Hallucinations and Delusions Signal Alzheimer’s Associated Cognitive Dysfunction More Strongly Compared to Other Neuropsychiatric Symptoms
Bibliographic record
Abstract
OBJECTIVES: Neuropsychiatric symptoms (NPS) are common among individuals with dementia of the Alzheimer's type (DAT). We sought to characterize which NPS more purely relate to cognitive dysfunction in DAT, relative to other NPS. METHOD: Demographic, neurocognitive, neuroimaging, and NPS data were mined from the Alzheimer's Disease Neuroimaging Initiative database (n = 906). Using factor analysis, we analyzed the degree to which individual NPS were associated with DAT-associated cognitive dysfunction. We also employed item response theory to graphically depict the ability of individual NPS to index DAT-associated cognitive dysfunction across a continuum ranging from cognitively normal to mild DAT. RESULTS: Psychotic symptoms (hallucinations and delusions) were more strongly related to the continuum of DAT-associated cognitive dysfunction than other NPS, with the strength of the relationship peaking at high levels of disease severity. Psychotic symptoms also negatively correlated with brain volume and did not relate to the presence of vision problems. Aberrant motor behavior and apathy had relatively smaller associations with DAT-associated cognitive dysfunction, while other NPS showed minimal associations. DISCUSSION: Psychotic symptoms most strongly indexed DAT-associated cognitive dysfunction, whereas other NPS, such as depression and anxiety, were not as precisely related to the DAT-associated cognitive dysfunction.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".