Screening for Cognitive Impairment After Stroke: Validation of the Chinese Version of the Quick Mild Cognitive Impairment Screen

MoCA and MMSE for the detection of post-stroke cognitive impairment: a comparative diagnostic test accuracy systematic review and meta‑analysis

BACKGROUND AND PURPOSE

Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke, which profoundly influences the quality of life of stroke survivors. The Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) are the two cognitive screening tools most widely used in stroke settings. Previous studies investigated the diagnostic accuracy of MoCA and MMSE but yielded controversial results. We conducted this study to compare the diagnostic accuracy of MoCA with MMSE for PSCI.

METHODS

Embase, PubMed, CINAHL, Web of Science, and The Cochrane Library were searched until August 17, 2024 for diagnostic accuracy studies comparing MoCA and MMSE. Data extraction was performed by two independent researchers. Risk of bias and applicability assessment was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Coupled forest plots and hierarchical summary receiver operating characteristic (hsROC) curves were created in R statistical software.

RESULTS

9 studies with 1,135 patients were included in this review. Most studies were at high risk of bias. MoCA displayed a pooled sensitivity of 0.80 (95% CI 0.72 to 0.86) and specificity of 0.79 (95% CI 0.71 to 0.85). MMSE displayed a sensitivity and specificity of 0.76 (95% CI 0.71 to 0.81) and 0.78 (95% CI 0.73 to 0.83), respectively. No difference was shown between these modalities (SEN p = 0.36, SPE p = 0.80).

CONCLUSION

No difference was observed between MoCA and MMSE in the detection of PSCI. We recommend both screeners be considered for the detection of PSCI based on the purpose of the test and by other metrics, such as acceptability and feasibility. Although it should be noted MoCA and MMSE were cognitive screening tools in stroke settings and not a substitute for detailed clinical assessment.

Validation of the Quick Mild Cognitive Impairment Screen in an American Sample of Patients With Mild Cognitive Impairment and Mild Dementia

OBJECTIVE

Early detection of cognitive impairment is critical for patient outcomes, yet cognitive impairment is under identified in primary care settings largely due to time constraints. The Quick Mild Cognitive Impairment (Qmci) screen was developed to address the need for a short cognitive screening instrument (< 5 min) that is sensitive to early cognitive change but has not been validated in the United States (US). The objective of this study was to examine the classification accuracy of the Qmci in participants from two memory specialty (e.g., secondary outpatient) clinics in the US.

METHODS

Participants were 152 older adults: 87 participants were cognitively normal (CN), 48 were diagnosed with mild cognitive impairment (MCI) and 17 were diagnosed with mild dementia (DEM). Classification accuracy of the Qmci and Mini Mental State Examination (MMSE) were compared in participants with and without cognitive impairment.

RESULTS

The Qmci demonstrated higher classification accuracy in differentiating CN from cognitively impaired participants (i.e., MCI and DEM) (AUC = 0.82) than the MMSE (AUC = 0.77). The optimal cut-off score for the Qmci was < 67, which achieved a sensitivity of 79% and specificity of 80%. The optimal MMSE cut-off score was < 27, which achieved a sensitivity of 97% and specificity of 43%.

CONCLUSIONS

The Qmci is a valid cognitive screening instrument for detecting early stages of cognitive impairment in memory clinic samples in the US. Its short administration time and increased specificity for detecting MCI make it an attractive option for use in primary care settings. Further validation of the Qmci is needed, specifically within primary care settings.

Diagnostic accuracy, reliability, and construct validity of the German quick mild cognitive impairment screen

BACKGROUND

Early detection of cognitive impairment is among the top research priorities aimed at reducing the global burden of dementia. Currently used screening tools have high sensitivity but lack specificity at their original cut-off, while decreasing the cut-off was repeatedly shown to improve specificity, but at the cost of lower sensitivity. In 2012, a new screening tool was introduced that aims to overcome these limitations - the Quick mild cognitive impairment screen (Qmci). The original English Qmci has been rigorously validated and demonstrated high diagnostic accuracy with both good sensitivity and specificity. We aimed to determine the optimal cut-off value for the German Qmci, and evaluate its diagnostic accuracy, reliability (internal consistency) and construct validity.

