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[Warming acupuncture combined with conventional acupuncture for diabetic peripheral neuropathy with syndrome of <i>yang</i> deficiency and cold coagulation, obstruction of collaterals and blood stasis].

2018· article· en· W2990529002 on OpenAlexaboutno aff
Guoqing Ma, Ting Ye, Zhongren Sun

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAcupunctureZusanliBlood stasisPeripheral neuropathySurgeryDiabetes mellitusNerve conduction velocityAnesthesiaInternal medicineTraditional Chinese medicineEndocrinologyElectroacupuncturePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: deficiency and cold coagulation, obstruction of collaterals and blood stasis. METHODS: A total of 64 patients were randomly divided into a warming acupuncture group and a conventional acupuncture group, 32 cases in each one. Based on basic treatment of blood glucose regulation, warming acupuncture was applied at Pishu (BL 20), Shenshu (BL 23), Guanyuanshu (BL 26), Zusanli (ST 36), Chongyang (ST 42), Quchi (LI 11) and Hegu (LI 4) in the warming acupuncture group, while acupuncture was applied at the identical acupoints in the conventional acupuncture group. Both the treatments were given once a day with an interval of one day every six days; totally the treatment was given for 4 weeks. The TCM symptom score, Toronto clinical scoring system (TCSS) and nerve conduction velocity (NCV) before and after treatment were compared in the two groups. RESULTS: >0.05). CONCLUSION: deficiency and cold coagulation, obstruction of collaterals and blood stasis; warming acupuncture has advantage in symptom improvement.

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)0.000
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 score0.004
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.230
Teacher spread0.216 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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