Evidence map›Paper›PMID 41853180›Full record

SynthesisFrontiers in neurology

Effect of robot-assisted training on cognitive function in post-stroke patients: a meta-analysis.

Juan Wang, Man Ding, Chao Weng, Hui Cai

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Juan Wang *Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Man Ding *Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Chao Weng *Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Hui CaiDepartment of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: About 1/3 of stroke patients worldwide experience post-stroke cognitive impairment (PSCI). The management of cognitive function (CF) after stroke is an important issue that needs to be addressed. In recent years, robot-assisted training (RAT) has been widely used in the rehabilitation of CF, its intervention effect is still controversial. Therefore, this study was aimed at reporting the latest meta-analysis (MA) and evidence updates to compare the effects of RAT with traditional training (TT) on CF in post-stroke (PS) patients. Methods: Databases (PubMed, Embase, Cochrane Library and Web of Science) were retrieved to include randomized controlled trial articles that met the criteria. The intervention group used RAT, and the control group used TT. Outcome measures mainly included the Montreal Cognitive Assessment score (MoCA), and so on. Study screening, quality assessment, and data extraction were done separately by two investigators. The stability of results and potential sources of heterogeneity were explored by sensitivity and subgroup analyses. Data were pooled by RevMan 5.4 and STATA 15.0. Results: A total of 13 studies with 488 patients were included. The MA results showed that in PS patients, RAT significantly improved the MoCA score [SMD = 0.43, 95% CI (0.04-0.81), Conclusion: RAT improved CF in PS patients to some extent. However, evidence for this conclusion was of low quality. Therefore, further studies are still required for confirmation. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier (CRD42024568846).

Indexed as

cognitive functionmeta-analysisRCTrobot-assisted trainingstroke

Identifiers

PMID41853180
PMCPMC12992045

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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.