Literature DB >> 23716072

Predictive value of MoCA in the acute phase of stroke on the diagnosis of mid-term cognitive impairment.

Emilia Salvadori1, Marco Pasi, Anna Poggesi, Guido Chiti, Domenico Inzitari, Leonardo Pantoni.   

Abstract

Post-stroke cognitive impairment (PSCI) includes all forms of cognitive decline that develop after stroke, even if not severe enough to fit the criteria of dementia. Our aims were to investigate the predictive value of a brief bedside examination (Montreal Cognitive Assessment, MoCA) in the acute phase of stroke on the diagnosis of mid-term PSCI, taking into account other clinical, cognitive, functional, and neuroimaging predictors. Consecutive patients admitted to a stroke unit were evaluated with MoCA between 5 and 9 days after stroke. At baseline, clinical, functional, and neuroimaging data were collected. Patients were reassessed between 6 and 9 months after stroke by means of an extensive neuropsychological and functional evaluation. Out of 137 enrolled stroke patients, 80 (58.4%) were followed up (mean age 68.2 ± 14.6 years, males 66%, mean NIHSS score 3.6 ± 4.8). PSCI was diagnosed in 47 patients (59%; 35 mild cognitive impairment, 12 dementia). Controlling for age, education, functional and cognitive pre-morbid status, stroke severity, and pre-existing lacunar infarcts, MoCA baseline score [OR (95% CI) = 1.4(1.1-1.8)] for each point] and leukoaraiosis severity [OR (95% CI) = 0.4(0.2-0.9)] for each point of the van Swieten scale] were independently associated with PSCI. Using a ROC analysis, a cut-off of 21 predicted the diagnosis of PSCI with 91.4 % sensitivity, 75.8 % specificity, 80 % positive predictive value, and 89.3 % negative predictive value. In a sample of mild stroke patients, MoCA seems to be a good predictor of mid-term PSCI, making it a possible candidate for a brief cognitive screening in the acute stroke setting.

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Year:  2013        PMID: 23716072     DOI: 10.1007/s00415-013-6962-7

Source DB:  PubMed          Journal:  J Neurol        ISSN: 0340-5354            Impact factor:   4.849


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