Neuropsychiatric symptom burden across neurodegenerative disorders and its association with function
Bibliographic record
Abstract
Abstract Background Neuropsychiatric symptoms (NPS) are common in neurodegenerative disorders such as Alzheimer’s disease/Mild Cognitive Impairment (AD/MCI), Parkinson’s disease (PD), Frontotemporal Dementia (FTD), Amyotrophic Lateral Sclerosis (ALS) and in those with Cerebrovascular disease (CVD). The relationship between symptoms, cognition, and function in these cohorts is unclear. Method Data was obtained from the Ontario Neurodegenerative Disease Research Initiative study. We used the Neuropsychiatric Inventory Questionnaire‐ severity scale (NPIQ) to measure NPS, Montreal Cognitive Assessment (MoCA) for cognition, and Lawton’s informant based questionnaires to measure basic and instrumental activities of daily living (ADLs/iADLs). Linear regression was performed to investigate the effects of NPS on ADL and iADL function while controlling for age, education and cognition. Results were bootstrapped by resampling residuals (n=1,000) to control for non‐normal sample distribution. Result 520 participants were enrolled: AD/MCI (n=126), VCD (n=161), PD (n=140), FTD (n=53), and ALS (n=40). There were significant differences between these cohorts on NPIQ scores (AD/MCI=16.77±0.18, VCD=16.94±0.12, PD=16.34±0.17, FTD=21.44±0.15, ALS=14.19±0.22, p < .001). Across combined cohorts, NPIQ was inversely correlated with MoCA (rs=‐0.15, p=.001), iADLs (rs=‐0.32, p<.001), and ADLs (rs=‐0.34, p<.001). NPIQ (alone) predicted iADLs in FTD, and (together with MoCA) in MCI/AD and PD (Corrected p values < .05) but not in CVD or ALS. Further, NPIQ alone predicted ADLs in AD/MCI, FTD and PD (Corrected p values < .05) but not in VCD or ALS. Conclusion NPS burden was different across neurodegenerative disease cohorts. NPS were the main determinants of function in FTD, and in AD/MCI and PD when combined with cognition. However, NPS did not determine function in VCD or ALS. These findings indicate the need for further research into biomarkers of NPS and function, and targets of clinical interventions in neurodegenerative disorders.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".