Neuropsychiatric symptoms and cognition: An observational study in a Filipino memory clinic setting
Bibliographic record
Abstract
Abstract Background A growing body of evidence has described neuropsychiatric symptoms (NPS) as early markers of cognitive decline and may precede onset of measurable neurocognitive changes.1,2 NPS have been associated with accelerated cognitive decline and higher dementia conversion rates.3 The repeated observation that individuals with NPS are at increased risk of further cognitive decline delineates this group as high risk and suitable for early interventions to prevent cognitive and functional loss.4 The objectives are to determine the prevalence and compare the demographic and cognitive profiles of non‐demented individuals with NPS in a Filipino cohort. Method A total of 435 patients with no cognitive impairment (NCI) and Mild Cognitive Impairment (MCI) from St. Luke’s Medical Center Memory Clinic were included. NPS were assessed by administration of the Neuropsychiatric Inventory Questionnaire (NPI‐Q) to a reliable caregiver. Participants were administered the Mini‐Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Alzheimer’s Disease Assessment Scale Cognitive Subscale (ADAS‐Cog). Result Compared to patients without NPS, patients with NPS have more impaired cognition with lower MMSE (25 + 4 vs 27 + 3, p=0.001); MoCA (21 + 5 vs 23 + 5, p=0.002) and higher ADAS‐Cog scores (12.4.6 + 6 vs 10.6 + 6, p=0.01). A fully adjusted model showed NPS to be significantly associated with MMSE (‐0.8, 95% CI ‐1.6 to ‐0.02, p=0.04) and MoCA scores (‐1.2, 95% CI ‐2.3 to ‐0.2, p=0.02). Conclusion This study shows that non‐demented individuals with NPS have more cognitive impairment suggesting the importance of NPS as a potential marker for early cognitive decline and a need for further trials that targets treatment for NPS even at an early stage to prevent cognitive impairment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".