Abstract 2640: Montreal Cognitive Assessment as a Short and Valuable Cognitive Evaluation in Acute Stroke
Bibliographic record
Abstract
Background: Stroke patients are at high risk of developing dementia, but no agreement exists on what instrument should be used in the acute stroke phase to detect patients at higher risk of cognitive decline. Our aims were to investigate: 1) the feasibility and applicability of the Montreal Cognitive Assessment (MoCA) test in the acute phase of stroke; 2) the predictive value of MoCA on the diagnosis of cognitive impairment. Methods: Consecutive stroke patients (ischemic or hemorrhagic) admitted to our Stroke Unit were evaluated with MoCA between 5-9 days after stroke. Pre-morbid functional and cognitive status were assessed by a structured interview to caregivers. Neuroimaging information was collected regarding index and pre-existing lesions (number and site of lesions, leukoaraiosis, atrophy). Clinical and neuropsychological follow-up was scheduled after 6 months. Results: From December 2009 to December 2010, out of 208 patients with stroke, 138 (66%) were enrolled [mean age 69.1+/-15.0; males 62%; mean NIHSS score 5.7+/-7.7]. Non-enrolment was mostly due to unfitting of the time window inclusion criteria. MoCA was applicable to 114/138 (83%) of enrolled patients and the mean score was 17.9+/-7.2. Multivariate analyses showed that non-applicability was associated with higher NIHSS scores [OR(95% CI)=1.4(1.2-1.7) for each point] and left sided lesions [OR(95% CI)=13.3(1.8-97.9)]. After 6 months, 73 patients (53%) have been re-assessed: 40 had cognitive impairment (6 dementia, 34 MCI), while the remaining 33 did not show any cognitive impairment. Using logistic regression model, considering clinical variables such as age, gender, years of schooling, NIHSS, and pre-morbid cognitive status, MoCA was the only predictor of cognitive decline [OR(95% CI)=1.4(1.2-1.6) for each test point]. When adding neuroimaging features to the model, the independent effect of MoCA was only slightly attenuated [OR(95% CI)=1.4(1.1-1.7)]. The other independent predictor of cognitive decline turned out to be leukoaraiosis severity [OR(95%CI)=0.4(0.2-0.9) for each point of the van Swieten scale]. Conclusions: Our preliminary results indicate that the MoCA is feasible and applicable in the acute phase of stroke. Moreover, MoCA seems to have a predictive effect on the diagnosis of cognitive decline at 6-month follow-up, making it a good candidate for cognitive screening in stroke setting.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".