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Trial registered on ANZCTR
Registration number
ACTRN12617001434381
Ethics application status
Approved
Date submitted
6/10/2017
Date registered
10/10/2017
Date last updated
11/02/2021
Date data sharing statement initially provided
12/02/2019
Type of registration
Prospectively registered
Titles & IDs
Public title
TWIST: Time to Walking Independently after STroke
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Scientific title
TWIST: A prospective, single-site, assessor-blind observational study to validate the Time to Walking Independently after STroke (TWIST) algorithm
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Secondary ID [1]
293080
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Nil
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Universal Trial Number (UTN)
U1111-1203-2929
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Trial acronym
TWIST
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Linked study record
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Health condition
Health condition(s) or problem(s) studied:
Stroke
305009
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Condition category
Condition code
Stroke
304330
304330
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0
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Ischaemic
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Stroke
304351
304351
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0
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Haemorrhagic
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Intervention/exposure
Study type
Observational
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Patient registry
False
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Target follow-up duration
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Target follow-up type
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Description of intervention(s) / exposure
This study will observe recovery of walking ability after stroke. Participants' walking ability will be classified using the Functional Ambulation Category at 1, 2, 4, 6, 9, 12, 16, 20 and 26 weeks post-stroke. The TWIST algorithm combines clinical assessments of trunk control and lower limb muscle strength in order to predict when a patient will recover independent walking. The algorithm was previously developed in a sample of 40 patients. This study will validate the algorithm by seeing whether it correctly predicts the recovery of independent walking in an independent and larger sample of patients.
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Intervention code [1]
299321
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Diagnosis / Prognosis
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Comparator / control treatment
The accuracy of TWIST algorithm predictions will be compared to the accuracy of therapists' predictions.
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Control group
Active
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Outcomes
Primary outcome [1]
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Week post-stroke at which the patient is able to walk independently, defined as a Functional Ambulation Category score of either 4 or 5.
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Assessment method [1]
303593
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Timepoint [1]
303593
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Walking ability will be assessed using the Functional Ambulation Category scores, at 1, 2, 4, 6, 9, 12, 16, 20 and 26 weeks post-stroke.
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Secondary outcome [1]
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Walking ability at 26 weeks post-stroke, measured with the Functional Ambulation Category.
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Assessment method [1]
339529
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Timepoint [1]
339529
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26 weeks post-stroke.
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Secondary outcome [2]
339530
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Discharge destination at the conclusion of inpatient rehabilitation
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Assessment method [2]
339530
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Timepoint [2]
339530
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Discharge from inpatient rehabilitation
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Secondary outcome [3]
339603
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The accuracy of TWIST algorithm predictions will be compared to the accuracy of therapists' predictions.
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Assessment method [3]
339603
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Timepoint [3]
339603
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The week post-stroke by which patients recover independent walking.
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Eligibility
Key inclusion criteria
Ischaemic stroke or intracerebral haemorrhage within the previous 72 hours
New lower limb motor symptoms
At least 18 years old
Previous stroke is allowed provided the patient was walking independently prior to the new stroke
Cognitive or communication impairment is allowed as assent to participation can be obtained from a family member
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Minimum age
18
Years
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Maximum age
No limit
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Sex
Both males and females
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Can healthy volunteers participate?
No
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Key exclusion criteria
Subarachnoid haemorrhage
Unable to follow a one-step command, precluding lower limb strength testing
Contraindications to non-invasive transcranial magnetic stimulation
Pre-stroke Functional Ambulation Category score less than 4, meaning the patient was not walking independently
Other neurological or orthopaedic conditions affecting lower limb function or walking
Life expectancy less than 12 months
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Study design
Purpose
Natural history
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Duration
Longitudinal
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Selection
Convenience sample
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Timing
Prospective
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Statistical methods / analysis
The planned sample size is 140 patients. Allowing for attrition, the sample size available for analysis is estimated to be 100 patients. With this sample size, we estimate that there will be at least 20 patients in each outcome group (based on the week that independent walking was regained after stroke). This is sufficient for analysis with a Classification and Regression Tree (CaRT). First, a hypothesis-free cluster analysis will be used to categorise patients based on their primary outcome (week they achieved independent walking after stroke). All baseline clinical and demographic variables, lower limb motor-evoked potential (MEP) status, therapy dose, and falls, will be entered into the CaRT analysis, to determine which factors best predict the primary outcome categories. The results of the CaRT analysis will be used to validate the TWIST algorithm, which is a clinical decision tree for predicting the week at which a patient will recover independent walking after stroke. Baseline clinical and demographic variables, lower limb MEP status, therapy dose, and falls, will be also entered into separate analyses, to determine which factors best predict the secondary outcomes of FAC value at six months post-stroke and discharge destination.
