Clinical and functional impact of cognitive fluctuations in dementia
Bibliographic record
Abstract
Cognitive fluctuations (CFs) are defined as spontaneous alterations in cognition, attention, and arousal, and are highly prevalent and disabling among people with dementia. CFs occur with a frequency of 80-90% in dementia with Lewy bodies (DLB), 40% in vascular dementia (VaD), and 20% in Alzheimer’s disease (AD). While CFs have been recognized as an important component of dementia, the majority of studies examining them have lacked objective methods of assessing their presence and severity, making it difficult to determine the degree of interference with other clinical features that can be attributable to fluctuations. The present study examined the nature and frequency of CFs in 55 individuals with dementia living in a long-term care facility. Participants underwent neuropsychological assessment to profile their current cognitive functioning. The Dementia Cognitive Fluctuation Scale (DCFS) was used to characterize CFs in this sample. Patients also completed brief cognitive measures on three separate occasions during a one-week period to obtain objective evidence of variability in cognitive performance. This study also assessed the association between CFs and informant based measures of patients’ quality of life, activities of daily living, and formal caregiver burden. Longitudinal cognitive data was analyzed retrospectively to determine patients’ rate of cognitive decline over the past six months. Consistent with the limited research already completed in this area, this study found that increasing severity of CFs predicts lower cognitive performance and reduced ability to complete activities of daily living. Also, this is the first study to demonstrate that CFs predict patients’ overall quality of life and the degree of caregiver burden in primary nursing staff. Results of the current study suggest that CFs exert a broad range of influence over patients’ functional abilities and well being. Identifying which patients experience CFs could play an important role in developing individualized treatment plans best suited for patients specific care needs.
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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 | 0.005 |
| 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 | 0.000 |
| 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".