Evidence map›Paper›PMID 35664504›Full record

ArticleContemporary clinical trials communications2022

Quantitative assessment of training effects using EksoGT® exoskeleton in Parkinson's disease patients: A randomized single blind clinical trial.

M Romanato, F Spolaor, C Beretta, F Fichera, A Bertoldo, D Volpe, Z Sawacha

Open access · goldAbstract read
In one paragraph

Article in Contemporary clinical trials communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 14% 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.

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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. 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

7 authors at 1 institution in 1 country.

M RomanatoDepartment of Information Engineering, University of Padua, Padua, Italy.
F SpolaorDepartment of Information Engineering, University of Padua, Padua, Italy.
C BerettaFresco Parkinson Center, Villa Margherita, S. Stefano, Vicenza, Italy.
F FicheraFresco Parkinson Center, Villa Margherita, S. Stefano, Vicenza, Italy.
A BertoldoDepartment of Information Engineering, University of Padua, Padua, Italy.
D VolpeFresco Parkinson Center, Villa Margherita, S. Stefano, Vicenza, Italy.
Z SawachaDepartment of Information Engineering, University of Padua, Padua, Italy.
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gait alterations are among the most disabling motor-symptoms associated with Parkinson's Disease (PD): reduced stride length, stride velocity and lower limb joint range of motion are hallmarks of parkinsonian gait. Research focusing on optimal functional rehabilitation methods has been directed towards powered lower-limb exoskeletons which combines the advantages delivered from the grounded robotic devices with the ability to train the patient in a real-world environment Methods: Two cohorts of subjects will be enrolled and equally distributed between one group (n = 25) who will undergo a functional kinematic therapy, and one group (n = 25) who will undergo an overground wearable-exoskeleton training. Participants are evaluated at three time points: before the therapy (T0), after the therapy (T1), 4-weeks after T1 (T2). Comprehensive gait analysis and surface electromyography will be combined into neuromusculoskeletal modelling to determine modifications at the PNS level. Functional magnetic resonance imaging coupled with electroencephalography will be used to determine modifications at the CNS level. Conclusion: The findings of the proposed trial will likely give substantial solutions for the management of gait and postural disorders in PD where valid interventions are lacking. The coupling of movement evaluation, which assesses neuromuscular and biomechanical features, with neurological data, will better define the impact of the therapy on the relationship between PD motor alterations and brain activity. This will provide an active treatment that is personalized and shared to large populations.

Indexed as

Clinical gait analysisNeurophysiological assessmentParkinson's diseaseRehabilitationrobotic gait training

Identifiers

PMID35664504
PMCPMC9156880
OpenAlexW4281559725

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.