The Role of Cerebrovascular Disease on Cognitive and Functional Status and Psychosis in Severe Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: The pathophysiology behind psychosis in patients with Alzheimer's disease (AD) remains unknown. Recently, vascular risk factors have been recognized as important modifiers of the clinical presentation of AD. OBJECTIVE: The purpose of our study is to investigate the mechanism through which vascular risk factors mediate psychosis and whether or not it involves cerebrovascular lesions. METHODS: Data was provided by the National Alzheimer's Coordinating Centre. The Uniform Data Set was used to collect information on subject-reported history of vascular risk factors, clinician-reported state of cognitive performance, and presence of psychosis based on the Neuropsychiatric Inventory Questionnaire (NPI-Q). The Neuropathology Data Set was used to evaluate the presence of vascular lesions and the severity of AD pathology. Subjects with high probability of AD based on the NIA/AA Reagan criteria were included in the analysis. RESULTS: We identified 1,459 patients with high probability of AD and corresponding NPI-Q scores. We confirmed the association between hypertension and diabetes on psychosis, specifically in delusions and the co-occurrence of delusions and hallucinations. Furthermore, the presence of white matter rarefaction based on pathological evaluation was associated with hallucinations. A history of vascular risk factors was positively associated with vascular lesions. However, vascular lesions in the presence of vascular risk factors did not increase the likelihood of psychosis. Furthermore, vascular lesions were not associated with greater cognitive or functional impairments in this group with severe AD pathology. CONCLUSION: Vascular risk factors and vascular lesions are independently associated with psychosis in patients with severe AD. However, vascular lesions are not the mechanism through which vascular risk factors mediate psychosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".