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Record W2364800057

Comparative observation of scapulohumeral periarthritis treated with kinetic acupuncture on the distal points of the affected meridians

2010· article· en· W2364800057 on OpenAlexaboutno aff
Mao Xiang

Bibliographic record

Venue世界针灸杂志(英文版) · 2010
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcupunctureShoulder jointSurgeryFrozen shoulderRange of motion
DOInot available

Abstract

fetched live from OpenAlex

Objective To compare the clinical therapeutic effects on scapulohumeral periarthritis between kinetic acupuncture on the distal points of the affected meridians and shoulder three-needle therapy.Methods Fifty cases of scapulohumeral periarthritis were randomly divided into an observation group and a control group,25 cases for each.The cases in observation group were treated with kinetic acupuncture on the distal points of the affected meridians.For example,the case of Hand-Taiyin type was treated with Yuji (鱼际 LU 10) and the case of Hand-Yangming type was treated with Hegǔ (合谷 LI 4),etc.The cases in control group were treated with shoulder three-needle therapy,in which,Jiānqian (肩前 Extral),Jiānyu (肩髃 LI 15) and Jiānliao (肩髎 TE 14) were selected;7 days of treatment made one session,totally 2 sessions were required.Results In observation group,the curative rate based on ROM of shoulder joint was 72.0% (18/25),which was superior to that of 40.0% (10/25) in control group (P0.05).After treatment,the improvements of McGill SF-MPQ score,VAS and PPI in observation group were all superior to those in control group (all P0.05).Conclusion The kinetic acupuncture on the distal points of the affected meridians is advantageous at analgesia and motor improvements of shoulder joint in treatment of scapulohumeral periarthritis as compared with shoulder three-needle therapy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.022
GPT teacher head0.282
Teacher spread0.259 · 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 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

Citations1
Published2010
Admission routes1
Has abstractyes

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