Validation of the MDS clinical diagnostic criteria for Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: In 2015, the International Parkinson and Movement Disorder Society published clinical diagnostic criteria for Parkinson's disease. These criteria aimed to codify/reproduce the expert clinical diagnostic process and to help standardize diagnosis in research and clinical settings. Their accuracy compared with expert clinical diagnosis has not been tested. The objectives of this study were to validate the International Parkinson and Movement Disorder Society diagnostic criteria against a gold standard of expert clinical diagnosis, and to compare concordance/accuracy of the International Parkinson and Movement Disorder Society criteria to 1988 United Kingdom Brain Bank criteria. METHODS: From 8 centers, we recruited 626 parkinsonism patients (434 PD, 192 non-PD). An expert neurologist diagnosed each patient as having PD or non-PD, regardless of International Parkinson and Movement Disorder Society criteria (gold standard, clinical diagnosis). Then a second neurologist evaluated the presence/absence of each individual item from the International Parkinson and Movement Disorder Society criteria. The overall accuracy/concordance rate, sensitivity, and specificity of the International Parkinson and Movement Disorder Society criteria compared with the expert gold standard were calculated. RESULTS: Of 434 patients diagnosed with PD, 94.5% met the International Parkinson and Movement Disorder Society criteria for probable PD (5.5% false-negative rate). Of 192 non-PD patients, 88.5% were identified as non-PD by the criteria (11.5% false-positive rate). The overall accuracy for probable PD was 92.6%. In addition, 59.3% of PD patients and only 1.6% of non-PD patients met the International Parkinson and Movement Disorder Society criteria for clinically established PD. In comparison, United Kingdom Brain Bank criteria had lower sensitivity (89.2%, P = 0.008), specificity (79.2%, P = 0.018), and overall accuracy (86.4%, P < 0.001). Diagnostic accuracy did not differ according to age or sex. Specificity improved as disease duration increased. CONCLUSIONS: The International Parkinson and Movement Disorder Society criteria demonstrated high sensitivity and specificity compared with the gold standard, expert diagnosis, with sensitivity and specificity both higher than United Kingdom Brain Bank criteria. © 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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.000 |
| 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".