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Record W2382504712

Clinical research of needling Thirteen Ghost points on depression patients with cognitive dysfunction

2014· article· en· W2382504712 on OpenAlexaboutno aff
Jin Hu

Bibliographic record

VenueJournal of Jinan University · 2014
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentDepression (economics)Dry needlingMedicineCognitionSignificant differenceCognitive impairmentAcupuncturePhysical therapyInternal medicinePsychiatryAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

Aim: To reveal the effect of the Thirteen Ghost Points( Renzhong,Shaoshang,Yingbai,Daling,Shenmai,Fengfu,Jiache,Chengjiang,Laogong,Shangxing,Quchi) treating the cognitive dysfunction of patients with depression. Methods: Eighty patients are divided as figure randomly into routine treatment group and acupuncture Thirteen Ghost Points group. 4 weeks as a course. Given marks to each patient before and after treatment using Montreal cognitive assessment scale( MoCA,Chinese version),the mini mental state examination( MMSE) and activity of daily living scale( ADL) score. SPSS 19. 0was used on all data. Paired samples t test was used within groups,chi square test was used between groups. P 0. 05 was statistically significant. Results: All patients were gotten significant difference between before and after treat( P 0. 05). On the MoCA and ADL scores,Thirteen Ghost points group got a better achievement than routine drug group. Conclusion: Acupuncture Thirteen Ghost points is effectiveon cognitive dysfunction patients with depression. This treatment has seldom side effect.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.050
GPT teacher head0.366
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 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

Citations0
Published2014
Admission routes1
Has abstractyes

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