MétaCan
Menu
Back to cohort
Record W7024969666

Traditional Chinese Medicine Treating Dilated Cardiomyopathy: A Literature Review

2025· article· en· W7024969666 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsDigital Payment Technologies (Canada)
Fundersnot available
KeywordsTraditional Chinese medicineDiseaseAlternative medicineAdverse effectMechanism (biology)Dilated cardiomyopathyMEDLINEClinical research
DOInot available

Abstract

fetched live from OpenAlex

Hua Fan, Mengjiao Ma, Longping Peng, Feifei Liu, Tianyi Feng, Youhua Wang Cardiovascular Department, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of ChinaCorrespondence: Youhua Wang, Email doctorwyh@163.comAbstract: Dilated cardiomyopathy (DCM), as a difficult problem in modern medical treatment, has become an important cardiovascular disease threatening human beings all over the world with an increasing incidence rate and mortality. Conservative drug therapy is mainly used in clinical practice, but due to unavoidable adverse reactions such as low blood pressure, it is often difficult to achieve satisfactory prognosis. Traditional Chinese medicine has the characteristics of syndrome differentiation and multi-target treatment for DCM, with few adverse reactions and certain advantages. It has achieved good therapeutic effects in clinical practice. Therefore, we summarized and analyzed the clinical evidence and mechanism of traditional Chinese medicine in the treatment of DCM, and combined with the current research status of this disease to analyze the problems and shortcomings, in order to provide more ideas and methods for the treatment of DCM with traditional Chinese medicine.Keywords: dilated cardiomyopathy, traditional Chinese medicine, clinical evidence, potential mechanisms, research progress

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)0.002
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.164
GPT teacher head0.537
Teacher spread0.373 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicCardiac Fibrosis and RemodelingFrench-language works237,207