Detección del deterioro cognitivo con la Evaluación Cognitiva de Montreal en pacientes españoles con ictus minor o ataque isquémico transitorio
Bibliographic record
Abstract
Los síntomas de un ictus minor o un ataque isquémico transitorio (AIT) son leves y de corta duración. A pesar de la naturaleza pasajera de los síntomas focales y la ausencia de lesiones cerebrales visibles en algunos pacientes, muchos experimentan problemas cognitivos persistentes posteriormente. Nuestro objetivo es establecer el poder discriminativo del Montreal Cognitive Assessment (MoCA, «Evaluación Cognitiva de Montreal») en la detección del deterioro cognitivo (DC) dentro de los 90 días posteriores al AIT. Se incluyeron un total de 50 pacientes con ictus minor y AIT. Se les aplicó la prueba MoCA y una batería neuropsicológica formal. El DC se definió clínicamente según los hallazgos de las pruebas neuropsicológicas. La edad promedio de los pacientes seleccionados fue de 57,7 ± 8,0 años, siendo la mayoría de ellos varones (70,0%). Todos los pacientes tenían un nivel educativo igual o superior al primario. Treinta y siete (74,0%) sujetos presentaron DC. Mediante el análisis de la curva característica del receptor se obtuvo un punto de corte del test MoCA de 25 puntos para discriminar entre sujetos con y sin DC, siendo el área bajo la curva de 0,835 (intervalo de confianza del 95% [IC 95%] 0,720 a 0,949), la sensibilidad, del 78,4% (IC 95% 62,8-88,6%), la especificidad, del 76,9% (IC 95% 49,7-91,8%), el valor predictivo positivo, del 90,6% (IC 95% 81,0-95,6%) y el negativo, del 55,6% (IC 95% 39,5-70,4%). Más de la mitad de la muestra presentaba DC según lo determinado por la batería formal de pruebas neuropsicológicas. Un punto de corte de 25 en el MoCA es lo suficientemente sensible y específico para detectar DC tras un ictus minor o AIT y podría implementarse en la práctica clínica como método de cribado. The symptoms of minor stroke and transient ischemic attack (TIA) are temporary and mild. Despite the transient nature of the focal symptoms and the absence of visible brain lesions in some patients, many experience persistent cognitive problems subsequently. We aimed to establish the discriminant capacity of the Montreal Cognitive Assessment (MoCA) in screening for cognitive impairment (CI) within 90 days of TIA. A total of 50 patients with minor stroke or TIA were recruited. Patients were administered the MoCA test and a formal neuropsychological test battery. CI was defined clinically according to neuropsychological test findings. The average age of recruited patients was 57.7 ± 8.0 years; 70.0% were men; all patients had completed at least primary education. Thirty-seven patients (74.0%) presented CI. Receiver operating characteristic curve analysis obtained an optimal MoCA cut-off point of 25 for discriminating between patients with CI and those without, with an area under the curve of 0.835 (95% confidence interval [95% CI] 0.720-0.949), sensitivity of 78.4% (95% CI 62.8-88.6%), specificity of 76.9% (95% CI 49.7-91.8%), positive predictive value of 90.6% (95% CI 81.0-95.6%), and negative predictive value of 55.6% (95% CI 39.5-70.4%). More than half of the patients presented CI as determined by the formal battery of neuropsychological tests. A MoCA cut-off point of 25 is sufficiently sensitive and specific for detecting CI after minor stroke or TIA, and may be implemented as a screening technique in routine clinical practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".