ArticleScientific reports2022
Body weight-supported gait training for patients with spinal cord injury: a network meta-analysis of randomised controlled trials.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Non-invasive cerebral and spinal cord stimulation for motor and gait recovery in incomplete spinal cord injury: systematic review and meta-analysis.Journal of neuroengineering and rehabilitation · 2025Pooled it
- The effect of robot-assisted gait training for patients with spinal cord injury: a systematic review and meta-analysis.Frontiers in neuroscience · 2023Pooled it
- Three-Grade Neurological Recovery (ASIA Impairment Scale A to D) Following Surgical Stabilization of Traumatic D11-D12 Meyerding Grade IV Spondylolisthesis: A Case Report.Journal of orthopaedic case reports · 2026Article
- Physiotherapists' User Acceptance of a Lower Limb Robotic Exoskeleton in Specialized Rehabilitation: Qualitative Exploratory Study.JMIR rehabilitation and assistive technologies · 2025Article
- Comparative effectiveness of lower body positive pressure and traditional treadmill training on adults with mild balance impairment.Frontiers in aging · 2025Article
- Rehabilitation to Improve Outcomes after Cervical Spine Surgery: Narrative Review.Journal of clinical medicine · 2024Review
- Robot-assisted gait training in patients with various neurological diseases: A mixed methods feasibility study.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Different body weight-supported gait-training strategies are available for improving ambulation in individuals with spinal cord injury (SCI). These include body weight-supported overground training (BWSOGT), body weight-supported treadmill training (BWSTT), and robot-assisted gait training (RAGT). We conducted a network meta-analysis of randomised controlled trials (RCTs) to assess the effect and priority of each training protocol. We searched the PubMed, Cochrane Library, Scopus, and Embase databases from inception to 6 August 2022. The eligibility criteria were as follows: (1) being RCTs, (2) recruiting participants with SCI diagnosis and requiring gait training, (3) comparing different body weight-supported gait training strategies, and (4) involving ambulatory assessments. We conducted a network meta-analysis to compare different training strategies using the standard mean difference and its 95% credible interval. To rank the efficacy of training strategies, we used the P score as an indicator. Inconsistency in network meta-analysis was evaluated using loop-specific heterogeneity. We included 15 RCTs in this analysis. RAGT was had significantly more favourable performance than had the control intervention. The ranking probabilities indicated that the most effective approach was RAGT, followed by BWSOGT, BWSTT, and the control intervention. No significant inconsistency was noted between the results of the direct and indirect comparisons.
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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.