Literature DB >> 31416391

Breaking Proportional Recovery After Stroke.

Merav R Senesh1, David J Reinkensmeyer1.   

Abstract

People with hemiparesis after stroke appear to recover 70% to 80% of the difference between their baseline and the maximum upper extremity Fugl-Meyer (UEFM) score, a phenomenon called proportional recovery (PR). Two recent commentaries explained that PR should be expected because of mathematical coupling between the baseline and change score. Here we ask, If mathematical coupling encourages PR, why do a fraction of stroke patients (the "nonfitters") not exhibit PR? At the neuroanatomical level of analysis, this question was answered by Byblow et al-nonfitters lack corticospinal tract (CST) integrity at baseline-but here we address the mathematical and behavioral causes. We first derive a new interpretation of the slope of PR: It is the average probability of scoring across remaining scale items at follow-up. PR therefore breaks when enough test items are discretely more difficult for a patient at follow-up, flattening the slope of recovery. For the UEFM, we show that nonfitters are most unlikely to recover the ability to score on the test items related to wrist/hand dexterity, shoulder flexion without bending the elbow, and finger-to-nose movement, supporting the finding that nonfitters lack CST integrity. However, we also show that a subset of nonfitters respond better to robotic movement training in the chronic phase of stroke. These persons are just able to move the arm out of the flexion synergy and pick up small blocks, both markers of CST integrity. Nonfitters therefore raise interesting questions about CST function and the basis for response to intensive movement training.

Entities:  

Keywords:  movement; projections and predictions; proportional recovery; rating scales; rehabilitation; stroke

Mesh:

Year:  2019        PMID: 31416391      PMCID: PMC6851474          DOI: 10.1177/1545968319868718

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


  67 in total

1.  Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience.

Authors:  C G Burgar; P S Lum; P C Shor; H F Machiel Van der Loos
Journal:  J Rehabil Res Dev       Date:  2000 Nov-Dec

2.  The long-term outcome of arm function after stroke: results of a follow-up study.

Authors:  J G Broeks; G J Lankhorst; K Rumping; A J Prevo
Journal:  Disabil Rehabil       Date:  1999-08       Impact factor: 3.033

3.  Proportional Motor Recovery After Stroke: Implications for Trial Design.

Authors:  Cathy M Stinear; Winston D Byblow; Suzanne J Ackerley; Marie-Claire Smith; Victor M Borges; P Alan Barber
Journal:  Stroke       Date:  2017-01-31       Impact factor: 7.914

4.  Taking Proportional Out of Stroke Recovery.

Authors:  Rachel L Hawe; Stephen H Scott; Sean P Dukelow
Journal:  Stroke       Date:  2018-12-07       Impact factor: 7.914

5.  Comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial.

Authors:  Jessica McCabe; Michelle Monkiewicz; John Holcomb; Svetlana Pundik; Janis J Daly
Journal:  Arch Phys Med Rehabil       Date:  2014-11-15       Impact factor: 3.966

6.  A standardized approach to the Fugl-Meyer assessment and its implications for clinical trials.

Authors:  Jill See; Lucy Dodakian; Cathy Chou; Vicky Chan; Alison McKenzie; David J Reinkensmeyer; Steven C Cramer
Journal:  Neurorehabil Neural Repair       Date:  2013-06-17       Impact factor: 3.919

7.  Corticospinal excitability as a predictor of functional gains at the affected upper limb following robotic training in chronic stroke survivors.

Authors:  Marie-Hélène Milot; Steven J Spencer; Vicky Chan; James P Allington; Julius Klein; Cathy Chou; Kristin Pearson-Fuhrhop; James E Bobrow; David J Reinkensmeyer; Steven C Cramer
Journal:  Neurorehabil Neural Repair       Date:  2014-03-18       Impact factor: 3.919

8.  Functional and motor outcome 5 years after stroke is equivalent to outcome at 2 months: follow-up of the collaborative evaluation of rehabilitation in stroke across Europe.

Authors:  Sarah Meyer; Geert Verheyden; Nadine Brinkmann; Eddy Dejaeger; Willy De Weerdt; Hilde Feys; Andreas R Gantenbein; Walter Jenni; Annouschka Laenen; Nadina Lincoln; Koen Putman; Birgit Schuback; Wilfried Schupp; Vincent Thijs; Liesbet De Wit
Journal:  Stroke       Date:  2015-05-07       Impact factor: 7.914

9.  Efficacy of robot-assisted fingers training in chronic stroke survivors: a pilot randomized-controlled trial.

Authors:  Evan A Susanto; Raymond Ky Tong; Corinna Ockenfeld; Newmen Sk Ho
Journal:  J Neuroeng Rehabil       Date:  2015-04-25       Impact factor: 4.262

10.  Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke.

