How to apply the movement disorder society criteria for diagnosis of progressive supranuclear palsy
Bibliographic record
Abstract
BACKGROUND: The Movement Disorder Society criteria for progressive supranuclear palsy define diagnostic allocations, stratified by certainty levels and clinical predominance types. We aimed to study the frequency of ambiguous multiple allocations and to develop rules to eliminate them. METHODS: We retrospectively collected standardized clinical data by chart review in a multicenter cohort of autopsy-confirmed patients with progressive supranuclear palsy, to classify them by diagnostic certainty level and predominance type and to identify multiple allocations. RESULTS: Comprehensive data were available from 195 patients. More than one diagnostic allocation occurred in 157 patients (80.5%). On average, 5.4 allocations were possible per patient. We developed four rules for Multiple Allocations eXtinction (MAX). They reduced the number of patients with multiple allocations to 22 (11.3%), and the allocations per patient to 1.1. CONCLUSIONS: The proposed MAX rules help to standardize the application of the Movement Disorder Society criteria for progressive supranuclear palsy. © 2019 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 | 0.037 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".