Trajectories of Cognitive Decline following Dementia Onset: What Accounts for Variation in Progression?
Bibliographic record
Abstract
BACKGROUND: Delineating the natural history of dementia progression has important clinical implications, including reducing caregiver burden and targeting effective drug trials. We examined whether trajectories of cognitive change differed reliably after diagnosis, and whether diverse predictors of such differences (demographic, psychological, biological, genetic, social) could be identified. METHODS: Cognitive change was examined for incident dementia cases (mild: n = 156; moderate: n = 77; severe: n = 73) and controls (n = 249) from the Kungsholmen Project, a community-based study of adults 75 years and older. RESULTS: For those with dementia, total variance attributed to between-person differences in cognitive decline was modest and linked to but a single predictor (history of cardiovascular disease). Although less variance in cognitive decline was observed for the similarly aged controls, numerous significant predictors of these differences were identified. CONCLUSION: The neurodegenerative process underlying dementia overshadows formerly significant predictors of cognitive change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".