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Record W4296709977 · doi:10.1177/17474930221129982

Implementation of increased physical therapy intensity for improving walking after stroke: Walk ’n watch protocol for a multisite stepped-wedge cluster-randomized controlled trial

2022· article· en· W4296709977 on OpenAlexafffund
Sue Peters, Shannon B. Lim, Mark Bayley, Krista L. Best, Louise Connell, Hélène Corriveau, Sarah J. Donkers, Sean P. Dukelow, Tara D. Klassen, Marie-Hélène Milot, Brodie M. Sakakibara, Lisa Sheehy, Hubert Wong, Jennifer Yao, Janice J. Eng

Bibliographic record

VenueInternational Journal of Stroke · 2022
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsBruyèreUniversity of British Columbia, Okanagan CampusUniversity of CalgaryUniversity of SaskatchewanUniversité LavalSt. Paul's HospitalToronto Rehabilitation InstituteUniversity Health NetworkWestern UniversityUniversité de SherbrookeUniversity of TorontoUniversity of British ColumbiaGF Strong Rehabilitation Centre
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsMedicineRehabilitationRandomized controlled trialPhysical therapyStroke (engine)Clinical trialPhysical medicine and rehabilitationProtocol (science)Quality of life (healthcare)Alternative medicineSurgeryNursing

Abstract

fetched live from OpenAlex

RATIONALE: Clinical practice guidelines support structured, progressive protocols for improving walking after stroke. Yet, practice is slow to change, evidenced by the little amount of walking activity in stroke rehabilitation units. Our recent study (n = 75) found that a structured, progressive protocol integrated with typical daily physical therapy improved walking and quality-of-life measures over usual care. Research therapists progressed the intensity of exercise by using heart rate and step counters worn by the participants with stroke during therapy. To have the greatest impact, our next step is to undertake an implementation trial to change practice across stroke units where we enable the entire unit to use the protocol as part of standard of care. AIMS: What is the effect of introducing structured, progressive exercise (termed the Walk 'n Watch protocol) to the standard of care on the primary outcome of walking in adult participants with stroke over the hospital inpatient rehabilitation period? Secondary outcomes will be evaluated and include quality of life. METHODS AND SAMPLE SIZE ESTIMATES: This national, multisite clinical trial will randomize 12 sites using a stepped-wedge design where each site will be randomized to deliver Usual Care initially for 4, 8, 12, or 16 months (three sites for each duration). Then, each site will switch to the Walk 'n Watch phase for the remaining duration of a total 20-month enrolment period. Each participant will be exposed to either Usual Care or Walk 'n Watch. The trial will enroll a total of 195 participants with stroke to achieve a power of 80% with a Type I error rate of 5%, allowing for 20% dropout. Participants will be medically stable adults post-stroke and able to take five steps with a maximum physical assistance from one therapist. The Walk 'n Watch protocol focuses on completing a minimum of 30 min of weight-bearing, walking-related activities (at the physical therapists' discretion) that progressively increase in intensity informed by activity trackers measuring heart rate and step number. STUDY OUTCOME(S): The primary outcome will be the change in walking endurance, measured by the 6-Minute Walk Test, from baseline (T1) to 4 weeks (T2). This change will be compared across Usual Care and Walk 'n Watch phases using a linear mixed-effects model. Additional physical, cognitive, and quality of life outcomes will be measured at T1, T2, and 12 months post-stroke (T3) by a blinded assessor. DISCUSSION: The implementation of stepped-wedge cluster-randomized trial enables the protocol to be tested under real-world conditions, involving all clinicians on the unit. It will result in all sites and all clinicians on the unit to gain expertise in protocol delivery. Hence, a deliberate outcome of the trial is facilitating changes in best practice to improve outcomes for participants with stroke in the trial and for the many participants with stroke admitted after the trial ends.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.027
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0240.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.360
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes2
Has abstractyes

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