Prediction of post-stroke cognitive impairment by Montreal Cognitive Assessment (MoCA) performances in acute stroke: comparison of three normative datasets.
Acute stroke
Montreal Cognitive Assessment
Neuropsychology
Normality cut-off
Post-stroke cognitive impairment
Journal
Aging clinical and experimental research
ISSN: 1720-8319
Titre abrégé: Aging Clin Exp Res
Pays: Germany
ID NLM: 101132995
Informations de publication
Date de publication:
Aug 2022
Aug 2022
Historique:
received:
23
03
2022
accepted:
29
03
2022
pubmed:
21
4
2022
medline:
19
7
2022
entrez:
20
4
2022
Statut:
ppublish
Résumé
Cognitive assessment in acute stroke is relevant for identifying patients at risk of persistent post-stroke cognitive impairment (PSCI). Despite preliminary evidence on MoCA accuracy, there is no consensus on its optimal score in the acute stroke setting to predict PSCI. (1) To explore whether the application of different normative datasets to MoCA scores obtained in the acute stroke setting results in variable frequency of patients defined as cognitively impaired; (2) to assess whether the normality cut-offs provided by three normative datasets predict PSCI at 6-9 months; (3) to calculate alternative MoCA cut-offs able to predict PSCI. Consecutive stroke patients were reassessed at 6-9 months with extensive neuropsychological and functional batteries for PSCI determination. Out of 207 enrolled patients, 118 (57%) were followed-up (mean 7.4 ± 1.7 months), and 77 of them (65%) received a PSCI diagnosis. The application of the normality thresholds provided by the 3 normative datasets yielded to variable (from 28.5% to 41%) rates of patients having an impaired MoCA performance, and to an inadequate accuracy in predicting PSCI, maximizing specificity instead of sensitivity. In ROC analyses, a MoCA score of 22.82, adjusted according to the most recent normative dataset, achieved a good diagnostic accuracy in predicting PSCI. The classification of acute stroke patients as normal/impaired based on MoCA thresholds proposed by general population normative datasets underestimated patients at risk of persistent PSCI. We calculated a new adjusted MoCA score predictive of PSCI in acute stroke patients to be further tested in larger studies.
Sections du résumé
BACKGROUND
BACKGROUND
Cognitive assessment in acute stroke is relevant for identifying patients at risk of persistent post-stroke cognitive impairment (PSCI). Despite preliminary evidence on MoCA accuracy, there is no consensus on its optimal score in the acute stroke setting to predict PSCI.
AIMS
OBJECTIVE
(1) To explore whether the application of different normative datasets to MoCA scores obtained in the acute stroke setting results in variable frequency of patients defined as cognitively impaired; (2) to assess whether the normality cut-offs provided by three normative datasets predict PSCI at 6-9 months; (3) to calculate alternative MoCA cut-offs able to predict PSCI.
METHODS
METHODS
Consecutive stroke patients were reassessed at 6-9 months with extensive neuropsychological and functional batteries for PSCI determination.
RESULTS
RESULTS
Out of 207 enrolled patients, 118 (57%) were followed-up (mean 7.4 ± 1.7 months), and 77 of them (65%) received a PSCI diagnosis. The application of the normality thresholds provided by the 3 normative datasets yielded to variable (from 28.5% to 41%) rates of patients having an impaired MoCA performance, and to an inadequate accuracy in predicting PSCI, maximizing specificity instead of sensitivity. In ROC analyses, a MoCA score of 22.82, adjusted according to the most recent normative dataset, achieved a good diagnostic accuracy in predicting PSCI.
CONCLUSIONS
CONCLUSIONS
The classification of acute stroke patients as normal/impaired based on MoCA thresholds proposed by general population normative datasets underestimated patients at risk of persistent PSCI. We calculated a new adjusted MoCA score predictive of PSCI in acute stroke patients to be further tested in larger studies.
Identifiants
pubmed: 35441928
doi: 10.1007/s40520-022-02133-9
pii: 10.1007/s40520-022-02133-9
pmc: PMC9283135
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1855-1863Informations de copyright
© 2022. The Author(s).
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