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Record W2895458276 · doi:10.1136/bmjopen-2018-023838

Acupuncture treatment for knee osteoarthritis with sensitive points: protocol for a multicentre randomised controlled trial

2018· article· en· W2895458276 on OpenAlexaffabout
Li Tang, Pengli Jia, Ling Zhao, Deying Kang, Yanan Luo, Jiali Liu, Ling Li, Hui Zheng, Ying Li, Ning Li, Gordon Guyatt, Xin Sun

Bibliographic record

VenueBMJ Open · 2018
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsMcMaster UniversityImpact
FundersNational Natural Science Foundation of China
KeywordsMedicineAcupuncturePhysical therapyOsteoarthritisRandomized controlled trialClinical trialPopulationProtocol (science)Alternative medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: There is a lack of curative medical treatment for patients with knee osteoarthritis (KOA). Acupuncture represents an important alternative therapy. According to the theory of traditional Chinese medicine and preliminary clinical evidence, the patients' acupoints and tender points may become sensitised when the body suffers from a disease state; stimulation of such sensitive points could lead to a disease improvement. It is thus hypothesised that acupuncture at highly sensitised points on patients with KOA would achieve better treatment outcomes than acupuncture at low/non-sensitised points. Previously, we conducted a pilot trial to prove the feasibility of further investigation. METHODS AND ANALYSIS: A three-arm, parallel, multicentre randomised controlled trial of 666 patients will be conducted at four hospitals of China. Eligible patients with KOA who consent to participate will be randomly assigned to a high-sensitisation group (patients receive acupuncture treatment at high-sensitive points), a low/non-sensitisation group (patients receive acupuncture treatment at low/non-sensitive points) or a waiting-list group (patients receive standard acupuncture treatment after the study is concluded) via a central randomisation system using 1:1:1 ratio. The primary outcome is the change of Western Ontario and McMaster Universities Osteoarthritis Index total score from baseline to 16 weeks. Outcome assessors and data analysts will be blinded and participants will be asked not to reveal their allocation to assessors. The outcome analyses will be performed both on the intention-to-treat and per-protocol population. The primary analyses will test if acupuncture at highly sensitised points would achieve statistically better treatment outcomes than acupuncture at low/non-sensitised points and no acupuncture (ie, waiting list), respectively. A small number of prespecified subgroup analyses will be conducted. ETHICS AND DISSEMINATION: Ethics approval has been granted by the Bioethics Subcommittee of West China Hospital, Sichuan University: 2017 (Number 228). Results will be expected to be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03299439.

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)0.001
metaresearch head score (Gemma)0.002
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.089
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.079
GPT teacher head0.454
Teacher spread0.375 · 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
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

Citations26
Published2018
Admission routes2
Has abstractyes

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