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Record W4307424969 · doi:10.13702/j.1000-0607.20210968

[Clinical observation of acupotomy combined with warm needling for cervical spondylotic radiculopathy of qi and blood stagnation syndrome].

2022· article· en· W4307424969 on OpenAlexaboutno aff
Ailin Li, Xuewen Wang, JinRong Wang, Yu Fang, Quan Li, Hao-Nan Feng, Ling-Su Liu

Bibliographic record

VenuePubMed · 2022
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDry needlingMedicineClinical efficacyAnesthesiaSurgeryAcupunctureDefecationMcGill Pain QuestionnaireCervical spondylosisTherapeutic effectRating scaleVisual analogue scalePsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: and blood stagnation syndrome. METHODS: A total of 90 CSR patients were randomly divided into an acupotomy group, a warm needling group and a combined treatment group, with 30 cases in each group. The patients in the acupotomy group were treated with acupotomy, once every 7 days, consecutively for 3 times. The patients in the warm needling group received warm needling, once daily, at the interval of 2 days after consecutive treatments for 5 days, 7 days as one session of treatment and 3 consecutive sessions were required. The patients in the combined treatment group were treated with acupotomy and warm needling, and the methods and the treatment session were same as the the previous two groups. Before and after the treatment, the pain rating index (PRI) of McGill pain questionnaire (MPQ) and the 20-point scale of CSR developed by Yasuhisa Tanaka (CSR20) were adopted in the assessment. The changes of clinical symptoms and functions of patients were observed and the clinical efficacy was assessed in each group. RESULTS: <0.05). CONCLUSION: and blood stagnation syndrome. Its efficacy is remarkably higher than that of the simple application of acupotomy or warm needling.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.290
Teacher spread0.245 · 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 designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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