Literature DB >> 26450442

Long-term Effectiveness of Intensive Therapy in Chronic Stroke.

Xiaotian Wu1, Peter Guarino1, Albert C Lo2, Peter Peduzzi1, Michael Wininger3.   

Abstract

Background While recent clinical trials involving robot-assisted therapy have failed to show clinically significant improvement versus conventional therapy, it is possible that a broader strategy of intensive therapy-to include robot-assisted rehabilitation-may yield clinically meaningful outcomes. Objective To test the immediate and sustained effects of intensive therapy (robot-assisted therapy plus intensive conventional therapy) on outcomes in a chronic stroke population. Methods A multivariate mixed-effects model adjusted for important covariates was established to measure the effect of intensive therapy versus usual care. A total of 127 chronic stroke patients from 4 Veterans Affairs medical centers were randomized to either robot-assisted therapy (n = 49), intensive comparison therapy (n = 50), or usual care (n = 28), in the VA-ROBOTICS randomized clinical trial. Patients were at least 6 months poststroke, of moderate-to-severe upper limb impairment. The primary outcome measure was the Fugl-Meyer Assessment at 12 and 36 weeks. Results There was significant benefit of intensive therapy over usual care on the Fugl-Meyer Assessment at 12 weeks with a mean difference of 4.0 points (95% CI = 1.3-6.7); P = .005; however, by 36 weeks, the benefit was attenuated (mean difference 3.4; 95% CI = -0.02 to 6.9; P = .05). Subgroup analyses showed significant interactions between treatment and age, treatment and time since stroke. Conclusions Motor benefits from intensive therapy compared with usual care were observed at 12 and 36 weeks posttherapy; however, this difference was attenuated at 36 weeks. Subgroups analysis showed that younger age, and a shorter time since stroke were associated with greater immediate and long-term improvement of motor function.
© The Author(s) 2015.

Entities:  

Keywords:  robot; therapy; upper limb

Mesh:

Year:  2015        PMID: 26450442     DOI: 10.1177/1545968315608448

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  12 in total

1.  Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

Authors:  Justin B Rowe; Vicky Chan; Morgan L Ingemanson; Steven C Cramer; Eric T Wolbrecht; David J Reinkensmeyer
Journal:  Neurorehabil Neural Repair       Date:  2017-08       Impact factor: 3.919

2.  Baseline Predictors of Response to Repetitive Task Practice in Chronic Stroke.

Authors:  Michael A Dimyan; Stacey Harcum; Elsa Ermer; Amy F Boos; Susan S Conroy; Fang Liu; Linda B Horn; Huichun Xu; Min Zhan; Hegang Chen; Jill Whitall; George F Wittenberg
Journal:  Neurorehabil Neural Repair       Date:  2022-05-26       Impact factor: 4.895

Review 3.  The effect of time spent in rehabilitation on activity limitation and impairment after stroke.

Authors:  Beth Clark; Jill Whitall; Gert Kwakkel; Jan Mehrholz; Sean Ewings; Jane Burridge
Journal:  Cochrane Database Syst Rev       Date:  2021-10-25

Review 4.  Robot-Assisted Therapy in Upper Extremity Hemiparesis: Overview of an Evidence-Based Approach.

Authors:  Christophe Duret; Anne-Gaëlle Grosmaire; Hermano Igo Krebs
Journal:  Front Neurol       Date:  2019-04-24       Impact factor: 4.003

Review 5.  Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke.

Authors:  Martina Coscia; Maximilian J Wessel; Ujwal Chaudary; José Del R Millán; Silvestro Micera; Adrian Guggisberg; Philippe Vuadens; John Donoghue; Niels Birbaumer; Friedhelm C Hummel
Journal:  Brain       Date:  2019-08-01       Impact factor: 13.501

6.  Long-Dose Intensive Therapy Is Necessary for Strong, Clinically Significant, Upper Limb Functional Gains and Retained Gains in Severe/Moderate Chronic Stroke.

Authors:  Janis J Daly; Jessica P McCabe; John Holcomb; Michelle Monkiewicz; Jennifer Gansen; Svetlana Pundik
Journal:  Neurorehabil Neural Repair       Date:  2019-05-25       Impact factor: 3.919

7.  Clustering of Directions Improves Goodness of Fit in Kinematic Data Collected in the Transverse Plane During Robot-Assisted Rehabilitation of Stroke Patients.

Authors:  Ling Li; John Hartigan; Peter Peduzzi; Peter Guarino; Alexander T Beed; Xiaotian Wu; Michael Wininger
Journal:  Front Robot AI       Date:  2018-05-24

8.  Self-directed arm therapy at home after stroke with a sensor-based virtual reality training system.

Authors:  Frieder Wittmann; Jeremia P Held; Olivier Lambercy; Michelle L Starkey; Armin Curt; Raphael Höver; Roger Gassert; Andreas R Luft; Roman R Gonzenbach
Journal:  J Neuroeng Rehabil       Date:  2016-08-11       Impact factor: 4.262

Review 9.  Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective.

Authors:  Roger Gassert; Volker Dietz
Journal:  J Neuroeng Rehabil       Date:  2018-06-05       Impact factor: 4.262

10.  Methods for an Investigation of Neurophysiological and Kinematic Predictors of Response to Upper Extremity Repetitive Task Practice in Chronic Stroke.

Authors:  Stacey Harcum; Susan S Conroy; Amy Boos; Elsa Ermer; Huichun Xu; Min Zhan; Hegang Chen; Jill Whitall; Michael A Dimyan; George F Wittenberg
Journal:  Arch Rehabil Res Clin Transl       Date:  2019-09-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.