The Montreal Cognitive Assessment: A screening tool for mild cognitive impairment in REM sleep behavior disorder
Bibliographic record
Abstract
Mild cognitive impairment (MCI) is a frequent feature in idiopathic REM sleep behavior disorder (RBD), a sleep disturbance that can be a preclinical stage of Parkinson's disease or Lewy body dementia. We evaluated the sensitivity and specificity of two brief screening tools, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), in detecting MCI in idiopathic RBD. Thirty-eight idiopathic RBD patients underwent a comprehensive neuropsychological assessment, including the MoCA and the MMSE. Receiver operating characteristic curves were created for the MoCA and the MMSE to assess their ability to identify MCI in idiopathic RBD patients, with neuropsychological assessment as the gold standard. For the MoCA, a normality cutoff of 26 yielded the best balance between sensitivity (76%) and specificity (85%) with a correct classification of 79%. For the MMSE, the optimal normality cutoff was 30, with a sensitivity of 84% and a specificity of 54% and a correct classification of 74%. The MoCA is superior to the MMSE in detecting MCI in idiopathic RBD patients, showing good sensitivity and very good specificity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".