The relationship between executive dysfunction and neuropsychiatric symptoms in patients with Korsakoff’s syndrome
Bibliographic record
Abstract
Objective: Patients with Korsakoff’s syndrome (KS) show executive dysfunction and neuropsychiatric symptoms. This study investigates whether specific executive subcomponents (shifting, updating, and inhibition) predict variance in neuropsychiatric symptoms. We hypothesized that shifting deficits, in particular, are associated with neuropsychiatric symptoms.Method: Forty-seven patients participated (mean age 61.5; 11 women). Executive function (EF) was measured using six component-specific tasks. Neuropsychiatric symptoms were measured with the Neuropsychiatric Inventory – Questionnaire (NPI-Q). General cognitive functioning was assessed with the Montreal Cognitive Assessment (MoCA). First, factor analysis was conducted to examine shared variance across the EF tasks. Subsequently, a regression analysis was performed with the EF factors and the MoCA as predictors and the NPI-Q as the dependent variable. It was also investigated whether an interaction effect between the EF factors and the MoCA was present.Results: The prevalence of neuropsychiatric symptoms was high (85.7% of the KS patients showed at least one symptom). A two-factor model was extracted with a shifting-specific factor and a combined updating/inhibition factor. The overall regression model was not significant, and no interaction was found between the EF factors and general cognitive functioning. However, a significant relationship between general cognitive functioning and neuropsychiatric symptoms (r = -.43; p <.01) was detected.Conclusions: Results point at an association between neuropsychiatric symptoms and general cognitive functioning. Possibly, diminished cognitive differentiation in these patients with severe cognitive dysfunction accounts for the absence of a significant association between EF and neuropsychiatric symptoms. While the results should be interpreted with caution due to a limited sample size, the found association highlights the need to further unravel the underlying cognitive mechanisms of neuropsychiatric symptoms in patients with KS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".