Trajectories of Behavioural Disturbances Across Dementia Types
Bibliographic record
Abstract
OBJECTIVE: To replicate a previous finding that the trajectory of the Neuropsychiatric Inventory (NPI) shifts in the sixth year of behavioural variant frontotemporal dementia (bvFTD). We evaluated longitudinal tracking with both the Frontal Behavioural Inventory (FBI) and NPI, comparing bvFTD against other dementias. METHODS: Chart reviews over two to five years for patients with bvFTD (n=30), primary progressive aphasia (PPA, n=13) and Alzheimer's disease (AD, n=118) at an urban Canadian tertiary clinic specializing in dementia. Linear regressions of the longitudinal data tested predictors of annualized rates of change (ROC) in NPI and FBI total and subscales for apathy and disinhibition among dementia groups. RESULTS: The mode of the overall sample for the most advanced duration of illness observed was 5 years, with the median at 7 years. We did not find a crescendo-decrescendo pattern in scores although, for bvFTD and AD, high initial scores correlated with ensuing downward ROCs on the NPI and FBI. Educational level showed an influence on disinhibition ROCs. The FBI was no more revealing than the NPI for apathy and disinhibition scores in these dementias. CONCLUSIONS: A cognitive reserve effect on behavioural disturbance was supported but it may take longer than our 4 years of observing the clinical sample to record inflection points in the behavioural and psychiatric symptoms seen in bvFTD. The current data only imply that both apathy and disinhibition will diminish over the course of dementia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".