Visual Hallucinations and Cognitive Impairment in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Visual hallucination (VH) is a common psychotic symptom in patients with Parkinson's disease (PD) and may be a significant predictor of cognitive impairment (CI) in such patients. OBJECTIVE: This study aimed to investigate the pattern of glucose metabolism of VH and the relationship between VH and CI in PD. METHODS: We studied 28 PD patients, including 15 with VH (PD-VH) and 13 without VH (PD-NVH). Of the 15 PD-VH patients, 8 patients had cognitive impairment (PD-VHCI) whereas 7 did not (PD-VHNCI). All patients underwent [18F] fluorodeoxyglucose positron emission tomography ([18F] FDG PET) followed by statistical parametric mapping (SPM) analyses. RESULTS: Compared to the patients with PDNVH, PD-VHNCI patients showed glucose hypometabolism in the inferior and middle temporal cortices, fusiform gyri, and frontal areas, suggesting the involvement of the ventral visual pathway. Compared to the patients with PDNVH, PD-VHCI patients showed glucose hypometabolism in the temporoparietal association cortices with scattered frontal areas. CONCLUSION: Dysfunction of ventral visual pathway involving the temporal lobe may play a key role in VH development in PD patients. The evolving distribution from the ventral visual pathway to more extensive posterior cortices in PD-VHCI patients suggests that VH may be a prodromal symptom occurring prior to CI in PD patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".