Editors' Note: Cognitive-Driven Activities of Daily Living Impairment as a Predictor for Dementia in Parkinson Disease: A Longitudinal Cohort Study
Bibliographic record
Abstract
In “Cognitive-Driven Activities of Daily Living Impairment as a Predictor for Dementia in Parkinson Disease: A Longitudinal Cohort Study,” Becker et al. report that while 40% of 268 patients with Parkinson disease (PD) had mild cognitive impairment (MCI) at baseline, of 164 patients who completed follow-up after 3.78 ± 0.84 years, 33% had MCI and 10% had dementia. Patients in this study were evaluated using the Functional Activities Questionnaire (FAQ) to differentiate cognitive and motor contributions to impairment in performance of instrumental activities of daily living (IADL). Kasten questions how the results of the FAQ compared with results of the Montreal Cognitive Assessment (MoCA) and whether these scores could be used interchangeably. Dr. Kasten also cites a prior study that found that the Unified Parkinson Disease Rating Scale was moderately correlated with the MoCA. Becker reports there was a weak to moderate correlation between FAQ and MoCA scores at both baseline and follow-up. However, although there is some overlap between these assessments, Becker does not believe they should be used interchangeably because MoCA measures general cognition while the FAQ measures cognitive contributions to IADL impairment. This exchange highlights important methodological considerations when screening for cognitive decline in PD.
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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 | 0.018 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".