Late‐life onset psychotic symptoms and incident cognitive impairment in people without dementia: Modification by genetic risk for Alzheimer's disease
Bibliographic record
Abstract
Abstract Introduction Late‐life onset psychosis is associated with faster progression to dementia in cognitively normal people, but little is known about its relationship with cognitive impairment in advance of dementia. Methods Clinical and genetic data from 2750 people ≥50 years of age without dementia were analyzed. Incident cognitive impairment was operationalized using the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and psychosis was rated using the Mild Behavioral Impairment Checklist (henceforth MBI‐psychosis). The whole sample was analyzed before stratification on apolipoprotein E ( APOE ) ε4 status. Results In Cox proportional hazards models, MBI‐psychosis had a higher hazard for cognitive impairment relative to the No Psychosis group (hazard ratio [HR]: 3.6, 95% confidence interval [CI]: 2.2–6, p < 0.0001). The hazard for MBI‐psychosis was higher in APOE ε4 carriers and there was an interaction between the two (HR for interaction: 3.4, 95% CI: 1.2–9.8, p = 0.02). Discussion Psychosis assessment in the MBI framework is associated with incident cognitive impairment in advance of dementia. These symptoms may be particularly important in the context of APOE genotype.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".