Validación de la versión española de la Escala Cognitiva de Montreal (MoCA) como herramienta de cribado de deterioro cognitivo asociado a la esclerosis múltiple
Bibliographic record
Abstract
Las baterías neuropsicológicas empleadas tradicionalmente para el diagnóstico del deterioro cognitivo (DC) en la esclerosis múltiple son pruebas complejas que conllevan mucho tiempo. Se necesitan test más simples para detectar el DC en la práctica clínica diaria. Evaluar la validez diagnóstica y la fiabilidad de la escala Montreal Cognitive Assessment (MoCA) como herramienta de cribado de DC en la esclerosis múltiple frente a la Batería Neuropsicológica Breve. Se seleccionaron 52 pacientes (61,5% mujeres, edad media [desviación estándar] 41,7 [11,5] años). Se analizaron la fiabilidad (consistencia interna, interobservador y test-retest) y la validez de constructo (análisis factorial, coeficiente de correlación de Pearson y coeficiente de determinación) y de criterio (curva ROC, sensibilidad, especificidad, acuerdo global, valores predictivos positivo y negativo, cocientes de probabilidad positivo y negativo y nomograma de Fagan). La prevalencia de DC fue del 21,2% según la Batería Neuropsicológica Breve y del 25% según el MoCA. El MoCA mostró buena consistencia interna (alfa de Cronbach 0,822) y buena fiabilidad interobservador y test-retest (coeficiente de correlación intraclase de 0,80 y 0,96, respectivamente). El coeficiente de correlación entre la puntuación total de la Batería Neuropsicológica Breve y el MoCA fue de 0,82. El punto óptimo de corte en la curva ROC fue 25-26, con una sensibilidad del 91% y una especificidad del 93%. El MoCA es una herramienta de cribado válida y fiable para la detección de DC en pacientes con esclerosis múltiple. The neuropsychological batteries traditionally used for the assessment of cognitive impairment (CI) in patients with multiple sclerosis are complex tests requiring a long time to administer. Simpler tests are needed to detect cognitive impairment in daily clinical practice. We aimed to evaluate the diagnostic validity and reliability of the Montreal Cognitive Assessment (MoCA) test as a screening tool for CI in patients with multiple sclerosis, as compared against the Brief Neuropsychological Battery. We recruited 52 patients with multiple sclerosis (61.5% women; mean age [standard deviation]: 41.7 [11.5] years). We analysed the reliability (internal consistency, interobserver reliability, and test-retest reliability), construct validity (factor analysis, Pearson correlation coefficient, and coefficient of determination), and criterion validity (ROC curve, sensitivity, specificity, total agreement, positive and negative predictive values, positive and negative likelihood ratios, and Fagan nomogram) of the MoCA test in this population. The prevalence of CI was 21.2% according to findings from the Brief Neuropsychological Battery, and 25% according to the MoCA test. The MoCA test showed good internal consistency (Cronbach alpha, 0.822) and interobserver and test-retest reliability (intraclass correlation coefficient 0.80 and 0.96, respectively). The correlation coefficient between total Brief Neuropsychological Battery and MoCA test scores was 0.82. The optimal cut-off point on the ROC curve was 25-26, yielding 91% sensitivity and 93% specificity. The MoCA test is a valid and reliable tool for screening for CI in patients with multiple sclerosis.
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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 | 0.011 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".