Validity of the Chinese version of the Montreal Cognitive Assessment (MoCA) 5-minute protocol for patients with stroke
Bibliographic record
Abstract
Abstract Background and propose The aim of the present study is to examine the validity of 2 Chinese versions of the short-form Montreal Cognitive Assessment (MoCA) in patients with stroke.Methods A prospective observational study was conducted which included patients with stroke as compared to healthy controls. The Chinese version of the Montreal Cognitive Assessment 5-minute protocol (MoCA 5-min protocol), National Institute for Neurological Disorders and Stroke and Canadian Stroke Network 5-minute Protocol (NINDS-CSN 5-min protocol), and Neurobehavioural Cognitive Status Examination (NCSE) were administered to each participant.Results A total of 54 patients with stroke and 27 healthy controls were enrolled in this study. We identified patients with cognitive impairments using the NCSE, and found that the 5-min protocol was equivalent to the MoCA in differentiating patients with cognitive impairments from those without (area under the receiver operating characteristic curve, AUC, of 0.948 for the MoCA 5-min protocol v.s. 0.984 for MoCA, P = 0.097); however, the NINDS-CSN 5-min protocol was less effective than MoCA in differentiating patients with cognitive impairments from those without (AUC of 0.925 for the NINDS CSN 5-min protocol v.s. 0.984 for MoCA, P = 0.027). These three assessments demonstrated equal performance in differentiating patients with stroke from controls.Conclusions The Chinese version of the MoCA 5-min protocol can be used as a valid screening for patients with stroke.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".