montreal cognitive assessment moca cultural bias

#Montreal cognitive assessment moca cultural bias serial

The use of demographically and culturally appropriate correction norms for the evaluation of MoCA performances in acute stroke might represent an added value on the way of defining predictive scores in this setting. Normative values were firstly published by Conti and colleagues in 2004 (225 subjects, age range 60–80), then by Santangelo and colleagues in 2005 (415 subjects, age range 21–95), and recently by Aiello and colleagues in 2021 (579 subjects, age range 21–96).

Īt present, three general population normative datasets are available for the Italian version of the MoCA. The latter represent a relevant issue because MoCA normative studies have clearly showed the wide impact of demographic and cultural factors on its performance. In this peculiar setting, MoCA scores predictive of PSCI were variable across studies evaluating acute stroke patients, ranging from 19 to 22, and were based on raw scores. However, one unsolved issue in the use of MoCA in acute stroke patients concerns the definition of cut-offs able to predict patients at risk of persistent PSCI. ĭuring the last decade, several studies have tested Montreal Cognitive Assessment (MoCA) in acute stroke patients, and some encouraging evidence on its accuracy and predictive validity have made it one of the best candidates in this setting. Diagnostic accuracy of such a tool would have to reach a sensitivity ≥ 80% and a specificity ≥ 60% and should be evaluated with respect to a long-term PSCI diagnosis based on a comprehensive neuropsychological test battery. Because cognitive assessment in acute stroke must fulfill a feasibility criterion imposed by the setting and patients’ conditions, a multidomain, quick and easy to use, screening tool represents the gold standard.

#Montreal cognitive assessment moca cultural bias serial

The identification of patients at risk of persistent PSCI in the acute phase might help clinicians to early plan treatment options as well as serial cognitive assessments. In the chronic phase, cognitive impairment persists in approximately 50% of patients and is associated with poor functional and survival outcomes. In the acute phase, approximately 75% of stroke patients experience cognitive deficits. The cognitive profile of PSCI is heterogeneous and may include deficits in cortical functions (e.g., aphasia, neglect, apraxia, agnosia) as well as a dysexecutive syndrome caused by the dysfunction of integrated brain networks. Post-stroke cognitive impairment (PSCI) encompasses all forms and degrees of cognitive disorders whose onset is temporally related with a stroke. We calculated a new adjusted MoCA score predictive of PSCI in acute stroke patients to be further tested in larger studies. 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. 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 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. 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. MethodsĬonsecutive stroke patients were reassessed at 6–9 months with extensive neuropsychological and functional batteries for PSCI determination. (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. Despite preliminary evidence on MoCA accuracy, there is no consensus on its optimal score in the acute stroke setting to predict PSCI. Cognitive assessment in acute stroke is relevant for identifying patients at risk of persistent post-stroke cognitive impairment (PSCI).