Therapists will be asked 1 week post-stroke to predict whether each participant will recover independent walking by 6 months post-stroke, and if so, at what time point. The accuracy of therapists' predictions will be compared to the TWIST algorithm's predictions to determine whether the algorithm performs as well as, or better than, therapists' clinical judgement. Secondary analyses will explore whether the accuracy of therapist predictions varies depending on the therapists' confidence and experience levels, and depending on patient factors such as age and stroke severity.
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Recruitment
Recruitment status
Recruiting
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Date of first participant enrolment
Anticipated
22/02/2018
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Actual
21/02/2018
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Date of last participant enrolment
Anticipated
1/07/2021
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Actual
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Date of last data collection
Anticipated
31/12/2021
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Actual
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Sample size
Target
140
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Accrual to date
115
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Final
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Recruitment outside Australia
Country [1]
9267
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New Zealand
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State/province [1]
9267
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Auckland
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Funding & Sponsors
Funding source category [1]
297701
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University
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Name [1]
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Auckland Academic Health Alliance Collaboration Fund, the Auckland District Health Board and the University of Auckland
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Address [1]
297701
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C/- University of Auckland
Faculty of Medical and Health Sciences
Private Bag 92019 AMC
Auckland 1142
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Country [1]
297701
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New Zealand
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Funding source category [2]
301946
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Charities/Societies/Foundations
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Name [2]
301946
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Neurological Foundation of New Zealand
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Address [2]
301946
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66 Grafton Rd
Grafton
Auckland 1010
New Zealand
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Country [2]
301946
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New Zealand
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Primary sponsor type
University
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Name
The University of Auckland
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Address
Private Bag 92019 AMC
Auckland 1142
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Country
New Zealand
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Secondary sponsor category [1]
296733
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None
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Name [1]
296733
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None
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Address [1]
296733
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Country [1]
296733
0
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Other collaborator category [1]
279760
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Government body
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Name [1]
279760
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Auckland District Health Board
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Address [1]
279760
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2 Park Rd
Grafton
Auckland 1023
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Country [1]
279760
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New Zealand
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Ethics approval
Ethics application status
Approved
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Ethics committee name [1]
298772
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New Zealand Health and Disability Ethics Committee
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Ethics committee address [1]
298772
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Ministry of Health Health and Disability Ethics Committees PO Box 5013 Wellington 6140
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Ethics committee country [1]
298772
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New Zealand
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Date submitted for ethics approval [1]
298772
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01/11/2017
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Approval date [1]
298772
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14/02/2018
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Ethics approval number [1]
298772
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Summary
Brief summary
Stroke is a leading cause of long-term adult disability. The most common rehabilitation goal after stroke is to be able to walk again. However, of those initially unable to walk, only 60-70% recover the ability to walk independently by 6 months. Predicting the recovery of walking after stroke may assist clinicians, patients and their families to set realistic and attainable goals during rehabilitation and to make more informed decisions around discharge planning. Decisions around whether a patient is able to return to their own home after the stroke or whether they need to move into a residential care facility are often based on the ability to walk independently. Our research group has recently developed the TWIST (Time to Walk Independently after Stroke Trial) algorithm that enables a clinician, at 1 week after stroke, to predict not only whether an individual patient will walk independently, but when they will achieve this. The algorithm correctly predicted time to walk independently for 92% of patients. The purpose of this observational study is to evaluate and validate the TWIST algorithm in a larger patient sample.
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Trial website
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Trial related presentations / publications
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Public notes
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Contacts
Principal investigator
Name
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Prof Cathy Stinear
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Address
78186
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Department of Medicine
University of Auckland
Private Bag 92019 AMC
Auckland 1142
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Country
78186
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New Zealand
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Phone
78186
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+6499233779
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Fax
78186
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Email
78186
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[email protected]
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Contact person for public queries
Name
78187
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Marie-Claire Smith
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Address
78187
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Department of Medicine
University of Auckland
Private Bag 92019 AMC
Auckland 1142
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Country
78187
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New Zealand
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Phone
78187
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+6499236919
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Fax
78187
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Email
78187
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[email protected]
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Contact person for scientific queries
Name
78188
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Marie-Claire Smith
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Address
78188
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Department of Medicine
University of Auckland
Private Bag 92019 AMC
Auckland 1142
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Country
78188
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New Zealand
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Phone
78188
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+6499236919
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Fax
78188
0
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Email
78188
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[email protected]
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Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
Yes
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What data in particular will be shared?
All requested data.
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When will data be available (start and end dates)?
From 01/01/2021 until 31/12/2026
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Available to whom?
Researchers who request access.
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Available for what types of analyses?
Any.
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How or where can data be obtained?
The research team will evaluate all reasonable requests for data. Anonymised electronic data will be made available in response to approved requests.
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What supporting documents are/will be available?
No Supporting Document Provided
Results publications and other study-related documents
Documents added manually
No documents have been uploaded by study researchers.
Documents added automatically
No additional documents have been identified.
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