Early Cognitive Assessment Following Acute Stroke: Feasibility and Comparison between Mini-Mental State Examination and Montreal Cognitive Assessment

Suda, Satoshi; Muraga, Kanako; Ishiwata, Akiko; Nishimura, Takuya; Aoki, Junya; Kanamaru, Takuya; Suzuki, Kentaro; Sakamoto, Yuki; Katano, Tayo; Nagai, Kiyohisa; Hatake, Seira; Satoi, Sera; Matsumoto, Noriko; Nito, Chikako; Nishiyama, Yasuhiro; Mishina, Masayoshi; Kimura, Kazumi

doi:10.1016/j.jstrokecerebrovasdis.2020.104688

Cited by 22 publications

(13 citation statements)

References 22 publications

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“…After the assessment, the scores were summed to yield a total score of 30 points. If the duration of education was less than 12 years, 1 point was added, and less than 26 points was regarded as a cognitive impairment [16]. The assessment was performed by an experienced neurologist.…”

Section: Assessment Of Cognitive Functionmentioning

confidence: 99%

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Liu

et al. 2021

Neurological Research

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Objective: The purpose of our study was to distinguish the changes in the microstructure of the cingulate cortex in patients with mild cognitive impairment (MCI) induced by cerebral small vessel disease (CSVD). Method: 80 patients were diagnosed with CSVD in this study, including 55 patients with MCI and 25 patients without MCI. Diffusion kurtosis imaging (DKI) and Montreal cognitive assessment (MoCA) were performed in all patients. The anterior cingulate gyrus, posterior cingulate gyrus and middle cingulate gyrus were selected as the regions of interest, and some parameters were recorded. Results: Compared with the non-MCI group, the MCI group mainly showed obviously higher mean diffusion (MD) and radial diffusion (RD) values (P = 0.022 and P = 0.029) but lower fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK) and radial kurtosis (RK) values (P = 0.047, P = 0.001, P < 0.01, and P = 0.001, respectively) in the right anterior cingulate gyrus. Meanwhile, in the right posterior cingulate gyrus, the MCI group also showed higher axial diffusion (AD) and MD (P = 0.027 and P = 0.030) and lower AK (P = 0.014). Additionally, negative correlations of AD, MD, and RD with MoCA scores and positive correlations of FA, AK, MK and RK with MoCA scores were observed in some regions of the cingulate gyrus. Conclusions: DKI is a good method to examine microstructural damage in the cingulate cortex, and some parameters of DKI may be used as imaging biomarkers to detect early MCI in patients with CSVD.

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Section: Assessment Of Cognitive Functionmentioning

confidence: 99%

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Liu

et al. 2021

Neurological Research

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“…A subsequent study showed that the MMSE and MoCA were both good screening tools for cognitive impairment at 3 months post-stroke (Cumming et al, 2013 ). MoCA, on the other hand, was reported to be particularly useful to discern PSCI in patients whose cognitive deficits were undetectable with the MMSE (Suda et al, 2020 ). To compare the prognostic value of the MMSE and MoCA for the detection of cognitive impairment 3–6 months after stroke, a study was conducted to evaluate the MMSE and MoCA in the acute phase of stroke patients (Dong et al, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Mini-Mental State Examination and the Montreal Cognitive Assessment for Predicting Post-stroke Cognitive Impairment During the Acute Phase in Chinese Minor Stroke Patients

Zhu

Zhao

Fan

et al. 2020

Front. Aging Neurosci.

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Objective: To assess the value of the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) during acute phase in predicting post-stroke cognitive impairment (PSCI) at 3-6 months. Methods: We prospectively recruited 229 patients who had suffered their first-ever ischemic stroke. PSCI was determined in 104 of these patients by a comprehensive neuropsychological battery performed at 3-6 months. Receiver operating characteristic (ROC) curve analysis was then performed to compare the discriminatory ability of the MMSE and MoCA. Also, we applied a decision tree generated by the classification and regression tree methodology. Results: In total, 66 patients had PSCI when evaluated 3-6 months after the onset of minor stroke. Logistic regression analysis revealed that education, body mass index (BMI), and baseline MoCA scores were independently associated with PSCI. ROC curve analysis showed that the ability to predict PSCI was similar when compared between baseline MoCA scores [area under curve (AUC), 0.821; 95% confidence interval (CI), 0.743-0.898] and baseline MMSE scores (AUC, 0.809; 95% CI, 0.725-0.892, P = 0.75). Both MMSE and MoCA exhibited similar predictive values at their optimal cutoff points (MMSE ≤27; sensitivity, 0.682; specificity, 0.816; MoCA ≤21; sensitivity, 0.636; specificity, 0.895). Classification and regression tree-derived analysis yielded an AUC of 0.823 (sensitivity, 0.803; specificity, 0.842). Conclusion: When applied within 2 weeks of stroke, the MMSE and MoCA are both useful and have similar predictive value for PSCI 3-6 months after the onset of minor stroke.

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“…Several AD screening scales commonly used in clinical practice include the clock-drawing test (CDT), mini-mental state examination (MMSE), Montreal cognitive assessment (MOCA), and Alzheimer’s disease assessment scale (ADAS-COG), among others. [ 33 , 34 , 35 ]. Brodaty H. et al [ 36 ] argued that a clock map is a very effective test screening measure for detecting mild or moderate AD in the clinical population, with very low false-negative and false-positive rates.…”

Section: Related Workmentioning

confidence: 99%

An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer’s Disease

Sun

Wang

Liu

2021

Sensors

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The early diagnosis of Alzheimer’s disease (AD) can allow patients to take preventive measures before irreversible brain damage occurs. It can be seen from cross-sectional imaging studies of AD that the features of the lesion areas in AD patients, as observed by magnetic resonance imaging (MRI), show significant variation, and these features are distributed throughout the image space. Since the convolutional layer of the general convolutional neural network (CNN) cannot satisfactorily extract long-distance correlation in the feature space, a deep residual network (ResNet) model, based on spatial transformer networks (STN) and the non-local attention mechanism, is proposed in this study for the early diagnosis of AD. In this ResNet model, a new Mish activation function is selected in the ResNet-50 backbone to replace the Relu function, STN is introduced between the input layer and the improved ResNet-50 backbone, and a non-local attention mechanism is introduced between the fourth and the fifth stages of the improved ResNet-50 backbone. This ResNet model can extract more information from the layers by deepening the network structure through deep ResNet. The introduced STN can transform the spatial information in MRI images of Alzheimer’s patients into another space and retain the key information. The introduced non-local attention mechanism can find the relationship between the lesion areas and normal areas in the feature space. This model can solve the problem of local information loss in traditional CNN and can extract the long-distance correlation in feature space. The proposed method was validated using the ADNI (Alzheimer’s disease neuroimaging initiative) experimental dataset, and compared with several models. The experimental results show that the classification accuracy of the algorithm proposed in this study can reach 97.1%, the macro precision can reach 95.5%, the macro recall can reach 95.3%, and the macro F1 value can reach 95.4%. The proposed model is more effective than other algorithms.

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Early Cognitive Assessment Following Acute Stroke: Feasibility and Comparison between Mini-Mental State Examination and Montreal Cognitive Assessment

Cited by 22 publications

References 22 publications

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Evaluation of the Mini-Mental State Examination and the Montreal Cognitive Assessment for Predicting Post-stroke Cognitive Impairment During the Acute Phase in Chinese Minor Stroke Patients

An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer’s Disease

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