Evidence map›Paper›PMID 33648444›Full record

ArticleBMC neurology2021

Consistency and applicability of different brief screen instrument of cognitive function in elderly population.

Lixia Lu, Lin Chen, Weiwen Wu, Yang Wang, Zhenbao Liu, Jun Xu, Qianhong Yang, Jun Zhao, Liangxian Liu, Hui Yu

Abstract read
In one paragraph

Article in BMC neurology, 2021. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Montreal Cognitive Assessment: Seeking a Single Cutoff Score May Not Be Optimal.Evidence-based complementary and alternative medicine : eCAM · 2021
    Article
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

10 authors.

Lixia Lu *Department of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Lin Chen *Department of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Weiwen WuDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China. wuweiwen6669@163.com.
Yang WangDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Zhenbao LiuDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Jun XuDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Qianhong YangDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Jun ZhaoDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Liangxian LiuDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.
Hui YuDepartment of Neurology, Qingpu Branch of Zhongshan Hospital, Fudan University, 1158 East of Park Road, Qingpu District, Shanghai, 201700, China.

Funding

Health Committee of Qingpu District W2017-06
6 · The paper itself

Abstract

backgroundScreening for cognitive impairment (CI) is often hampered by lack of consensus as to which screening instrument to use. The aim is to assess the consistence and applicability of different CI screening tools.

methodIn a cross-sectional study from October 2017 to September 2018 in 7 communities in Shanghai, China, elder (≧60) residential volunteers with no history of major cardiovascular diseases, cancers and other comorbidities known to affect cognitive functions were recruited. The participants underwent tests with 7 cognitive function screening instruments. Multivariate linear regressions were performed to test correlations between demographic characteristics, including gender, age, education, and marital status, with cognitive test scores. Mini-Mental State Examination (MMSE) score adjusted according to the correlation coefficients was used to detect CI with a cutoff of 24. Other cognitive function scores were compared between participants with and without CI. In addition, Pearson's correlation test was used to detect association between different test scores.

results172 participants with relatively low education levels were included. Age and education showed significant association with cognitive test scores. Using adjusted MMSE, 39.6% of participants were identified with CI, while the percentage was 87.2% when adjusted Montreal Cognitive Assessment (MoCA) with cutoff of 26 was used. Analysis of "abnormal" test scores showed that MMSE had the highest percentage of valid data (98.8%). MoCA and Isaacs test of Verbal Fluency (VF) score had correlation with most the other scores, while MMSE only significantly associated with VF and MoCA.

conclusionsMMSE may still present the most applicable tools for quick screen of cognitive functions, especially when environmental conditions may interfere with participants' attention.

Indexed as

Neuropsychological TestsAgedAged, 80 and overChinaCognitive DysfunctionCross-Sectional StudiesFemaleHumansMaleMass ScreeningMiddle AgedApplicabilityCognitive assessment screening instrumentCognitive dysfunctionConsistencyMini-mental state examination

Identifiers

PMID33648444
PMCPMC7919302

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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.