Evidence map›Paper›PMID 33336432›Full record

ArticleGeriatrics & gerontology international2021

Usefulness of CogEvo, a computerized cognitive assessment and training tool, for distinguishing patients with mild Alzheimer's disease and mild cognitive impairment from cognitively normal older people.

Hajime Takechi, Hiroshi Yoshino

Abstract read
In one paragraph

Article in Geriatrics & gerontology international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Validation of the Computerized Cognitive Assessment Test: NNCT.International journal of environmental research and public health · 2022
    Article
  9. Article
  10. Observational
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

2 authors.

Hajime TakechiDepartment of Geriatrics and Cognitive Disorders, Fujita Health University School of Medicine, Toyoake, Japan.ORCID https://orcid.org/0000-0001-8618-9825
Hiroshi YoshinoDepartment of Geriatrics and Cognitive Disorders, Fujita Health University School of Medicine, Toyoake, Japan.ORCID https://orcid.org/0000-0003-2656-1482

Funding

a grant for promoting research from Fujita Health UniversityLife Science Institute, Inc.
6 · The paper itself

Abstract

aimThis study aimed to assess whether CogEvo, a computerized cognitive assessment and training tool, could distinguish patients with mild Alzheimer's disease and mild cognitive impairment from cognitively normal older people.

methodsThis cross-sectional study enrolled 166 participants with Alzheimer's disease, mild cognitive impairment and cognitively normal older people. In CogEvo, five types of cognitive tasks were carried out, and the z-scores were used as a composite score. Logistic regression and receiver operating characteristics analyses were then carried out to evaluate the usefulness of CogEvo in distinguishing between the three groups.

resultsCogEvo and Mini-Mental State Examination scores showed excellent correlation, and could significantly differentiate between the Alzheimer's disease, mild cognitive impairment and cognitively normal older people groups (Mini-Mental State Examination 20.4 ± 3.5, 25.5 ± 1.6 and 27.6 ± 2.0, respectively; CogEvo: -1.9 ± 0.9, -0.8 ± 0.8 and 0.0 ± 1.0, respectively; both P < 0.001 by analysis of variance). Logistic regression analysis adjusted for age, sex and years of education significantly differentiated the mild cognitive dysfunction group (mild cognitive impairment plus mild Alzheimer's disease; n = 78) from the cognitively normal group (n = 88) (P < 0.001), whereas receiver operating characteristics analysis showed moderate accuracy (area under the receiver operating characteristic curve 0.830).

conclusionsThese results suggest that CogEvo, a computerized cognitive assessment tool, is useful for evaluating early-stage cognitive impairment. Further studies are required to assess its effectiveness as a combination assessment and training tool. Geriatr Gerontol Int 2021; 21: 192-196.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedCognitionCross-Sectional StudiesHumansMental Status and Dementia TestsAlzheimer’s diseasecognitive trainingcomputerized cognitive assessmentdementiamild cognitive impairment

Identifiers

PMID33336432
PMCPMC7898622

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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.