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[Moxibustion at different temperatures for cognitive impairment in type 2 diabetes mellitus: a randomized controlled trial].

2025· article· en· W4414263653 on OpenAlexaboutno aff
Wei Yan, Yuejin Qu, Lele Zhang, Min Ye, Qunwei Li, Hongyu Xie

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsType 2 diabetesCognitive impairmentCognitionRandomized controlled trialDiabetes mellitusType 2 Diabetes Mellitus

Abstract

fetched live from OpenAlex

Objective: To observe the effects of moxibustion at different temperatures on cognitive function and blood glucose levels in patients with cognitive impairment associated with type 2 diabetes mellitus (T2DM). Methods: A total of 66 T2DM patients with cognitive impairment were randomly assigned to a high-temperature group (22 cases, 1 case dropped out, 1 case was eliminated), a medium-temperature group (22 cases, 2 cases were eliminated), and a low-temperature group (22 cases, 2 cases were eliminated). All groups received moxibustion at Baihui (GV20), Dazhui (GV14), and Shenting (GV24) based on their existing glycemic control treatment. Moxibustion temperatures were maintained at 44-46 ℃ (high-temperature group), 41-43 ℃ (medium-temperature group), and 38-40 ℃ (low-temperature group), respectively, for 20 min per session, every other day, 3 times a week for 3 months. The Montreal cognitive assessment (MoCA) score, mini-mental state examination (MMSE) score, short-term memory (STM) accuracy and average reaction time, Rey-Osterrieth complex figure (ROCF) score, fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c) were assessed before and after treatment. Clinical efficacy was evaluated after treatment. Results: <0.05). Conclusion: Moxibustion at different temperatures has a dose-effect relationship in treating cognitive impairment in T2DM patients. A temperature range of 44-46 ℃ is more effective in improving cognitive function and stabilizing average blood glucose levels over 2-3 months.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized trialhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.016
GPT teacher head0.294
Teacher spread0.279 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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
Published2025
Admission routes1
Has abstractyes

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