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Record W4411294944 · doi:10.1186/s40814-025-01660-2

A feasibility randomised trial evaluating the levitation tri-compartment offloader knee brace for multicompartment knee osteoarthritis

2025· article· en· W4411294944 on OpenAlexafffundabout
Emily L. Bishop, Justin Bonhomme, Chris Cowper‐Smith, Janet L. Ronsky, Marcia Clark

Bibliographic record

VenuePilot and Feasibility Studies · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersMcCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of CalgaryCanadian Institutes of Health ResearchCumming School of Medicine, University of CalgaryMitacsAlberta Health Services
KeywordsBraceOsteoarthritisMedicinePhysical therapyKnee JointPhysical medicine and rehabilitationAlternative medicineSurgeryEngineeringMechanical engineeringPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The Levitation™ "Tri-Compartment Offloader" (TCO) knee brace (Spring Loaded Technology) is designed to reduce pain for individuals with knee osteoarthritis (OA). The TCO is available on the market, however, has not been compared to the current standard of care treatment for knee OA with a controlled clinical trial. This feasibility study aimed to (i) evaluate the feasibility of conducting a full RCT, (ii) evaluate the distributional properties of the Visual Analog Scale (VAS) activity-specific knee pain score to estimate the sample size required for a full randomised controlled trial (RCT), and (iii) refine and optimise the study protocol. METHODS: A prospective, 3-group, parallel, single-centre feasibility RCT of individuals with moderate to severe patellofemoral or multicompartment knee OA was undertaken at the University of Calgary (Alberta, Canada). Participants were randomised using a 1:1:1 random allocation to one of three intervention groups: standard of care (Control), Control plus a knee sleeve (Sleeve), or Control plus a TCO brace (TCO). Participants were assessed at baseline (before intervention) and after 6 weeks and 3 months (primary endpoint) of controlled intervention. The sample size for a full RCT was estimated based on the change in VAS knee pain between baseline and 3 months. Feasibility was assessed using participant recruitment, intervention adherence, participant response rates, data quality, dropout rate and adverse events. All protocol changes made throughout the duration of the study were recorded. RESULTS: Twenty-nine participants (13 females; age: 62 ± 9 years) were recruited. The estimated sample size for a full RCT is 93 individuals (31 per group). Participants showed high intervention adherence and follow-up rates were 86% at 3 months. Four participants dropped out of the study, and there were 3 adverse events reported. Changes were made to participant eligibility criteria, recruitment strategy and data collection methods to improve feasibility, efficiency, and appropriateness for a full RCT. CONCLUSIONS: This study supports the feasibility of a full scale RCT evaluating the clinical effectiveness of the TCO knee brace compared to the current (conservative) standard of care treatment for individuals with knee OA, and an adequately powered RCT is now warranted. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT05543486. Registered 15 September 2022-retrospectively registered, https://clinicaltrials.gov/study/NCT05543486.

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)0.013
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.266
GPT teacher head0.454
Teacher spread0.188 · 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 designRandomized trial
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes3
Has abstractyes

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