Longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in non-demented ALS patients.


Journal

European neurology
ISSN: 1421-9913
Titre abrégé: Eur Neurol
Pays: Switzerland
ID NLM: 0150760

Informations de publication

Date de publication:
20 Apr 2024
Historique:
received: 12 10 2023
accepted: 16 03 2024
medline: 22 4 2024
pubmed: 22 4 2024
entrez: 21 4 2024
Statut: aheadofprint

Résumé

The present study aimed at testing the longitudinal feasibility of the Montreal Cognitive Assessment (MoCA) in an Italian cohort of non-demented amyotrophic lateral sclerosis (ALS) patients. N=39 non-demented ALS patients were followed-up at a 5-to-10-month interval (M=6.8; SD=1.4) with the MoCA and the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). Practice effects, test-retest reliability and predictive validity (against follow-up ECAS scores) were assessed. Reliable change indices (RCIs) were derived via a regression-based approach by accounting for retest interval and baseline confounders (i.e., demographics, disease duration and severity and progression rate). At retest, 100% and 69.2% of patients completed the ECAS and the MoCA, respectively. Patients who could not complete the MoCA showed a slightly more severe and fast-progressing disease. The MoCA was not subject to practice effects (t(32)=-.80; p=.429) and was reliable at retest (ICC=.82). Moreover, baseline MoCA scores predicted the ECAS at retest. RCIs were successfully derived - with baseline MoCA scores being the only significant predictor of retest performances (ps<.001). As long as motor disabilities do not undermine its applicability, the MoCA appears to be longitudinally feasible at a 5-to-10-month interval in non-demented ALS patients. However, ALS-specific screeners - such as the ECAS - should be preferred whenever possible.

Identifiants

pubmed: 38643758
pii: 000538828
doi: 10.1159/000538828
doi:

Types de publication

News

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

S. Karger AG, Basel.

Auteurs

Classifications MeSH