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Record W2530025644

针刺百会、神庭联合基础治疗和常规康复训练治疗脑卒中后认知障碍:随机对照研究

2016· article· zh· W2530025644 on OpenAlexaboutno aff
詹杰, 广东广州 广州中医药大学, 潘锐焕, 郭友华, 詹乐昌, 何铭锋, 王秋纯, 陈红霞, 广州 广东省中医院广州中医药大学第二附属医院

Bibliographic record

Venue中国针灸 · 2016
Typearticle
Languagezh
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsAcupunctureRehabilitationMedicineMontreal Cognitive AssessmentPhysical therapyTreatment and control groupsCognitionCognitive impairmentMental stateStroke (engine)Mini–Mental State ExaminationPhysical medicine and rehabilitationPsychiatryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective To observe the clinical effect of acupuncture at Baihui(GV 20) and Shenting(GV 24) combined with rehabilitation for post-stroke cognitive impairment(PSCI).Methods Fifty patients with PSCI were randomly assigned to an observation group and a control group,25 cases in each one.In the control group,basic treatment and regular rehabilitation were applied.In the observation group,acupuncture at Baihui(GV 20) and Shenting(GV 24) and the same therapies as the control group were used for continuous four weeks,once a day and five times a week.Mini-mental state examination (MMSE) and Montreal cognitive assessment(MoCA) were observed before and after treatment in the two groups.Results After treatment,the scores of MMSE and MoCA were improved apparently(both P<0.05),with better results in the observation group(both P<0.05).Conclusion Acupuncture at Baihui(GV 20) and Shenting(GV 24) combined with basic treatment and regular rehabilitation can obviously improve the cognitive function of PSCI,and the effect is superior to that of basic treatment and regular rehabilitation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.828
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.023

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 head0.149
GPT teacher head0.469
Teacher spread0.320 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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