Authors:  Kai Keng Ang; Cuntai Guan; Kok Soon Phua; Chuanchu Wang; Longjiang Zhou; Ka Yin Tang; Gopal J Ephraim Joseph; Christopher Wee Keong Kuah; Karen Sui Geok Chua
Journal:  Front Neuroeng       Date:  2014-07-29
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  10 in total

1.  β-Oscillations Reflect Recovery of the Paretic Upper Limb in Subacute Stroke.

Authors:  Chih-Wei Tang; Fu-Jung Hsiao; Po-Lei Lee; Yun-An Tsai; Ya-Fang Hsu; Wei-Ta Chen; Yung-Yang Lin; Charlotte J Stagg; I-Hui Lee
Journal:  Neurorehabil Neural Repair       Date:  2020-04-23       Impact factor: 3.919

2.  Translating concepts of neural repair after stroke: Structural and functional targets for recovery.

Authors:  Robert W Regenhardt; Hajime Takase; Eng H Lo; David J Lin
Journal:  Restor Neurol Neurosci       Date:  2020       Impact factor: 2.406

3.  Using a bimanual lever-driven wheelchair for arm movement practice early after stroke: A pilot, randomized, controlled, single-blind trial.

Authors:  Brendan W Smith; Joan Lobo-Prat; Daniel K Zondervan; Christopher Lew; Vicky Chan; Cathy Chou; Spencer Toledo; David J Reinkensmeyer; Susan Shaw; Steven C Cramer
Journal:  Clin Rehabil       Date:  2021-05-24       Impact factor: 3.477

4.  Differential Changed Excitability of Spinal Motor Neurons Innervating Tibialis Anterior and Peroneus Muscles Cause Foot Inversion After Stroke.

Authors:  Gang Liu; Chin-Hsuan Chia; Yue Cao; Xin-Wei Tang; Shan Tian; Xue-Yan Shen; Ying Chen; Rong-Rong Lu; Jun-Fa Wu; Yi Wu
Journal:  Front Neurol       Date:  2020-11-24       Impact factor: 4.003

5.  Does Measurement of Corticospinal Tract Involvement Add Value to Clinical Behavioral Biomarkers in Predicting Motor Recovery after Stroke?

Authors:  Jong Youb Lim; Mi-Kyoung Oh; Jihong Park; Nam-Jong Paik
Journal:  Neural Plast       Date:  2020-11-27       Impact factor: 3.599

6.  Computerised patient-specific prediction of the recovery profile of upper limb capacity within stroke services: the next step.

Authors:  Ruud W Selles; Eleni-Rosalina Andrinopoulou; Rinske H Nijland; Rick van der Vliet; Jorrit Slaman; Erwin Eh van Wegen; Dimitris Rizopoulos; Gerard M Ribbers; Carel Gm Meskers; Gert Kwakkel
Journal:  J Neurol Neurosurg Psychiatry       Date:  2021-01-21       Impact factor: 10.154

7.  Corticospinal Tract Microstructure Predicts Distal Arm Motor Improvements in Chronic Stroke.

Authors:  Bokkyu Kim; Nicolas Schweighofer; Justin P Haldar; Richard M Leahy; Carolee J Winstein
Journal:  J Neurol Phys Ther       Date:  2021-10-01       Impact factor: 4.655

8.  Prediction of Motor Recovery in Patients with Basal Ganglia Hemorrhage Using Diffusion Tensor Imaging.

Authors:  Yu-Sun Min; Kyung Eun Jang; Eunhee Park; Ae-Ryoung Kim; Min-Gu Kang; Youn-Soo Cheong; Ju-Hyun Kim; Seung-Hwan Jung; Jaechan Park; Tae-Du Jung
Journal:  J Clin Med       Date:  2020-05-01       Impact factor: 4.241

9.  Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches.

Authors:  Hiren Kumar Thakkar; Wan-Wen Liao; Ching-Yi Wu; Yu-Wei Hsieh; Tsong-Hai Lee
Journal:  J Neuroeng Rehabil       Date:  2020-09-29       Impact factor: 4.262

10.  Analysis of Prognostic Risk Factors Determining Poor Functional Recovery After Comprehensive Rehabilitation Including Motor-Imagery Brain-Computer Interface Training in Stroke Patients: A Prospective Study.

Authors:  Qiong Wu; Yunxiang Ge; Di Ma; Xue Pang; Yingyu Cao; Xiaofei Zhang; Yu Pan; Tong Zhang; Weibei Dou
Journal:  Front Neurol       Date:  2021-06-10       Impact factor: 4.003

  10 in total

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