Evidence map›Paper›PMID 31849821›Full record

ArticleFrontiers in neurology2019

Assessing Performance on Digital Clock Drawing Test in Aged Patients With Cerebral Small Vessel Disease.

Hóngyi Zhào, Wei Wei, Ellen Yi-Luen Do, Yonghua Huang

Abstract read
In one paragraph

Article in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 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

4 authors.

Hóngyi ZhàoDepartment of Neurology, Seventh Medical Center of PLA General Hospital, Beijing, China.
Wei WeiDepartment of Neurology, Seventh Medical Center of PLA General Hospital, Beijing, China.
Ellen Yi-Luen DoATLAS Institute, University of Colorado Boulder, Boulder, CO, United States.
Yonghua HuangDepartment of Neurology, Seventh Medical Center of PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The term small vessel disease (SVD) encompasses all the pathological processes that affect the small vessels of the brain, including small arteries and arterioles but also capillaries and small veins, which can result in multi-domain cognitive deficits. The digital clock drawing test (dCDT) has been proved to be a more useful assessment tool for cognitive disorders compared to traditional clock drawing test DT (tCDT) in many neuropsychological diseases. This study aimed to check whether this tool worked well in capturing some specific aspects of cognitive performance in aged patients with SVD. A total of 20 aged patients with high-burden SVD (severe-SVD), 10 aged patients with low burden SVD (low-SVD), and 10 age-matched (healthy) individuals were grouped according to Fazekas' score. The dCDT and a series of neuropsychological assessments were performed to evaluate the cognitive function of participants. severe-SVD patients showed higher air-time percentage and lower mean handwriting/drawing pressure on surface during drawing compared with low-SVD and healthy subjects. The linear regression analysis adjusted for age, gender and education showed that the air-time percentage during drawing correlated with the choice reaction test (CRT) and the digit symbol substitution test (DSST), and the mean handwriting/drawing pressure on surface showed a limited correlation with DSST. The data indicated that some early manifestations of cognitive deficits in aged patients with SVD could be detected using the dCDT with a brand-new perspective different from the tCDT.

Indexed as

agingassessmentdigital technologyexecutive functionsmall vessel disease

Identifiers

PMID31849821
PMCPMC6902025

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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.