both in major depressive disorder (MDD) and in bipolar disorder (BD) and are present in each phase of the illness, including euthymia. Adverse childhood experiences (ACE) have been associated with an increased risk of developing psychiatric disorders and cognitive deficits. The aim of this study was to assess neuropsychological performances in a sample of MDD and BD patients during a depressive episode compared to healthy controls (HC) and, to investigate if ACE affect the cognitive profiles in the three groups. METHODS: Seventy-six BD patients, 57 MDD patients, and 57 HC underwent neuropsychological assessment for cognitive performances through the Brief Assessment of Cognition in Schizophrenia and Wisconsin Card Sorting Test. RESULTS: Both BD and MDD patients obtained significantly lower domain scores across the entire battery compared to HC. Splitting the sample according to exposure to ACE (high and low), the differences observed in the whole sample persisted only in the subsample of those patients exposed to high ACE. CONCLUSION: This study confirms that cognitive impairment is present both in MDD and BD, albeit in different degrees of severity, and highlights the importance of early stress as a moderator factor when investigating cognitive functions in mood disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".