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Record W3201428576 · doi:10.1097/md.0000000000027260

Efficacy and safety of Zhen Wu Decoction against chronic heart failure

2021· article· en· W3201428576 on OpenAlexaff
Jian Liang, Xianming Tao, Dabi Hu, Yi Cao

Bibliographic record

VenueMedicine · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsMedicineHeart failureDecoctionTraditional medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Chronic heart failure (CHF) is the end stage of several cardiac diseases. 50% of patients with severe CHF would survive less than 1 year, which has seriously affected patients' survival and quality of life. The current modern therapy could improve survival and quality of life. However, a larger number of patients still suffer from repeated hospitalization, unsatisfactory efficacy, and many side effects. In China, Zhen Wu Decoction (ZWD), a classic prescription recorded in Treatise on Febrile Diseases, was widely used for CHF. In this study, we try to conduct a prospective, double-blinded, randomized, controlled study to evaluate the efficacy and safety of ZWD in the treatment of CHF patients in China. METHODS: Patients will be randomly divided into treatment group and control group in 1:1 ratio. Guideline directed medical therapies and ZWD will be provided for patients in treatment group, while guideline directed medical therapies and ZWD-granules simulations for control group. Left ventricular ejection fraction, left ventricular end diastolic diameter, left ventricular end systolic diameter, b-type natriuretic peptide, NT-proBNP, peak VO2, VO2 maximum, exercise time, and walking distance will be recorded. The data will be analyzed by SPSS 22.0. CONCLUSIONS: The results will evaluate the efficacy and safety of ZWD in the treatment of CHF patients. TRIAL REGISTRATION: OSF registration number: DOI 10.17605/OSF.IO/G3QNU.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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 designBench or experimental
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

Citations2
Published2021
Admission routes1
Has abstractyes

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