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Record W4286214323 · doi:10.1155/2022/2755332

Clinical Application of Traditional Chinese Medicine Therapy for Type 2 Diabetes Mellitus: An Evidence Map

2022· review· en· W4286214323 on OpenAlexaboutno aff
Ying Wang, Zelei Dai, Qin Wang, Ying He, Yalan Peng, Miaomiao Wu, Haiqi Song, Long Ma, Yonggang Zhang, Nian Li

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicTraditional Chinese Medicine Analysis
Canadian institutionsnot available
FundersDepartment of Science and Technology of Sichuan ProvinceNational Natural Science Foundation of China
KeywordsMedicineTraditional Chinese medicinePillAlternative medicineTraditional medicineEtiologyMEDLINEWeb of scienceType 2 Diabetes MellitusInternal medicineDiseaseIntensive care medicineDiabetes mellitusMeta-analysisPharmacologyPathology

Abstract

fetched live from OpenAlex

Type 2 diabetes mellitus (T2DM), a common disease with a complex etiology in the world, is an important risk factor for severe cardiovascular and cerebrovascular diseases. However, treatments of T2DM are mainly based on Western medicine, whose severe side effects make traditional Chinese medicine (TCM) therapy more appealing to patients and clinicians. The overall clinical evidence for different TCM therapies in the treatment of T2DM is still unclear. This study aimed to adopt the evidence-mapping method and integrate the evidence from various researches on this topic, to depict the whole picture of TCM therapies for T2DM. This review included searches of PubMed, Embase, Web of Science, and three major Chinese literature databases (CNKI, VIP, and Wanfang) from inception to November 18, 2021. Two independent reviewers screened the literature, extracted information, and evaluated the quality of all included studies. A systematic review was subsequently performed. In total, 47 studies were reviewed, of which 46 studies (97.9%) were from China and 1 (2.1%) was from Canada. The evidence map was conducted according to different TCM therapies, including herbs or herbal extracts, compounds, powders, decoctions, pills, external treatment, basic theories and treatment principles of TCM, proprietary Chinese medicines, and unspecified TCM integrated therapies. According to the AMSTAR-2 scoring results, 4 papers were rated as high quality, 11 were low quality, and 32 were very low quality. Outcome indicators mainly focused on FBG, HbA1c, 2-h PBG, TC, TG, LDL-C, etc. The results showed that different types of TCM treatment had different improvement effects on the outcome indicators of T2DM. More consistent benefits were observed in the improvement of FBG, HbA1c, and 2-h PBG with treatment regimens based on basic theories and treatment principles of TCM, decoctions and pills, and unspecified TCM integrated therapies. Among herbs, ginger and Coptis root showed more improvement in all outcomes. Compounds, powders, and external treatment showed relatively consistent beneficial effects on the improvement of FBG. No serious adverse events were reported. Overall, the current evidence map provided an intuitive overview of the beneficial effects of TCM therapies in the treatment of type 2 diabetes. This study can be used as a reference for the clinical application of traditional Chinese medicine in T2DM, but due to the low-quality level of the included studies, it should be treated with caution in clinical practices.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.414
GPT teacher head0.493
Teacher spread0.079 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations10
Published2022
Admission routes1
Has abstractyes

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