Screening for cognitive impairment after stroke: Validation of the Chinese version of the Quick Mild Cognitive Impairment screen
Molloy, D William
AffiliationRónán O'Caoimh, Department of Geriatric Medicine, Mercy University Hospital, Grenville Place, Cork, T12 WE28, Ireland.
mild cognitive impairment
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CitationXu Y, Yi L, Lin Y, Peng S, Wang W, Lin W, Chen P, Zhang W, Deng Y, Guo S, Shi L, Wang Y, Molloy DW, O'Caoimh R. Screening for Cognitive Impairment After Stroke: Validation of the Chinese Version of the Quick Mild Cognitive Impairment Screen. Front Neurol. 2021 Mar 5;12:608188. doi: 10.3389/fneur.2021.608188.
JournalFrontiers in neurology
AbstractBackground: Screening for post-stroke cognitive impairment (PSCI) is necessary because stroke increases the incidence of and accelerates premorbid cognitive decline. The Quick Mild Cognitive Impairment (Qmci) screen is a short, reliable and accurate cognitive screening instrument but is not yet validated in PSCI. We compared the diagnostic accuracy of a Chinese version of the Qmci screen (Qmci-CN) compared with the widely-used Chinese versions of the Montreal Cognitive Assessment (MoCA-CN) and Mini-Mental State Examination (MMSE-CN). Methods: We recruited 34 patients who had recovered from a stroke in rehabilitation unit clinics in 2 university hospitals in China: 11 with post-stroke dementia (PSD), 15 with post-stroke cognitive impairment no dementia (PSCIND), and 8 with normal cognition (NC). Classification was made based on clinician assessment supported by a neuropsychological battery, independent of the screening test scores. The Qmci-CN, MoCA-CN, and MMSE-CN screens were administered randomly by a trained rater, blind to the diagnosis. Results: The mean age of the sample was 63 ± 13 years and 61.8% were male. The Qmci-CN had statistically similar diagnostic accuracy in differentiating PSD from NC, an area under the curve (AUC) of 0.94 compared to 0.99 for the MoCA-CN (p = 0.237) and 0.99 for the MMSE-CN (p = 0.293). The Qmci-CN (AUC 0.91), MoCA-CN (AUC 0.94), and MMSE-CN (AUC 0.79) also had statistically similar accuracy in separating PSD from PSCIND. The MoCA-CN more accurately distinguished between PSCIND and normal cognition than the Qmci-CN (p = 0.015). Compared to the MoCA-CN, the administration times of the Qmci-CN (329s vs. 611s, respectively, p < 0.0001) and MMSE-CN (280 vs. 611s, respectively, p < 0.0001) were significantly shorter. Conclusion: The Qmci-CN is accurate in identifying PSD and separating PSD from PSCIND in patients post-stroke following rehabilitation and is comparable to the widely-used MoCA-CN, albeit with a significantly shorter administration time. The Qmci-CN had relatively poor accuracy in identifying PSCIND from NC and hence may lack accuracy for certain subgroups. However, given the small sample size, the study is under-powered to show superiority of one instrument over another. Further study is needed to confirm these findings in a larger sample size and in other settings (countries and languages).
SponsorsGuangzhou Municipal Technological Major Tackling Plan Modern Industrial Technology Project of China (Grant No. 201802010039); the Guangdong Hopson-Pearl River Education Development Foundation (Grant No. H20190116202012724); National Natural Science Foundation of China (Grant Nos. 81601981 and 81472155).
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Except where otherwise noted, this item's license is described as Copyright © 2021 Xu, Yi, Lin, Peng, Wang, Lin, Chen, Zhang, Deng, Guo, Shi, Wang, Molloy and O'Caoimh.
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