Neurocognitive Speed and Inconsistency in Parkinson's Disease with and without Incipient Dementia: An 18-Month Prospective Cohort Study
Bibliographic record
Abstract
We examined two-wave longitudinal changes in two indicators of neurocognitive speed (i.e., mean rate, intraindividual variability) using one simple and three complex reaction time tasks. Participants included idiopathic Parkinson's disease (PD) patients, with and without incipient dementia, and normal controls. At baseline, there were 45 patients (26 men, 19 women) with idiopathic PD who ranged from 65 to 84 years (M = 71.3; SD = 4.5) and 47 matched controls (27 men, 20 women) who ranged from 65 to 84 years (M = 71.4; SD = 4.9). The 18-month longitudinal sample comprised of 74 returning participants (43 controls; 31 PD patients) who had no cognitive impairment or dementia at both waves. Ten of the 31 PD patients returning for Time 3 had dementia or cognitive impairment. These constituted the PD with incipient dementia (PDID) group. Repeated measures analyses of variance showed that the PD and PDID groups were slower over time on the reaction time tasks, whereas the controls improved their performance over time on all tasks. Inconsistency distinguished the two clinical groups (i.e., the PDID group but not the PD group became more inconsistent over time). Changes in neurocognitive speed and inconsistency may be valid clinical markers of PDID.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".