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Record W1983197676 · doi:10.1186/1472-6882-13-59

Moxibustion for treating knee osteoarthritis: study protocol of a multicentre randomised controlled trial

2013· article· en· W1983197676 on OpenAlexaboutno aff
Seunghoon Lee, Kun Hyung Kim, Tae‐Hun Kim, Jung-Eun Kim, Joo‐Hee Kim, Jung Won Kang, Kyung‐Won Kang, So‐Young Jung, Ae‐Ran Kim, Hyo‐Ju Park, Mi‐Suk Shin, Kwon-Eui Hong, Ho-Sueb Song, Jin-Bong Choi, Hyungjun Kim, Sun‐Mi Choi

Bibliographic record

VenueBMC Complementary and Alternative Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
FundersKorea Institute of Oriental MedicineSemyung University
KeywordsMoxibustionMedicineOsteoarthritisAcupuncturePhysical therapyRandomized controlled trialClinical trialAlternative medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The treatment of knee osteoarthritis, which is a major cause of disability among the elderly, is typically selected from multidisciplinary options, including complementary and alternative medicine. Moxibustion has been used in the treatment of knee osteoarthritis in Korea to reduce pain and improve physical activity. However, there is no sufficient evidence of its effectiveness, and it cannot therefore be widely recommended for treating knee osteoarthritis. We designed a randomised controlled clinical trial to evaluate the effectiveness, safety, cost-effectiveness, and qualitative characteristics of moxibustion treatment of knee osteoarthritis compared to usual care. METHODS/DESIGNS: This is a protocol for a multicentre, pragmatic, randomised, assessor-blinded, controlled, parallel-group study. A total of 212 participants will be assigned to the moxibustion group (n = 106) and the usual care group (n = 106) at 4 clinical research centres. The participants assigned to the moxibustion group will receive moxibustion treatment of the affected knee(s) at 6 standard acupuncture points (ST36, ST35, ST34, SP9, Ex-LE04, and SP10) 3 times per week for 4 weeks (a total of 12 sessions). Participants in the usual care group will not receive moxibustion treatment during the study period. Follow-up will be performed on the 5th and 13th weeks after random allocation. Both groups will be allowed to use any type of treatment, including surgery, conventional medication, physical treatment, acupuncture, herbal medicine, over-the-counter drugs, and other active treatments. Educational material that explains knee osteoarthritis, the current management options, and self-exercise will be provided to each group. The global scale of the Korean Western Ontario and McMaster Osteoarthritis Index (K-WOMAC) will be the primary outcome measurement used in this study. Other subscales (pain, stiffness, and function) of the K-WOMAC, the Short-Form 36v2 Health Survey, the Beck Depression Inventory, the Physical Function test, Patient Global Assessment, and the Pain Numerical Rating Scale will be used as outcome variables to evaluate the effectiveness of moxibustion. Safety will be assessed at every visit. In addition, an economic evaluation and a qualitative study will be conducted as a mixed-methods approach. DISCUSSION: This trial may contribute to developing evidence for the effectiveness and safety of moxibustion for treating knee osteoarthritis. TRIAL REGISTRATION NUMBER: KCT0000130.

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)0.045
metaresearch head score (Gemma)0.038
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.060
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.038
Meta-epidemiology (narrow)0.0080.003
Meta-epidemiology (broad)0.0170.008
Bibliometrics0.0030.004
Science and technology studies0.0030.004
Scholarly communication0.0040.004
Open science0.0040.002
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0600.009

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 head0.058
GPT teacher head0.396
Teacher spread0.338 · 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
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

Citations20
Published2013
Admission routes1
Has abstractyes

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