METHODS

We retrospectively analyzed data from healthy older adults (HOA; n = 43) and individuals who have a clinical diagnosis of 'mild neurocognitive disorder' (mNCD; n = 37) with a biomarker supported characterization of the etiology of mNCD of three studies of the 'Brain-IT' project. Using Youden's Index, we calculated the optimal cut-off score to distinguish between HOA and mNCD. Receiver operating characteristic (ROC) curve analysis was performed to evaluate diagnostic accuracy based on the area under the curve (AUC). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Reliability (internal consistency) was analyzed by calculating Cronbach's α. Construct validity was assessed by analyzing convergent validity between Qmci-G subdomain scores and reference assessments measuring the same neurocognitive domain.

RESULTS

The optimal cut-off score for the Qmci-G was ≤ 67 (AUC = 0.96). This provided a sensitivity of 91.9% and a specificity of 90.7%. The PPV and NPV were 89.5% and 92.9%, respectively. Cronbach's α of the Qmci-G was 0.71 (CI95% [0.65 to 0.78]). The Qmci-G demonstrated good construct validity for subtests measuring learning and memory. Subtests that measure executive functioning and/or visuo-spatial skills showed mixed findings and/or did not correlate as strongly as expected with reference assessments.

CONCLUSION

Our findings corroborate the existing evidence of the Qmci's good diagnostic accuracy, reliability, and construct validity. Additionally, the Qmci shows potential in resolving the limitations of commonly used screening tools, such as the Montreal Cognitive Assessment. To verify these findings for the Qmci-G, testing in clinical environments and/or primary health care and direct comparisons with standard screening tools utilized in these settings are warranted.

Screening for post-stroke neurocognitive disorders in diverse populations: A systematic review

Objective: Although neurocognitive disorders (NCD) are common post-stroke, many populations do not have adapted cognitive screens and cut-offs. We therefore reviewed the appropriateness of the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and Oxford Cognitive Screen (OCS) for diagnosing NCD in culturally diverse stroke populations. Method: Using an extensive search string, diagnostic accuracy studies for MMSE, MoCA and OCS in the stroke population were retrieved from four databases. We compared translations and adaptations, adjustments in scores and cut-offs, and their diagnostic accuracy. Results: The search resulted in 28 MMSE, 39 MoCA and 5 OCS-studies in 13 western, educated, industrialized, rich and democratic (WEIRD) and 4 other countries. There was a lack of studies on South-American, African, and non-Chinese-Asian populations. All three tests needed adaptation for less WEIRD populations and populations with languages with non-Latin features. Optimal MMSE and OCS subtest cut-offs were similar across WEIRD and less WEIRD populations, whereas optimal MoCA cut-offs appeared lower for less WEIRD populations. The use of adjusted scores resulted in different optimal cut-offs or similar cut-offs with better accuracy. Conclusions: MoCA, MMSE and OCS are promising tools for diagnosing post-stroke-NCD. For culturally diverse populations, translation, adaptation and adjusted scores or cut-offs are necessary for diagnostic accuracy. Available studies report scarcely about their sample's cultural background and there is a lack of diagnostic accuracy studies in less WEIRD or culturally diverse populations. Future studies should report more cultural characteristics of their sample to provide better insight into the tests' accuracy in culturally diverse populations.

Which cutoff value of the Montreal Cognitive Assessment should be used for post-stroke cognitive impairment? A systematic review and meta-analysis on diagnostic test accuracy

BACKGROUND

Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke. The Montreal Cognitive Assessment (MoCA), as a brief cognitive impairment screening tool, is widely used in stroke survivors. However, some studies have suggested that the use of the universal cutoff value of 26 may be inappropriate for detecting cognitive impairments in stroke settings.

AIM

We conducted this study to identify the optimal cutoff value of the MoCA in screening for PSCI.

METHODS

PubMed, CINAHL, Embase, the Cochrane Library, and Web of Science were searched for eligible studies until March 23, 2023. All studies were screened by two independent researchers. The quality of each article was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate mixed-effects model was used to pool sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the summary receiver operating characteristic curve.

RESULTS

Twenty-four studies with a total of 4231 patients were included in this review. Despite the lack of evidence of publication bias, a high degree of heterogeneity was observed. A meta-analysis revealed that a cutoff value of 21/22 yielded the best diagnostic accuracy. The optimal cutoff varied in different regions, stroke types, and stroke phases as well.

CONCLUSION

The optimal cutoff of MoCA was 21/22 for stroke populations rather than the initially recommended cutoff of 26. A revised (lower) cutoff should be considered for stroke survivors.