Movement disorder society criteria for clinically established early Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: In 2015, the International Parkinson and Movement Disorder Society published clinical diagnostic criteria for Parkinson's disease (PD). Although recent validation studies suggest high accuracy, one unmet need is for highly specific criteria for clinical trials in early/de novo PD. OBJECTIVES: The objective of this study was to generate and test a PD diagnostic criteria termed "clinically established early PD." METHODS: We modified the Movement Disorder Society criteria to increase specificity for early PD by removing all disease duration components and changing red flags to absolute exclusions. We then estimated the sensitivity/specificity of clinically established early PD criteria in patients with disease duration <5 years, selected from a 626-patient validation study. RESULTS: After documentation of parkinsonism, 18 individual exclusion criteria are assessed that preclude the diagnosis of "clinically established early PD." Among 212 PD and 152 non-PD patients, the estimated specificity was 95.4%, with 69.8% sensitivity. CONCLUSIONS: We describe high-specificity criteria for de novo PD, which are freely available for use in clinical trials. © 2018 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".