Evidence map›Paper›PMID 29769127›Full record

Trial reportJournal of neuroengineering and rehabilitation2018

Reliability, validity and discriminant ability of the instrumental indices provided by a novel planar robotic device for upper limb rehabilitation.

Marco Germanotta, Arianna Cruciani, Cristiano Pecchioli, Simona Loreti, Albino Spedicato, Matteo Meotti, Rita Mosca, Gabriele Speranza, Francesca Cecchi, Giorgia Giannarelli and 2 more

2 registry-linked trialsOpen access · goldAbstract readClinical TrialMulticenter StudyValidation Study
In one paragraph

Trial report in Journal of neuroengineering and rehabilitation, 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 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
6.9field-weighted citation impact, top 2% 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.

NCT02879279 nacompletednot on this map

Efficacy of a Multi-segmental Robotic and Technological Upper Limb Rehabilitation Program, Compared With Traditional Therapy, in Individuals With Acute and Sub-acute Stroke: a Multicenter, Randomized, Controlled Clinical Trial.

TypeinterventionalSponsorFondazione Don Carlo Gnocchi ETSRan2016 to 2018Enrolled247ConditionsStrokeArmsAmadeo, Pablo, Diego and Motore., Conventional rehabilitation
NCT07199322 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Clinical validatiOn of an AI-based DEcision Support System for Robotic Upper Limb Rehabilitation in Patients With Stroke. A CO-AIDER Study.

TypeinterventionalSponsorFondazione Don Carlo Gnocchi ETSRan2025 to 2026Enrolled100ConditionsStroke, Stroke Ischemic, Stroke Hemorrhagic, Upper Limb RehabilitationArmsRobotic upper limb rehabilitation in patients with Stroke with AI support, Robotic upper limb rehabilitation in patients with Stroke without AI support
3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

  1. Systematic review of novel technology-based interventions for ischemic stroke.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
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  4. Quo Vadis, Amadeo Hand Robot? A Randomized Study with a Hand Recovery Predictive Model in Subacute Stroke.International journal of environmental research and public health · 2022
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  14. Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review.Archives of public health = Archives belges de sante publique · 2023
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  20. Robotic rehabilitation for end-effector device and botulinum toxin in upper limb rehabilitation in chronic post-stroke patients: an integrated rehabilitative approach.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
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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

12 authors at 2 institutions in 1 country.

Marco GermanottaIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy. mgermanotta@dongnocchi.it.ORCID 0000-0002-0747-831X
Arianna CrucianiIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Cristiano PecchioliIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Simona LoretiIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Albino SpedicatoIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Matteo MeottiIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Rita MoscaIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Gabriele SperanzaIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Francesca CecchiIRCCS Fondazione Don Carlo Gnocchi, Via di Scandicci, 269, 50143, Florence, Italy.
Giorgia GiannarelliIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Luca PaduaIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Irene AprileIRCCS Fondazione Don Carlo Gnocchi, Piazzale Morandi 6, 20121, Milan, Italy.
Don Carlo Gnocchi Foundation · ITUniversità Cattolica del Sacro Cuore · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the last few years, there has been an increasing interest in the use of robotic devices to objectively quantify motor performance of patients after brain damage. Although these robot-derived measures can potentially add meaningful information about the patient's dexterity, as well as be used as outcome measurements after the rehabilitation treatment, they need to be validated before being used in clinical practice. The present work aims to evaluate the reliability, the validity and the discriminant ability of the metrics provided by a novel robotic device for upper limb rehabilitation.

methodsForty-eight patients with sub-acute stroke and 40 age-matched healthy subjects were involved in this study. Clinical evaluation included: Fugl-Meyer Assessment for the upper limb, Action Research Arm Test, and Barthel Index. Robotic evaluation of the upper limb performance consisted of 14 measures of motor ability quantifying the dexterity in performing planar reaching movements. Patients were evaluated twice, one day apart, to assess the reliability of the robotic metrics, using the Intraclass Correlation Coefficient. Validity was assessed by analyzing the correlation of the robotic metrics with the clinical scales, by means of the Spearman's Correlation Coefficient. Finally, the ability of the robotic metrics to distinguish between patients with stroke and healthy subjects was investigated with t-tests and the Effect Size.

resultsReliability was found to be excellent for 12 measures and from moderate to good for the remaining 2. Most of the robotic indices were strongly correlated with the clinical scales, while a few showed a moderate correlation and only one was not correlated with the Barthel Index and weakly correlated with the remain two. Finally, all but one the provided metrics were able to discriminate between the two groups, with large effect sizes for most of them.

conclusionWe found that all the robotic indices except one provided by a novel robotic device for upper limb rehabilitation are reliable, sensitive and strongly correlated both with motor and disability clinical scales. Therefore, this device is suitable as evaluation tool for the upper limb motor performance of patients with sub-acute stroke in clinical practice.

trial registrationNCT02879279 .

Indexed as

AgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedMotor ActivityOutcome Assessment, Health CareReproducibility of ResultsRoboticsStrokeStroke RehabilitationUpper ExtremityDiscriminant abilityReliabilityRobot-mediated evaluationStrokeUpper limbValidity

Identifiers

PMID29769127
PMCPMC5956822
OpenAlexW2803578896

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.