A Call for Change: Updating the Operational Definition for Dementia in Parkinson's Disease
Bibliographic record
Abstract
In Parkinson's disease (PD), cognitive dysfunction ranges from subjective cognitive complaints to mild cognitive impairment (PD-MCI) and PD dementia (PDD). Timely identification and management of cognitive impairment are major challenges in PD, with substantial burdens on those affected and healthcare systems. Recognizing the need for criteria for different stages of cognitive impairment in PD, the Movement Disorder Society (MDS) commissioned task forces developed clinical diagnostic criteria for PDD2 (2007) and PD-MCI3 (2012) to identify cognitive impairments and ensure uniform participant criteria for therapeutic trials. The criteria, based on literature review and expert consensus, provide recommendations for diagnostic procedures that operationalize PDD4 and PD-MCI3 diagnoses and allow for Level I and II assessments (depending on available time and resources), which have both undergone formal validation. The PD-MCI criteria have not only advanced the field regarding clinical, biomarker, genetic features and the conversion to PDD, but also facilitated pathways for industry and regulatory authorities to conduct clinical trials, specifically addressing this “at risk” stage of cognitive impairment.7 At the time when the PDD criteria were established, however, there was still considerable influence from the Alzheimer's disease (AD) field and few robust biomarkers. Indeed, the only symptomatic medication approved by regulatory authorities for PDD (namely rivastigmine) used the ADAS-cog, as the primary outcome measure.8 Even recent PDD trials vary substantially in their inclusion criteria and outcome measures selected, making reliable comparisons among studies or conducting meta-analyses nearly impossible.
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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 | 0.255 | 0.363 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.019 | 0.050 |
| Open science | 0.021 | 0.014 |
| Research integrity | 0.018 | 0.056 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".