Evidence map›Paper›PMID 32528238›Full record

ArticleFrontiers in neuroscience2020

Exoskeleton Walk Training in Paralyzed Individuals Benefits From Transcutaneous Lumbar Cord Tonic Electrical Stimulation.

Elena Y Shapkova, Elena V Pismennaya, Dmitriy V Emelyannikov, Yury Ivanenko

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07767955 (Healthcare Professionals' Satisfaction With Various Exoskeleton Models), which is not on this map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
6.2field-weighted citation impact, top 3% 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.

NCT07767955 completednot on this mapstarted 2024, after this paper: background citation

Healthcare Professionals' Satisfaction With Various Exoskeleton Models

TypeobservationalSponsorUniversity of Sao Paulo General HospitalRan2024 to 2025Enrolled14ConditionsParaplegia and TetraplegiaArmsExoskeleton
3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.

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  17. Synergistic implications of combinatorial rehabilitation approaches using spinal stimulation on therapeutic outcomes in spinal cord injury.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2024
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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

4 authors at 4 institutions in 2 countries.

Elena Y ShapkovaThe Spinal Center of Saint-Petersburg State Research Institute of Phthisiopulmonology, Saint Petersburg, Russia.
Elena V PismennayaInstitute of Mechanics, Lomonosov Moscow State University, Moscow, Russia.
Dmitriy V EmelyannikovThe Spinal Center of Saint-Petersburg State Research Institute of Phthisiopulmonology, Saint Petersburg, Russia.
Yury IvanenkoIRCCS Santa Lucia Foundation, Rome, Italy.
Istituti di Ricovero e Cura a Carattere Scientifico · ITLomonosov Moscow State University · RUSaint-Petersburg Research Institute of Phthisiopulmonology · RUSt Petersburg University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, advanced technologies featuring wearable powered exoskeletons and neuromodulation of lumbosacral spinal networks have been developed to facilitate stepping and promote motor recovery in humans with paralysis. Here we studied a combined effect of spinal cord electrical stimulation (SCES) and exoskeleton walk training (EWT) during an intensive 2-week rehabilitative protocol in spinal cord injury individuals (

Indexed as

exoskeletonlocomotionneurorehabilitationspasticityspinal cord electrical stimulationspinal cord injury

Identifiers

PMID32528238
PMCPMC7263322
OpenAlexW3032742201

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.