Evidence map›Paper›PMID 37305744›Full record

SynthesisFrontiers in neurology2023

Can we trust computers to assess the cognition of stroke patients? A systematic review.

Qi Zhang, Jia-Hang Wei, Xue Fu, Xin Liu, Xin-Yi Li, Wei Liu, Zhong-Liang Liu, Xiao-Qin Duan, Bin Zheng

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

9 authors.

Qi Zhang *Department of Rehabilitation Medicine, Jilin University Second Hospital, Changchun, China.
Jia-Hang Wei *Jilin University, Changchun, China.
Xue Fu *Changchun University of Chinese Medicine, Changchun, China.
Xin LiuSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
Xin-Yi LiDepartment of Rehabilitation Medicine, Jilin University Second Hospital, Changchun, China.
Wei LiuDepartment of Rehabilitation Medicine, Jilin University Second Hospital, Changchun, China.
Zhong-Liang LiuDepartment of Rehabilitation Medicine, Jilin University Second Hospital, Changchun, China.
Xiao-Qin DuanDepartment of Rehabilitation Medicine, Jilin University Second Hospital, Changchun, China.
Bin ZhengSurgical Simulation Research Lab, Department of Surgery, University of Alberta, Edmonton, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To summarize the classification of computerized cognitive assessment (CCA) tools for assessing stroke patients, to clarify their benefits and limitations, and to reveal strategies for future studies on CCA tools. Methods: A literature review was performed using PubMed, Embase, Scopus, JAMA Network, Cochrane Library and PsycINFO databases from January 1st, 2010, to August 1st, 2022. Two authors independently screened the literature following the same criteria, evaluated the study quality, and collected data from the articles. Results: A total of 8,697 papers were acquired from the six databases. A total of 74 potentially eligible articles were selected for review. Of these, 29 articles were not relevant to this research, 3 were reviews, 2 were not written in English, and 1 was on an ongoing trial. By screening the references of the reviews, 3 additional articles were included in this study. Thus, a total of 42 articles met the criteria for the review. In terms of the CCA tools analyzed in these studies, they included five types: virtual reality (VR)-based, robot-based, telephone-based, smartphone-based, and computer-based cognitive assessments. Patients' stages of the disease ranged from the subacute phase and rehabilitation phase to the community phase. A total of 27 studies supported the effectiveness of CCA tools, while 22 out of 42 articles mentioned their benefits and 32 revealed areas for future improvement of CCA tools. Conclusions: Although the use of CCA tools for assessing the cognition of post-stroke patients is becoming popular, there are still some limitations and challenges of using such tools in stroke survivors. More evidence is thus needed to verify the value and specific role of these tools in assessing the cognitive impairment of stroke patients.

Indexed as

cognitive assessment screening instrumentcognitive impairmentscomputer-aided designreviewstroke

Identifiers

PMID37305744
PMCPMC10248476

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.