LANGUAGE DYSFUNCTION IN MOTOR NEURON DISEASE: COGNITIVE FEATURES AND SCREENING SENSITIVITY
Notice bibliographique
Résumé
Motor neuron disease (MND) is a set of neuromuscular diseases that affect the upper and/or lower motor neurons, resulting in progressive disability. Amyotrophic lateral sclerosis (ALS) and Primary lateral sclerosis (PLS) are two forms of MND that both involve upper motor neuron degeneration, which can also accompany extra-motor changes in cognitive, behavioral, and/or emotional functioning for some individuals. Characterization of the cognitive profile of MND is still evolving, with growing interest in cognitive subtypes. The development of cognitive screens targeted to the MND cognitive profile aim to provide efficient and accurate brief assessments. However, empirical evaluation of tailored MND cognitive screens is needed for cross-validation independent of tests’ original developers. The present study addresses the cognitive profile of MND and the utility of brief cognitive screens with a focus on impairments in the language domain. The two primary aims include: (1) comprehensive assessment and characterization of language dysfunction in MND, and (2) empirical evaluation of brief cognitive screens with regard to detecting language impairments.\nForty-one patients with MND (ALS n = 36; PLS n = 5) were administered a comprehensive language battery to classify cognitive impairment (MND/ALSci; Strong et al., 2017) in the language domain and/or verbal fluency. Patients also completed two tailored cognitive screens [ALS Cognitive Behavioral Screen (ALS-CBS), Edinburgh Cognitive and Behavioral ALS Screen (ECAS)] and one general screen (Montreal Cognitive Assessment; MoCA).\nThe current preliminary results suggest language dysfunction in MND is characterized by prominent difficulties with word retrieval (confrontation naming) and/or syntax comprehension. However, evidence of reduced word production resembling nonfluent/agrammatic aphasia was not found. In total, 19.5% of the sample met criteria for MND/ALSci in the language domain (n = 8, all ALS); 22.0% met criteria for MND/ALSci in the verbal fluency domain (n = 9). Patients were classified into three subgroups, those with broad language impairments (ALSci-L n = 4, 9.8%), phonemic fluency impairments (MNDci-VF n = 5, 12.2%), or both impairments (ALSci-L+VF n = 4, 9.8%). Results also revealed existing challenges in accurately classifying patients with language dysfunction using brief cognitive screens. The ECAS Language subscore offered limited classification of broad language impairments in the present MND sample (sensitivity 50%, specificity 70%). Among the broader cognitive screens, sensitivities to language impairments were: ALS-CBS (100%), ECAS ALS-Specific Score (75%), and MoCA (71%). Convergent validity was demonstrated between outcomes on the ALS-CBS and ECAS ALS-Specific Score (rФ = .59). Discriminant validity was also demonstrated between outcomes on ALS-CBS compared to the MoCA (rФ = .11).\nFuture research is needed to assess whether language dysfunction reflects a distinct MND cognitive phenotype(s) and potential relationships with disease prognosis. Naming and syntax comprehension may be fruitful language screening targets for future research.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
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| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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