Trial reportJournal of neurotrauma2024
Exoskeletal-Assisted Walking During Acute Inpatient Rehabilitation Enhances Recovery for Persons with Spinal Cord Injury-A Pilot Randomized Controlled Trial.
Trial report in Journal of neurotrauma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled 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.
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
4 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The effect of robot-assisted gait training on physical activity outcomes in people with spinal cord injury: A systematic review.Clinical rehabilitation · 2026Pooled it
- Effects of an exoskeleton robot on motor function in patients with spinal cord injuries: a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Kaempferide Promotes Neuroprotection and Functional Recovery After Spinal Cord Injury and is Associated with Differential Regulation of ARG1, CA4, CYP1B1, and OAT.Neuropsychiatric disease and treatment · 2026Article
- Kunming Locomotor Training: neurological, functional, and autonomic outcomes in complete spinal cord injury.Current opinion in neurology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Spinal cord injury (SCI) negatively impacts individuals' functional independence, and motor and sensory function. Intense walking training has been shown to facilitate recovery for individuals with chronic SCI. Powered robotic exoskeletons provide therapists with a tool that allows them to conduct walking training with less therapist effort as compared to conventional walking training. Exoskeletal-assisted walking (EAW) has been studied in the chronic SCI population with preliminary reports showing benefits in mobility, health, and quality-of-life outcomes. However, few reports have studied EAW's benefits in the acute (<90 days post) SCI population at a time when neural plasticity is most dynamic and modifiable. The purpose of the study was to conduct a pilot randomized controlled trial (RCT) to understand the effects of incorporated EAW in acute inpatient rehabilitation (AIR) for individuals with SCI on functional, motor, and sensory recovery. The study outcomes included the Spinal Cord Independence Measure (SCIM) III and International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) motor and sensory scores that were assessed by unblinded assessors. We also recorded EAW session data, including adverse events, walking and up time, step counts, Borg Rating of Perceived Exertion (RPE), and compliance with scheduled EAW training. From August 2019 to July 2022, 16 participants completed the AIR with incorporated EAW, and 12 completed the standard AIR, all with SCI and preserved leg function within 90 days post-injury. During each session, the AIR with incorporated EAW group averaged 34.3 (±9.4) min of up time, 25.4 (±7.7) min of walk time, and 536 (±157) steps. Analysis via two-by-two mixed-effects models showed significant increases in the SCIM total score and ISNCSCI total motor and sensory scores over time for the AIR with incorporated EAW group [SCIM total score:
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Registered trials
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