Neurological Sciences

, Volume 39, Issue 4, pp 705–716 | Cite as

Diagnostic test accuracy of the Montreal Cognitive Assessment in the detection of post-stroke cognitive impairment under different stages and cutoffs: a systematic review and meta-analysis

  • Dan Shi
  • Xiao Chen
  • Zheng Li
Original Article


The purposes of this review were to give the optimal cutoffs of the Montreal Cognitive Assessment (MoCA) by comparing sensitivity and specificity under different cutoffs and compare the MoCA with other screening tools in post-stroke cognitive impairment (PSCI) determined by a neuropsychological evaluation. Articles were derived from a systematic search in PubMed, Web of science, Embase, and CINAHL and were assessed for internal validity by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The figure of risk of bias was made by Review Manager 5.3, and data of selected studies were synthesized by MetaDisc 1.4. Twelve diagnostic studies, involving 2130 patients, were included. The area under the curve (AUC) under cutoffs of 20v19, 21v20, and 26v25 are 0.90, 0.90, and 0.95, showing high predictive validity for PSCI screening within 1 month. When the sensitivity and specificity are equal important, the optimal cutoff is 20v19 (Youden Index = 0.58). Compared to the Mini-Mental State Examination (MMSE), the MoCA has higher sensitivity but lower specificity. The optimal cutoff differs in different stages of stroke. Both the MMSE and MoCA are appropriate screening tools for PSCI, and the use of these two tools should be in accordance with the aim of screening. The Addenbrooke’s Cognitive Examination-Revised (ACE-R) can act as a supplement for the MoCA.


Post-stroke cognitive impairment MoCA MMSE ACE-R Cutoff 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical statement

All analyses were based on previous published studies, thus no ethical approval and patient consent are required.


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Copyright information

© Springer-Verlag Italia S.r.l., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of NursingFudan UniversityShanghaiChina

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