Relationship between neuropsychiatric symptoms and Alzheimer's disease pathology: An in vivo positron emission tomography study
Bibliographic record
Abstract
OBJECTIVES: To investigate the relationship between amyloid-β- and tau-based Alzheimer's disease (AD) pathologies assessed using positron emission tomography imaging and neuropsychiatric symptoms (NPS) in a sample of AD continuum including clinically normal subjects and patients with mild cognitive impairment or AD. METHODS: We analyzed datasets of the Alzheimer's disease Neuroimaging Initiative and included amyloid-positive subjects who underwent an AV-45 scan within 1 year of an AV-1451 scan (n = 99). Correlation between standardized uptake value ratio (SUVR) of AV-45 and AV-1451 and the Neuropsychiatric Inventory (NPI) score (and its four domain subscores for hyperactivity, psychosis, affective, and apathy) was evaluated. Stepwise logistic regression analysis was used to examine the influence of SUVRs on the presence of NPS. SUVRs were also tested for their ability to discriminate the group with NPS using receiver operating characteristic (ROC) curve analyses. RESULTS: Significant positive relationships were found between the total NPI score and affective symptoms and Braak 1&2 (transentorhinal region) AV-1451 SUVR. Stepwise logistic regression analysis identified tau accumulation in the area of Braak 1&2 as a significant covariate discriminating the presence of affective symptoms. The area under the ROC curve analysis showed that subjects with affective symptoms were discriminated by AV-1451 SUVR with an accuracy of 77.7%. CONCLUSIONS: Tau aggregation in the transentorhinal region, where neurodegeneration affected by tau pathology was seen in the early stage of AD, correlated with more severe NPS, especially affective symptoms. Therefore, tau pathology in the transentorhinal cortex might be associated with affective symptoms in the early stage of AD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".