Evidence map›Paper›PMID 30375325›Full record

SynthesisDeutsches Arzteblatt international2018

The Improvement of Walking Ability Following Stroke.

Jan Mehrholz, Marcus Pohl, Joachim Kugler, Bernhard Elsner

2 registry-linked trialsOpen access · greenAbstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in Deutsches Arzteblatt international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 24 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 5 pooled it
3.9field-weighted citation impact, top 6% of its field
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.

NCT04364490 nacompletednot on this map

Study of the Rehabilitative Efficacy of Copernicus®, a Visual Feedback Device for the Early Start to Locomotion of Post-stroke Patients

TypeinterventionalSponsorS.Anna Rehabilitation InstituteRan2018 to 2019Enrolled162ConditionsStrokeArmsCopernicus noVF, Copernicis VF-Plus, Control group
NCT06949839 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Effectiveness of a Therapeutic Exercise Program Combined With Respiratory Muscle Training in Patients With Subacute Stroke: a Randomized Clinical Trial

TypeinterventionalSponsorAna Lista PazRan2025 to 2027Enrolled64ConditionsStrokeArmsTherapeutic exercise program combined with RMT, Therapeutic exercise program combined with sham RMT
3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 5 syntheses or guidelines pooled it, 52 citations in OpenAlex.

  1. Electromechanical-assisted training for walking after stroke.The Cochrane database of systematic reviews · 2025
    Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Electromechanical-assisted training for walking after stroke.The Cochrane database of systematic reviews · 2020
    Pooled it
  6. Trial
  7. Trial
  8. Trial
  9. Review
  10. Article
  11. Article
  12. Article
  13. Robotic-Assisted Gait Training (RAGT) in Stroke Rehabilitation: A Pilot Study.Archives of rehabilitation research and clinical translation · 2023
    Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Jan MehrholzGesundheitswissenschaften/Public Health, Medical Faculty, Technical University of Dresden; SRH Hochschule für Gesundheit, University of Applied Health Sciences; Helios Klinik Schloss Pulsnitz.
Marcus Pohl
Joachim Kugler
Bernhard Elsner
SRH Hochschule für Gesundheit Gera · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGait velocity and maximum walking distance are central parameters for measuring the success of rehabilitation of gait after a stroke. The goal of this study was to provide an overview of current evidence on the rehabilitation of gait after a stroke.

methodsA systematic review of randomized, controlled trials was carried out using network meta-analysis. The primary endpoint was gait velocity; secondary end- points were the ability to walk, maximum walking distance, and gait stability. The following interventions were analyzed: no gait training, conventional gait training (reference category), training on a treadmill with or without body weight support, training on a treadmill with or without a speed paradigm, and electromechanically assisted gait training with end-effector or exoskeleton apparatus.

resultsThe systematic search yielded 40 567 hits. 95 randomized, controlled trials involving a total of 4458 post-stroke patients were included in the meta-analysis. With respect to the primary endpoint of gait velocity, gait training assisted by end- effector apparatus led to significant improvement (mean difference [MD] = 0.16 m/s; 95% confidence interval [0.04; 0.28]). None of the other interventions improved gait velocity to any significant extent. With respect to one of the secondary endpoints, maximum walking distance, both gait training assisted by end-effector apparatus and treadmill training with body weight support led to significant improvement (MD = 47 m, [4; 90], and MD = 38 m, [4; 72], respectively). A network meta-analysis could not be performed with respect to the ability to walk (a different secondary endpoint) because of substantial inconsistencies in the data. The interventions did not differ significantly with respect to safety.

conclusionIn comparison to conventional gait rehabilitation, gait training assisted by end-effector apparatus leads to a statistically significant and clinically relevant improvement in gait velocity and maximum walking distance after stroke, while treadmill training with body weight support leads to a statistically significant and clinically relevant improvement in maximum walking distance.

Indexed as

Recovery of FunctionHumansStrokeStroke RehabilitationWalking

Identifiers

PMID30375325
PMCPMC6224539
OpenAlexW2890575017

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.