Evidence map›Paper›PMID 40761519›Full record

SynthesisFrontiers in human neuroscience2025

Systematic review and meta-analysis of effectiveness of robotic therapy in the recovery of motor functions after stroke.

Mariyam Amirbekova, Tokzhan Kispayeva, Ausra Adomaviciene, Laura Eszhanova, Inna Bolshakova, Zhanna Ospanova

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in human neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 3 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

10 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Article
  8. Robotic rehabilitation with the LokomatFrontiers in aging neuroscience · 2026
    Article
  9. Review
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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.

Mariyam AmirbekovaInstitute of Life Sciences, Karaganda Medical University, Karaganda, Kazakhstan.
Tokzhan KispayevaSchool of Nursing Education, Karaganda Medical University, Karaganda, Kazakhstan.
Ausra AdomavicieneDepartment of Rehabilitation, Institute of Medical Sciences, Physical and Sports Medicine, Vilnius University, Vilnius, Lithuania.
Laura EszhanovaDepartment of Neurology, Medical University of Astana, Astana, Kazakhstan.
Inna BolshakovaSchool of Nursing Education, Karaganda Medical University, Karaganda, Kazakhstan.
Zhanna OspanovaDepartment of History of Kazakhstan and Socio-Political Disciplines, Karaganda Medical University, Karaganda, Kazakhstan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Stroke is a leading cause of adult disability worldwide, often resulting in persistent motor impairments. While conventional rehabilitation approaches often yield modest results, robotic-assisted therapy has emerged as a promising solution to enhance motor recovery. However, the impact of stroke phase (acute, subacute, chronic) and other clinical modifiers on the effectiveness of robotic rehabilitation remains underexplored. Methods: The protocol for this systematic review and meta-analysis was registered in PROSPERO under the registration number CRD420251038754. A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. The literature search was conducted using MEDLINE, PubMed, Cochrane Library, Scopus, Web of Science, and EMBASE. Risk of bias was assessed using the RoB 2.0. Primary outcomes included motor recovery, gait speed, and balance. A random-effects model (DerSimonian-Laird) was applied to calculate pooled standardized mean differences (SMD), and subgroup analyses and meta-regression were used to assess the influence of stroke phase, age, therapy duration, and combined interventions (e.g., virtual reality, mirror therapy). Results: Thirteen randomized controlled trials (RCTs) published between 2015 and 2025 were included, with a total of 424 post-stroke patients. Robotic therapy showed a moderate but statistically significant effect over conventional rehabilitation (SMD = 0.59, 95% CI: [0.33; 0.84], Conclusion: Robotic-assisted therapy provides clinically meaningful improvements in post-stroke motor recovery. The findings support early stratification and personalization of rehabilitation programs based on stroke timing, age, and intervention intensity. Integration of robotic systems with virtual and cognitive components may further enhance neuroplasticity, leading to improved functional outcomes. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251038754.

Indexed as

meta-analysismotor functionsneurorehabilitationrobotic therapystroke recovery

Identifiers

PMID40761519
PMCPMC12318999

What OpenQuestion holds

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Registered trials

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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.