Mild cognitive impairment as a risk factor for Parkinson's disease dementia
Bibliographic record
Abstract
BACKGROUND: The International Parkinson and Movement Disorder Society criteria for mild cognitive impairment in PD were recently formulated. OBJECTIVES: The aim of this international study was to evaluate the predictive validity of the comprehensive (level II) version of these criteria by assessment of their contribution to the hazard of PD dementia. METHODS: Individual patient data were selected from four separate studies on cognition in PD that provided information on demographics, motor examination, depression, neuropsychological examination suitable for application of level II criteria, and longitudinal follow-up for conversion to dementia. Survival analysis evaluated the predictive value of level II criteria for cognitive decline toward dementia as expressed by the relative hazard of dementia. RESULTS: A total of 467 patients were included. The analyses showed a clear contribution of impairment according to level II mild cognitive impairment criteria, age, and severity of PD motor symptoms to the hazard of dementia. There was a trend of increasing hazard of dementia with declining neuropsychological performance. CONCLUSIONS: This is the first large international study evaluating the predictive validity of level II mild cognitive impairment criteria for PD. The results showed a clear and unique contribution of classification according to level II criteria to the hazard of PD dementia. This finding supports their predictive validity and shows that they contribute important new information on the hazard of dementia, beyond known demographic and PD-specific factors of influence. © 2017 International Parkinson and Movement Disorder Society.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".