Association between visual hallucinations and cognitive performance in Lewy body dementia and Alzheimer's disease: A cross-sectional study
Bibliographic record
Abstract
Background: Visual hallucinations (VH) are an important neuropsychiatric feature of dementia. The association between VH and cognition remains controversial. Objective: To investigate the differences in clinical correlates of VH and explore the associations between VH and cognitive functional decline in individuals with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD). Methods: Outpatient medical records of 154 patients with DLB and 297 patients with AD between January 2017 and December 2023 were reviewed. We collected demographic characteristics and used neuropsychological assessments and semi-structured detailed interviews to evaluate cognition and VH. Multiple linear regression and mediation analyses were employed to analyze the data, adjusting for confounding variables. Results: DLB patients had a higher prevalence of VH than AD patients (p < 0.01). The presence of VH predicted lower Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores in both DLB and AD patients (p < 0.01). In DLB patients, VH were associated with lower attention function scores after adjustment (p = 0.027). In AD patients, VH were related to worsened orientation ability after adjustment (p = 0.033). Attention function partially mediated the association between VH and cognition in DLB patients (p < 0.01), whereas orientation function partially mediated this association in AD patients (p < 0.01). Conclusions: VH may independently correlate with deterioration in global cognitive performance. In DLB patients with VH, attentional function appears to be more impaired, whereas in AD patients, orientation function is the most affected. Different cognitive domains may help distinguish between DLB and AD patients with VH.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".