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Record W3108912619 · doi:10.1186/s40814-020-00729-4

Determining the feasibility of a trial to evaluate the effectiveness of phototherapy versus placebo at reducing pain during physical activity for people with knee osteoarthritis: a pilot randomized controlled trial 

2020· article· en· W3108912619 on OpenAlexaff
Kyle Vader, Abey Bekele Abebe, Mulugeta Bayisa Chala, Kevin Varette, Jordan Miller

Bibliographic record

VenuePilot and Feasibility Studies · 2020
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsOsteoarthritisPhysical therapyMedicineRandomized controlled trialPlaceboKnee painRehabilitationAdverse effectPhysical medicine and rehabilitationAlternative medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although practice guidelines recommend physical activity and exercise for the management of knee osteoarthritis, pain is a common barrier to participation. Phototherapy has been shown to reduce pain intensity for people with knee osteoarthritis, but it is unclear if it reduces pain during physical activity or contributes to improved rehabilitation outcomes. OBJECTIVE: The aim of this study is to assess the feasibility of performing a fully powered randomized controlled trial (RCT) comparing an active phototherapy intervention versus placebo on pain during physical activity for people with knee osteoarthritis. METHODS: A pilot RCT was conducted to test the feasibility of a trial comparing 8-sessions (4 weeks) of active phototherapy versus placebo. People were able to participate if they (1) were an English speaking adult (> 18 years of age), (2) had received a diagnosis of knee osteoarthritis from a physician, and (3) self-reported experiencing pain and disability related to their knee osteoarthritis for > 3 months. Primary outcomes were the feasibility of participant recruitment, retention, assessment procedures, and maintaining high treatment fidelity. Secondary outcomes piloted for a full trial included pain during physical activity (primary outcome of full trial); self-reported pain severity, physical function, stiffness, adherence to prescribed exercise, global rating of change, patient satisfaction, and adverse events; 6-min walk test; and pressure pain threshold. RESULTS: Twenty participants (4 men; 16 women) with knee osteoarthritis and a mean age of 63.95 (SD: 9.27) years were recruited over a 3-week period (6.7 participants per week). Fifteen out of 20 (75%) of participants completed the primary outcome assessment at 4 weeks and 19/20 (95%) of participants were retained and completed the final 16-week assessment. Overall, 89% of all assessment items were completed by participants across all time-points. Fifteen out of 20 participants (75%) completed all 8 treatment sessions. Treatment fidelity was 100% for all completed treatment sessions. No adverse events were reported by participants in either group. CONCLUSIONS: Results suggest that the trial methodology and intervention are feasible for implementation in a fully powered randomized controlled trial to determine the effectiveness of phototherapy at reducing pain during physical activity for people with knee osteoarthritis. TRIAL REGISTRATION: ClinicalTrials.gov , NCT04234685 , January 21, 2020-Retrospectively registered.

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)0.044
metaresearch head score (Gemma)0.044
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: none
Teacher disagreement score0.044
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.044
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.130
GPT teacher head0.402
Teacher spread0.272 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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