MétaCan
Menu
Back to cohort
Record W2753598112 · doi:10.5792/ksrr.17.004

Efficacy of JOINS on Cartilage Protection in Knee Osteoarthritis: Prospective Randomized Controlled Trial

2017· article· en· W2753598112 on OpenAlexaboutno aff
Joong Il Kim, Ja Young Choi, Kwang Gi Kim, Myung Chul Lee

Bibliographic record

VenueKnee Surgery and Related Research · 2017
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsOsteoarthritisRandomized controlled trialJoinsMedicinePhysical therapyCartilagePhysical medicine and rehabilitationSurgeryComputer scienceAlternative medicineAnatomyPathology

Abstract

fetched live from OpenAlex

Purpose: In this study, we compared the clinical efficacy of JOINS (SKI306X, SK Chemicals) with placebo on cartilage protection using magnetic resonance imaging (MRI). Materials and Methods: Sixty-nine patients were randomized to the JOINS group (200 mg, three times daily for 1 year; n=33) or the placebo group (n=36). Changes in cartilage volume and thickness were measured using MRI. Changes in the delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) index, subchondral bone marrow abnormality scores, and clinical scores including knee pain visual analog scale (VAS) score and Korean Western Ontario and McMaster Universities Osteoarthritis Index (K-WOMAC) were also evaluated. Results: Changes in cartilage thickness and volume and subarticular bone marrow abnormality scores were not different between groups. Changes in the dGEMRIC index in the lateral tibial plateau were greater in the JOINS group than in the placebo group (19.64±114.33 msec vs. -57.77±123.30 msec; p=0.011). Significantly greater changes in VAS were observed in the JOINS group than in the placebo group (-26.00±12.25 vs. -12.47±21.54; p=0.002) and K-WOMAC (-15.42 ± 7.73 vs. -8.15±13.71; p=0.003). Conclusions: Compared with placebo, JOINS had superior clinical efficacy in regard to cartilage protection.

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 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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.322
Teacher spread0.284 · 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 teacher head, 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

Citations11
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueKnee Surgery and Related ResearchSame topicOsteoarthritis Treatment and MechanismsFrench-language works237,207