Evidence map›Paper›PMID 31358792›Full record

ArticleScientific reports2019

Screening older adults for amnestic mild cognitive impairment and early-stage Alzheimer's disease using upper-extremity dual-tasking.

Nima Toosizadeh, Hossein Ehsani, Christopher Wendel, Edward Zamrini, Kathy O' Connor, Jane Mohler

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
3.6field-weighted citation impact, top 7% 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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 48 citations in OpenAlex.

  1. Pooled it
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  8. Differences in brain function entropy due to cognitive impairment: Application of functional near infrared spectroscopy measures during dual-tasking.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2025
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  20. Brain function complexity during dual-tasking is associated with cognitive impairment and age.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2022
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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

6 authors at 3 institutions in 1 country.

Nima ToosizadehDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, USA. ntoosizadeh@aging.arizona.edu.
Hossein EhsaniDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, USA.
Christopher WendelArizona Center on Aging (ACOA), Department of Medicine, University of Arizona, College of Medicine, Tucson, AZ, USA.
Edward ZamriniBanner Sun Health Research Institute, Sun City, AZ, USA.
Kathy O' ConnorBanner Sun Health Research Institute, Sun City, AZ, USA.
Jane MohlerDepartment of Biomedical Engineering, University of Arizona, Tucson, AZ, USA.
University of Arizona · USBanner Sun Health Research Institute · USUniversity of Utah · US

Funding

MCI and Alzheimer's Disease Screening using Upper-extremity Dual-taskR21AG055852 · NIA · UNIVERSITY OF ARIZONA · PI MOHLER, MARTHA JANE, TOOSIZADEH, NIMA · 2017 to 2018
$431k
NIA NIH HHS R21 AG055852U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) 1 R21 AG055852-01
6 · The paper itself

Abstract

The purpose of the current study was to develop an objective tool based on dual-task performance for screening early-stage Alzheimer's disease (AD) and mild cognitive impairment (MCI of the Alzheimer's type). Dual-task involved a simultaneous execution of a sensor-based upper-extremity function (UEF) motor task (normal or rapid speed) and a cognitive task of counting numbers backward (by ones or threes). Motor function speed and variability were recorded and compared between cognitive groups using ANOVAs, adjusted for age, gender, and body mass index. Cognitive indexes were developed using multivariable ordinal logistic models to predict the cognitive status using UEF parameters. Ninety-one participants were recruited; 35 cognitive normal (CN, age = 83.8 ± 6.9), 34 MCI (age = 83.9 ± 6.6), and 22 AD (age = 84.1 ± 6.1). Flexion number and sensor-based motion variability parameters, within the normal pace elbow flexion, showed significant between-group differences (maximum effect size of 1.10 for CN versus MCI and 1.39 for CN versus AD, p < 0.0001). Using these parameters, the cognitive status (both MCI and AD) was predicted with a receiver operating characteristic area under curve of 0.83 (sensitivity = 0.82 and specificity = 0.72). Findings suggest that measures of motor function speed and accuracy within a more practical upper-extremity test (instead of walking) may provide enough complexity for cognitive impairment assessment.

Indexed as

CognitionAgedAged, 80 and overAlzheimer DiseaseCognitive DysfunctionFemaleHumansMaleTask Performance and AnalysisUpper Extremity

Identifiers

PMID31358792
PMCPMC6662814
OpenAlexW2965957880

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.