Evidence map›Paper›PMID 41163210›Full record

SynthesisJournal of neuroengineering and rehabilitation2025

Optimal exercise modalities for post-intervention motor function changes in stroke survivors: a pairwise and network meta-analysis.

Liqun Jiang, Huimin Ding, Hyun Seo, Buongo Chun

Abstract readNetwork Meta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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.

Liqun JiangGraduate School of Physical Education, Myongji University, 116th Myongji University, Mingzhi Road, Churen District, Yongin, Gyeonggi, 17058, Republic of Korea.ORCID http://orcid.org/0009-0005-8637-6491
Huimin DingGraduate School of Physical Education, Myongji University, 116th Myongji University, Mingzhi Road, Churen District, Yongin, Gyeonggi, 17058, Republic of Korea.ORCID http://orcid.org/0009-0000-9469-3052
Hyun SeoDepartment of Sport and Leisure Studies, Graduate School, Korea University, Sejong, 02841, Republic of Korea.
Buongo ChunGraduate School of Physical Education, Myongji University, 116th Myongji University, Mingzhi Road, Churen District, Yongin, Gyeonggi, 17058, Republic of Korea. tianbingwu@mju.ac.kr.ORCID http://orcid.org/0000-0003-3831-2328

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStroke is a leading cause of long-term disability worldwide, particularly among older adults, and severely compromises functional independence and quality of life. Exercise interventions are well established as effective strategies for promoting motor recovery through improvements in neuroplasticity, fitness, strength, and psychosocial well-being, yet most evidence to date has focused on immediate post-intervention outcomes. The durability of these benefits during follow-up periods-defined as the post-intervention phase when patients are observed after completing structured rehabilitation and begin transitioning to self-directed activities-remains poorly understood. Clarifying functional trajectories during this phase is critical for assessing the sustainability and real-world value of rehabilitation strategies. A systematic evaluation of motor function outcomes beyond formal intervention is therefore urgently needed to inform the design of programs that prioritize long-term recovery.

methodsThis systematic review and network meta-analysis followed PRISMA 2020 guidelines and was registered in PROSPERO (CRD420251117014). Five databases (PubMed, Embase, Web of Science, Scopus, Cochrane Library) were searched up to March 13, 2025. We included randomized controlled trials comparing structured exercise interventions in post-stroke adults during follow-up periods, reporting motor function outcomes. Risk of bias was assessed using RoB 2.0, and evidence quality was graded via CINeMA. Pairwise and Bayesian network meta-analyses were conducted using netmeta and gemtc packages. Heterogeneity, inconsistency, regression, sensitivity, and publication bias analyses were also performed.

resultsSixty-four trials (n = 3074) were included, covering 23 exercise modalities. For the 6-min walk test, resistance training demonstrated the greatest effect [mean difference (MD) = 21.79, 95% CI 8.19-35.40], followed by robot-assisted therapy (MD = 19.78, 95% CI 3.30-36.27). In the 10-m walk test, robot-assisted therapy ranked highest (MD = 0.06, 95% CI 0.01-0.12). Task-oriented training significantly improved balance [standardized mean difference (SMD) = 0.35, 95% CI 0.07-0.64]. No significant effects were observed in lower or upper limb Fugl-Meyer outcomes. Consistency and heterogeneity were generally acceptable, and no publication bias was detected.

conclusionsResistance training and robot-assisted therapy appear most effective for enhancing walking capacity after stroke. Task-oriented training benefits postural balance. Evidence for upper and lower limb recovery remains inconclusive due to the small number of trials and wide confidence intervals. These findings can inform individualized, modality-specific rehabilitation strategies for older adults recovering from stroke.

trial registrationRegistered on PROSPERO (CRD420251117014).

Indexed as

Exercise TherapyStrokeStroke RehabilitationHumansNetwork Meta-Analysis as TopicRecovery of FunctionMotor functionNetwork meta-analysisOlder adultsResistance trainingRobot-assisted therapyStroke rehabilitationTask-oriented trainingWalking capacity

Identifiers

PMID41163210
PMCPMC12570818

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.