Evidence map›Paper›PMID 40383729›Full record

SynthesisJournal of neurology2025

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

Xiaoqin Wei, Yuxiang Liu, Jia Li, Ying Zhu, Wenyuan Li, Yu Zhu, Longchun Hua, Jianxun Cao, Yuxia Ma

Abstract readComparative StudyMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xiaoqin Wei *Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Yuxiang Liu *Lanzhou Traditional Chinese Medicine Hospital of Orthopedics and Traumatology, Lanzhou, China.
Jia LiEvidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.
Ying ZhuEvidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.
Wenyuan LiEvidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.
Yu ZhuEvidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China.
Longchun HuaNursing Department, Gansu Provincial Hospital, Lanzhou, China.
Jianxun CaoNursing Department, Gansu Provincial Hospital, Lanzhou, China. 914960539@qq.com.
Yuxia MaEvidence-Based Nursing Center, School of Nursing, Lanzhou University, Lanzhou, China. yuxiama@lzu.edu.cn.ORCID http://orcid.org/0000-0001-8154-8198

Funding

Gansu Province Health Care Industry Research Project GSWSHL2020-17Gansu Province Health Care Industry Research Project GSWSHL2024-07Gansu Provincial Key R&D Programme Project 23YFFA0006National Nature Science Foundation of China 72474092
6 · The paper itself

Abstract

background and purposePost-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.

methodsEmbase, 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.

results9 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).

conclusionNo 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.

Indexed as

Cognitive DysfunctionMental Status and Dementia TestsStrokeHumansSensitivity and SpecificityDiagnostic accuracyMeta‑analysisMini-mental state examinationMontreal cognitive assessmentPost-stroke cognitive impairment

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.