Predicting post‐stroke motor recovery of upper extremity using clinical variables and performance assays: A prospective cohort study protocol

物理医学与康复 冲程(发动机) 康复 物理疗法 前瞻性队列研究 医学 队列 外科 机械工程 内科学 工程类
作者
Sanjukta Sardesai,John Solomon M,Ashokan Arumugam,Vasudeva Guddattu,Sankar Prasad Gorthi,Aparna Pai,Senthil Kumaran D
出处
期刊:Physiotherapy Research International [Wiley]
卷期号:27 (2) 被引量:3
标识
DOI:10.1002/pri.1937
摘要

Measurement of movement quality is essential to distinguish motor recovery patterns and optimize rehabilitation strategies post-stroke. Recently, the Stroke Recovery and Rehabilitation Roundtable Taskforce (SRRR) recommended four kinetic and kinematic performance assays to measure upper extremity (UE) movements and distinguish behavioral restitution and compensation mechanisms early post-stroke. The purpose of this study is to develop and validate a prediction model to analyze the added prognostic value of performance assays over clinical variables assessed up to 1-month post stroke for predicting recovery of UE motor impairment, capacity and quality of movement (QoM) measured at 3 months post-stroke onset.In this prospective cohort study, 120 stroke survivors will be recruited within seven days post-stroke. Candidate predictors such as baseline characteristics, demographics and performance assays as per SRRR recommendations along with tonic stretch reflex threshold will be measured up to 1-month post-stroke. Upper extremity motor recovery will be evaluated in terms of motor impairment (Fugl-Meyer assessment for UE), UE capacity measured with Action Research Arm Test (ARAT) and QoM (movement smoothness in the form of peak metrics [PM]) assessed with a reach-to-grasp-to-mouth task (mimicking a drinking task) at 3 months post-stroke. Three multivariable linear regression models will be developed to predict factors responsible for the outcomes of Fugl-Meyer assessment for upper extremity (FM-UE), ARAT and movement quality. The developed models will be internally validated using a split-sample method.This study will provide a validated prediction model inclusive of clinical and performance assays that may assist in prediction of UE motor recovery. Predicting the amount of recovery and differentiating between behavioral restitution and compensation (as reflected by the FM-UE, QoM and ARAT) would enable us in realistic goal formation and planning rehabilitation. It would also help in encouraging patients to partake in early post-stroke rehabilitation thus improving the recovery potential.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
弃医从个啥完成签到,获得积分10
1秒前
大猫爪草完成签到,获得积分10
2秒前
明亮谷波发布了新的文献求助10
2秒前
5秒前
Rachel完成签到 ,获得积分10
6秒前
科研王子完成签到 ,获得积分10
7秒前
酷波er应助杨wen采纳,获得10
8秒前
小超人完成签到 ,获得积分10
8秒前
Qinzhiyuan1990完成签到 ,获得积分10
9秒前
10秒前
xuxu213发布了新的文献求助10
10秒前
11秒前
Ivy完成签到,获得积分10
13秒前
温乘云发布了新的文献求助10
16秒前
17秒前
juaner发布了新的文献求助10
18秒前
水之虞完成签到,获得积分10
18秒前
大大彬完成签到 ,获得积分10
19秒前
温乘云完成签到,获得积分10
22秒前
贪玩丸子完成签到 ,获得积分10
24秒前
juaner完成签到,获得积分10
27秒前
11112321321完成签到 ,获得积分10
31秒前
贪玩的德地完成签到,获得积分10
33秒前
xuxu213完成签到,获得积分20
33秒前
dongqulong完成签到 ,获得积分10
36秒前
一切顺利完成签到 ,获得积分10
37秒前
荔枝励志完成签到 ,获得积分10
42秒前
骑猪看月完成签到,获得积分10
43秒前
从容谷菱完成签到 ,获得积分10
43秒前
ppapp完成签到,获得积分10
45秒前
星辰大海应助eulota采纳,获得10
46秒前
LGH完成签到 ,获得积分10
46秒前
有何可不完成签到,获得积分10
47秒前
51秒前
恶魔小艾发布了新的文献求助10
54秒前
TianFuAI完成签到,获得积分10
56秒前
56秒前
王多肉发布了新的文献求助10
57秒前
无心的柚子完成签到,获得积分10
59秒前
roger完成签到,获得积分10
1分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6355757
求助须知:如何正确求助?哪些是违规求助? 8170509
关于积分的说明 17201011
捐赠科研通 5411733
什么是DOI,文献DOI怎么找? 2864357
邀请新用户注册赠送积分活动 1841893
关于科研通互助平台的介绍 1690224