Evidence map›Paper›PMID 36337480›Full record

ArticleFrontiers in psychology2022

Comparison of three cognitive assessment methods in post-stroke aphasia patients.

Zhijie Yan, Shuo Xu, Dongshuai Wei, Xinyuan He, Chong Li, Yongli Zhang, Mengye Chen, Jingna Zhang, Xiaofang Li, Qing Yang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 12 citations in OpenAlex.

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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

11 authors at 3 institutions in 1 country.

Zhijie YanDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Shuo XuDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Dongshuai WeiDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Xinyuan HeDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Chong LiDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Yongli ZhangDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Mengye ChenDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Jingna ZhangDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Xiaofang LiDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.
Qing YangDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Jie JiaDepartment of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Fudan University · CNHuashan Hospital · CNXinxiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The cognitive level of post-stroke aphasia (PSA) patients is generally lower than non-aphasia patients, and cognitive impairment (CI) affects the outcome of stroke. However, for different types of PSA, what kind of cognitive assessment methods to choose is not completely clear. We investigated the Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), and the Non-language-based Cognitive Assessment (NLCA) to observe the evaluation effect of CI in patients with fluent aphasia (FA) and non-fluent aphasia (NFA). Methods: 92 stroke patients were included in this study. Demographic and clinical data of the stroke group were documented. The language and cognition were evaluated by Western Aphasia Battery (WAB), MoCA, MMSE, and NLCA. PSA were divided into FA and NFA according to the Chinese aphasia fluency characteristic scale. Pearson's product-moment correlation coefficient test and multiple linear regression analysis were performed to explore the relationship between the sub-items of WAB and cognitive scores. The classification rate of CI was tested by Pearson's Chi-square test or Fisher's exact test. Results: The scores of aphasia quotient (AQ), MoCA, MMSE, and NLCA in NFA were lower than FA. AQ was positively correlated with MoCA, MMSE, and NLCA scores. Stepwise multiple linear regression analysis suggested that naming explained 70.7% of variance of MoCA and 79.9% of variance of MMSE; comprehension explained 46.7% of variance of NLCA. In the same type of PSA, there was no significant difference in the classification rate. The classification rate of CI in NFA by MoCA and MMSE was higher than that in FA. There was no significant difference in the classification rate of CI between FA and NFA by NLCA. Conclusion: MoCA, MMSE, and NLCA can be applied in FA. NLCA is recommended for NFA.

Indexed as

cognitive impairmentfluent aphasiaNLCAnon-fluent aphasiapost-stroke aphasia

Identifiers

PMID36337480
PMCPMC9631299
OpenAlexW4306867617

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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.