The association between cognitive impairment and neuropsychiatric symptoms in patients with Parkinson's disease dementia
Bibliographic record
Abstract
BACKGROUND: Neuropsychiatric symptoms (NPS) are common in patients with dementia associated with Parkinson's disease (PDD). The relationship between cognition and NPS in PDD has not been well studied. METHODS: Patients diagnosed with PDD were assessed for cognitive function and NPS. The instruments used were the Neuropsychiatric Inventory (NPI), Mini-Mental State Examination (MMSE), and semantic verbal fluency according to the recommendation of the Movement Disorder Society Task Force. RESULTS: We evaluated 127 PDD patients (76 males/51 females; mean age 77 ± 6.3 years). Their mean MMSE score was 17 ± 6.5 and the mean NPI score was 19 ± 20.4. The most prevalent NPI items were anxiety (57.5%), sleep problems (53.5%), and apathy (52.0%). Principal component factor analysis revealed that 12 items formed three factors, namely "mood and psychosis" (delusion, hallucination, agitation, depression, anxiety, apathy, and irritability), "vegetative" (sleep and appetite problems), and "frontal" (euphoria, disinhibition, and aberrant motor behavior). Symptoms of hallucination were significantly associated with MMSE score, even after controlling for the confounding variables. CONCLUSION: NPS are common and diverse among patients with PDD. Three specific subgroups of NPS were identified. Hallucination was significantly correlated with cognitive impairment, and could be a predictor of cognition in PDD patients.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".