Evidence map›Paper›PMID 38257564›Full record

ArticleSensors (Basel, Switzerland)2024

Error Enhancement for Upper Limb Rehabilitation in the Chronic Phase after Stroke: A 5-Day Pre-Post Intervention Study.

Marjan Coremans, Eli Carmeli, Ineke De Bauw, Bea Essers, Robin Lemmens, Geert Verheyden

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

6 authors.

Marjan CoremansDepartment of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium.ORCID 0000-0002-4331-892X
Eli CarmeliDepartment of Physical Therapy, University of Haifa, Haifa 3498838, Israel.ORCID 0000-0002-1704-112X
Ineke De BauwDepartment of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium.
Bea EssersDepartment of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium.ORCID 0000-0002-5894-2899
Robin LemmensDepartment of Neurosciences, Experimental Neurology, KU Leuven, 3000 Leuven, Belgium.ORCID 0000-0002-4948-5956
Geert VerheydenDepartment of Rehabilitation Sciences, KU Leuven, 3001 Leuven, Belgium.ORCID 0000-0003-3095-8175

Funding

BioXtreme S65699Promobilia Foundation 21052
6 · The paper itself

Abstract

A large proportion of chronic stroke survivors still struggle with upper limb (UL) problems in daily activities, typically reaching tasks. During three-dimensional reaching movements, the deXtreme robot offers error enhancement forces. Error enhancement aims to improve the quality of movement. We investigated clinical and patient-reported outcomes and assessed the quality of movement before and after a 5 h error enhancement training with the deXtreme robot. This pilot study had a pre-post intervention design, recruiting 22 patients (mean age: 57 years, mean days post-stroke: 1571, male/female: 12/10) in the chronic phase post-stroke with UL motor impairments. Patients received 1 h robot treatment for five days and were assessed at baseline and after training, collecting (1) clinical, (2) patient-reported, and (3) kinematic (KINARM, BKIN Technologies Ltd., Kingston, ON, Canada) outcome measures. Our analysis revealed significant improvements (median improvement (Q1-Q3)) in (1) UL Fugl-Meyer assessment (1.0 (0.8-3.0),

Indexed as

MovementStrokeCanadaFemaleHumansMaleMiddle AgedPilot ProjectsSelf Reporterror enhancementstrokeupper limb rehabilitation

Identifiers

PMID38257564
PMCPMC10820998

What OpenQuestion holds

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LicenceCC BY
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.