Cut-off points of the Portuguese version of the Montreal Cognitive Assessment for cognitive evaluation in Parkinson’s disease
Bibliographic record
Abstract
The Movement Disorder Society has published some recommendations for dementia diagnosis in Parkinson disease (PD), proposing the Montreal Cognitive Assessment (MOCA) as a cognitive screening tool in these patients. However, few studies have been conducted assessing the Portuguese version of this test in Brazil (MOCA-BR). OBJECTIVE: the aim of the present study was to define the cut-off points of the MOCA-BR scale for diagnosing Mild Cognitive Impairment (PD-MCI) and Dementia (PD-D) in patients with PD. METHODS: this was a cross-sectional, analytic field study based on a quantitative approach. Patients were selected after a consecutive assessment by a neurologist, after an extensive cognitive evaluation, and were classified as having normal cognition (PD-N), PD-MCI or PD-D. The MOCA-BR was then applied and 89 patients selected. RESULTS: on the cognitive assessment, 30.3% were PD-N, 41.6% PD-MCI and 28.1% PD-D. The cut-off score on the MOCA-Br to distinguish PD-N from PD-D was 22.50 (95% CI 0.748-0.943) for sensitivity of 85.5% and specificity of 71.1%. The cut-off for distinguishing PD-D from MCI was 17.50 (95% CI 0.758-0.951) for sensitivity of 81.6% and specificity of 76%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".