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Record W3045667826 · doi:10.13702/j.1000-0607.191015

[Comparision of therapertic effect of different acupuncture methods for knee osteoarthritis].

2020· article· en· W3045667826 on OpenAlexaboutno aff
Yu Chen, Yejuan Jia, Jiu-Heng Lü, Jingxuan Liu, Zi-di Zhang, Ruiqing Wang, Chun‐Sheng Jia

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineZusanliMoxibustionOsteoarthritisWOMACAcupunctureElectroacupunctureTherapeutic effectPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the clinical efficacy of acupuncture, electroacupuncture (EA) and moxibustion in the treatment of knee osteoarthritis (KOA). METHODS: A total of eight-four patients with KOA were randomly and equally divided into acupuncture group, EA group and moxibustion group. Neixiyan (EX-LE40), Dubi (ST35), Heding (EX-LE2), Liangqiu (ST34), Xuehai (SP10), Zusanli (ST36) and Ashi-point on the affected side of the body were punctured with filiform needles or EA (2 Hz/100 Hz) for 30 min. In the moxibustion group, moxibustion was applied to the surrounding area of the affected joint for 60 min. The treatment was conducted once every other day for 4 weeks. The pain degree was assessed by using numerical rating scale (NRS) and the Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) scale (0-240 points) was used to evaluate the severity of KOA. The "Minimal Clinically Important Improvement (MCII)" was used to assess the therapeutic effect after the treatment. RESULTS: <0.05). CONCLUSION: All the three different kinds of acupuncture and moxibustion methods have positively regulatory effect on KOA, and moxibustion is the best for reducing the joint pain and stiffness, and improving the motor function.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.042
GPT teacher head0.357
Teacher spread0.316 · 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 designOther design
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

Citations8
Published2020
Admission routes1
Has abstractyes

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