F4‐03‐03: NEURITIC PLAQUE LOAD AS SUBSTRATE OF PSYCHOSIS IN COGNITIVELY INTACT SUBJECTS
Bibliographic record
Abstract
Despite severe underlying Alzheimer's disease (AD) pathology, a significant number of individuals show no or mild cognitive deficits. Psychosis is a common neuropsychiatric symptom (NPS) of AD that has been linked to faster cognitive decline. Identifying NPS independent of cognitive deficits may allow us to better differentiate the neurobiology of these common deficits. The aim of the current study is to examine the prevalence and pathological correlates of psychosis in cognitively intact subjects with severe AD pathology. Furthermore, we seek to explore the role of vascular lesions and Lewy body pathology in the manifestation of psychosis. Data was obtained from the Uniform and the Neuropathology Data Set of the National Alzheimer's Coordinating Center collected between September 2005 and December 2015. Neuropsychiatric Inventory Questionnaire, quick version (NPI-Q), was used to evaluate presence of psychosis within the last month prior to clinical visit. The Mini-Mental Status Examination (MMSE) was used to assess cognitive function. The severity of AD pathology was evaluated based on the density of neuritic plaques (NPs) and neurofibillary tangles (NFTs). Subjects with frequent NPs or Braak&Braak (B&B) stage of NFTs of V/VI with MMSE score of 324 were defined as NPcASYM and NTcASYM respectively (collectively cASYM). Logistic regression analysis was used to examine the association between psychosis and NPcASYM or NTcASYM status, while accounting for potential confounders. We identified 697 subjects with MMSE score of 324, of which 174 were cASYM (137 NPcASYM, 96 NTcASYM, and 59 both NPcASYM and NTcASYM). NPcASYM subjects were at significantly higher risk of having psychosis, compared with those with moderate or sparse/no NPs (OR, 2.47, 95% CI: 1.54–3.96), independent of demographic factors, vascular pathology, and Lewy bodies. NTcASYM subjects were also at significantly higher risk of psychosis compared to subjects with B&B stage I-IV. However, the association was lost after adjustment for Lewy body pathology and vascular pathology. The load of NPs may be an important substrate of psychosis in individuals who show no gross cognitive symptoms. Longitudinal studies examining the progression of NPs are needed to identify factors that lead to divergence in clinical manifestations.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".