MétaCan
Menu
Back to cohort
Record W7075649019

Effectiveness of internet-based exercises aimed at treating knee osteoarthritis (iBEAT-OA): a randomized clinical trial

2021· other· en· W7075649019 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNottingham ePrints (University of Nottingham) · 2021
Typeother
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisRandomized controlled trialPittsburgh Sleep Quality IndexWOMACQuality of life (healthcare)Clinical trialIntervention (counseling)HamstringRating scaleKnee pain
DOInot available

Abstract

fetched live from OpenAlex

Importance Osteoarthritis is a prevalent, debilitating and costly chronic disease for which recommended first-line treatment is underused. Objective To compare the effect of digital treatment for knee osteoarthritis via app versus routine self-management in a randomized, parallel-group clinical trial. Design A 6-week randomised controlled trial (iBEAT-OA) started in winter 2018. Setting Primary care. Participants 551 participants, 45 years or older, with a diagnosis of knee osteoarthritis from an existing primary care database or from social media advertisements, were invited. Intervention The intervention (n=48) and control group (n=57) conformed to first-line knee osteoarthritis treatment. For intervention group, treatment was delivered via a smartphone application. The control group received routine self-management care. Main outcome and measures Primary outcome at 6 weeks was change from baseline in self-reported pain during the last seven days, reported on a Numerical Rating Scale (NRS, 0-10, 0 no pain, 10 worst pain), compared between the two groups. Secondary outcomes included two physical functioning scores, hamstring and quadriceps muscle strength, Sleep assessment, the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Pittsburgh Sleep Quality Index (PSQI), General health questionnaire (MSK-HQ), Inflammatory markers on ultrasound (synovial fluid, synovial hypertrophy and hypervascularity) and quantitative sensory testing (QST). Results 48 participants in the intervention group (mean age 65.2, 70.8% female, 30.4 BMI) and 57 participants in the control group (age 68, 64.9% female, 31.9 BMI) completed this study with no notable demographic difference between groups. The intervention group showed a greater NRS pain score decrease at follow-up than the control group (between-group difference -1.5 [95%CI, -0.8 to -2.2; P<0.001]. Similarly, the 30-second sit to stand test (30CST) and Timed Up and Go test (TUAG) improved more in the intervention group, 3.4 (95%CI, -2.2 to -4.5) and -1.8 (95%CI, -0.5 to -3.0), as did the WOMAC subscales for pain, stiffness and physical function (-1.1 [95%CI, -0.2 to -2.0], -1.0 [95%CI, -0.5 to -1.5], and -3.4 [95%CI, -0.7 to -6.2]). The magnitude of within-group changes in pain and function outcomes in the intervention group corresponded to medium to very strong effects. There was no between-group difference seen in actigraphy sleep data, PSQI, MSK-HQ, QST and sonographic features of knee OA. Conclusions and relevance Digitally delivered evidence-based first-line OA treatment is superior to routine self-managed care as usual and can be given without harming people with osteoarthritis. Effect sizes observed in the intervention group correspond to clinically important improvements.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.013
GPT teacher head0.258
Teacher spread0.244 · 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