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[Effect of scalp acupuncture on cognitive function and self-care ability of daily life in patients with traumatic brain injury].

2021· article· en· W3140678936 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTraumatic brain injuryScalpCognitionAcupunctureMedicineBrain functionPhysical medicine and rehabilitationPsychologyNeurosciencePsychiatrySurgeryAlternative medicinePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To observe the therapeutic effect of scalp acupuncture on cognitive dysfunction of traumatic brain injury. METHODS: Seventy patients with cognitive dysfunction of traumatic brain injury were randomly divided into an observation group and a control group, 35 cases in each group. After treatment, 5 cases dropped off in each group. The patients in the control group were treated with cognitive training; the patients in the observation group were treated with cognitive training and scalp acupuncture at Baihui (GV 20), Sishencong (EX-HN 1), Zhisanzhen and Niesanzhen, and the needles were retained for 6 h. The two groups were treated once a day, 6 times a week; one-month treatment was taken as one course, and 3 continuous courses were given. The scores of mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), activity of daily living (ADL) and functional independence measure (FIM) were compared between the two groups before and after treatment. RESULTS: <0.05). CONCLUSION: Scalp acupuncture could improve cognitive function and self-care ability of daily life in patients with traumatic brain injury.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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