Validation of the MDS research criteria for prodromal Parkinson's disease: Longitudinal assessment in a REM sleep behavior disorder (RBD) cohort
Bibliographic record
Abstract
BACKGROUND: Recently, the International Parkinson and Movement Disorder Society introduced the prodromal criteria for PD. Objectives Our study aimed to examine diagnostic accuracy of the criteria as well as the independence of prodromal markers to predict conversion to PD or dementia with Lewy bodies. METHODS: This prospective cohort study was performed on 121 individuals with rapid eye movement sleep behavior disorder who were followed annually for 1 to 12 years. Using data from a comprehensive panel of prodromal markers, likelihood ratio and post-test probability of the criteria were calculated at baseline and during each follow-up visit. RESULTS: Forty-eight (39.7%) individuals with rapid eye movement sleep behavior disorder converted to PD/dementia with Lewy bodies. The prodromal criteria had 81.3% sensitivity and 67.9% specificity for conversion to PD/dementia with Lewy bodies at 4-year follow-up. One year before conversion, sensitivity was 100%. The criteria predicted dementia with Lewy bodies with even higher accuracy than PD without dementia at onset. Those who met the threshold of prodromal criteria at baseline had significantly more rapid conversion into a neurodegenerative state (4.8 vs. 9.1 years; P < 0.001). Pair-wise combinations of different prodromal markers showed that markers were independent of one another. CONCLUSION: The prodromal criteria are a promising tool for predicting incidence of PD/dementia with Lewy bodies and conversion time in a rapid eye movement sleep behavior disorder cohort, with high sensitivity and high specificity with long follow-up. Prodromal markers influence the overall likelihood ratio independently, allowing them to be reliably multiplied. Defining additional markers with high likelihood ratio, further studies with longitudinal assessment and testing thresholds in different target populations will improve the criteria. © 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".