Validation of the Movement Disorder Society Criteria for the Diagnosis of 4‐Repeat Tauopathies
Bibliographic record
Abstract
BACKGROUND: The Movement Disorder Society criteria for progressive supranuclear palsy introduced the category "probable 4-repeat (4R)-tauopathy" for joint clinical diagnosis of progressive supranuclear palsy and corticobasal degeneration. OBJECTIVES: To validate the accuracy of these clinical criteria for "probable 4R-tauopathy" to predict underlying 4R-tauopathy pathology. METHODS: Diagnostic accuracy for 4R-tauopathies according to the established criteria was estimated retrospectively in autopsy-confirmed patients with progressive supranuclear palsy and corticobasal degeneration (grouped as 4R-tauopathies), and Parkinson's disease, multiple system atrophy, and frontotemporal lobar degeneration (grouped as non-4R-tauopathies). RESULTS: We identified 250 cases with progressive supranuclear palsy (N = 195) and corticobasal degeneration (N = 55) and with and non-4R-tauopathies (N = 161). Sensitivity and specificity of "probable 4R-tauopathy" was 10% and 99% in the first year and 59% and 88% at final record. CONCLUSIONS: The new diagnostic category "probable 4R-tauopathy" showed high specificity and may be suitable for the recruitment of patients with progressive supranuclear palsy and corticobasal degeneration into therapeutic trials targeting 4R-tauopathy. The low sensitivity underpins the need for diagnostic biomarkers. © 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".