Literature DB >> 29090654

The TWIST Algorithm Predicts Time to Walking Independently After Stroke.

Marie-Claire Smith1, P Alan Barber1,2, Cathy M Stinear1.   

Abstract

BACKGROUND AND
OBJECTIVE: The likelihood of regaining independent walking after stroke is of concern to patients and their families and influences hospital discharge planning. The objective of this study was to explore factors that could be combined in an algorithm for predicting whether and when a patient will walk independently after stroke.
METHODS: Adults with new lower limb weakness were recruited within 3 days of having a stroke. Clinical assessment, transcranial magnetic stimulation, and magnetic resonance imaging were completed 1 to 2 weeks poststroke. Classification and regression tree (CART) analysis was used to identify factors that predicted whether a patient achieved independent walking by 6 or 12 weeks, or remained dependent at 12 weeks.
RESULTS: We recruited 41 patients (24 women; median age 72 years, range 43-96 years). The CART analysis results were used to create the Time to Walking Independently after STroke (TWIST) algorithm, which made accurate predictions for 95% of patients. Patients with a trunk control test score >40 at 1 week walked independently within 6 weeks. Patients with a trunk control test score <40 only achieved independent walking by 12 weeks if they also had hip extension strength of Medical Research Council grade 3 or more. Neurophysiological and neuroimaging measures did not predict independent walking after stroke.
CONCLUSIONS: In this exploratory study, the TWIST algorithm accurately predicted whether and when an individual patient walked independently after stroke using simple bedside measures 1 week poststroke. Further work is required to develop and validate this algorithm in a larger study.

Entities:  

Keywords:  lower extremity; prognosis; stroke; trunk control; walking

Mesh:

Year:  2017        PMID: 29090654     DOI: 10.1177/1545968317736820

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


  12 in total

1.  Enhanced Evolutionary Feature Selection and Ensemble Method for Cardiovascular Disease Prediction.

Authors:  V Jothi Prakash; N K Karthikeyan
Journal:  Interdiscip Sci       Date:  2021-05-14       Impact factor: 2.233

2.  Absence of a Transcranial Magnetic Stimulation-Induced Lower Limb Corticomotor Response Does Not Affect Walking Speed in Chronic Stroke Survivors.

Authors:  Anjali Sivaramakrishnan; Sangeetha Madhavan
Journal:  Stroke       Date:  2018-08       Impact factor: 7.914

Review 3.  Transcranial magnetic stimulation implementation on stroke prognosis.

Authors:  Stella Karatzetzou; Dimitrios Tsiptsios; Aikaterini Terzoudi; Nikolaos Aggeloussis; Konstantinos Vadikolias
Journal:  Neurol Sci       Date:  2021-11-30       Impact factor: 3.830

4.  Functional magnetic resonance brain imaging of imagined walking to study locomotor function after stroke.

Authors:  Pierce Boyne; Sarah Doren; Victoria Scholl; Emily Staggs; Dustyn Whitesel; Thomas Maloney; Oluwole Awosika; Brett Kissela; Kari Dunning; Jennifer Vannest
Journal:  Clin Neurophysiol       Date:  2020-11-21       Impact factor: 3.708

Review 5.  Ipsilateral motor pathways to the lower limb after stroke: Insights and opportunities.

Authors:  Brice T Cleland; Sangeetha Madhavan
Journal:  J Neurosci Res       Date:  2021-03-04       Impact factor: 4.433

6.  Effectiveness of Radial Extracorporeal Shock Wave Therapy and Visual Feedback Balance Training on Lower Limb Post-Stroke Spasticity, Trunk Performance, and Balance: A Randomized Controlled Trial.

Authors:  Emanuela Elena Mihai; Ilie Valentin Mihai; Mihai Berteanu
Journal:  J Clin Med       Date:  2021-12-28       Impact factor: 4.241

7.  Physical activity dimensions after stroke: patterns and relation with lower limb motor function.

Authors:  Hanneke E M Braakhuis; Monique A M Berger; Ruben G R H Regterschot; Erwin E H van Wegen; Ruud W Selles; Gerard M Ribbers; Johannes B J Bussmann
Journal:  J Neuroeng Rehabil       Date:  2021-12-11       Impact factor: 4.262

Review 8.  Surface electroencephalography (EEG) during the acute phase of stroke to assist with diagnosis and prediction of prognosis: a scoping review.

Authors:  Lou Sutcliffe; Hannah Lumley; Lisa Shaw; Richard Francis; Christopher I Price
Journal:  BMC Emerg Med       Date:  2022-02-28

9.  A systematic review of the usefulness of magnetic resonance imaging in predicting the gait ability of stroke patients.

Authors:  Takeshi Imura; Tsubasa Mitsutake; Yuji Iwamoto; Ryo Tanaka
Journal:  Sci Rep       Date:  2021-07-12       Impact factor: 4.379

10.  Intra- and inter-rater reliability of Fugl-Meyer Assessment of Lower Extremity early after stroke.

Authors:  Edgar D Hernández; Sandra M Forero; Claudia P Galeano; Nubia E Barbosa; Katharina S Sunnerhagen; Margit Alt Murphy
Journal:  Braz J Phys Ther       Date:  2020-12-17       Impact factor: 3.377

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