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Record W4283219644 · doi:10.3389/fcvm.2022.888569

Effect of Acupuncture on Blood Pressure and Metabolic Profile Among Patients With Essential Hypertension: Protocol of a Randomized Clinical Trial

2022· article· en· W4283219644 on OpenAlexaboutno aff
Pan Zhang, Yalan Chen, Furong Zhang, Hong Pei, Mingsheng Sun, Yuzhu Qu, Jiyao Chen, Ting Du, Xiaoguo He, Fanrong Liang, Weiguo Jia, Mingxiao Yang

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
FundersNational Cancer InstituteNational Natural Science Foundation of China
KeywordsMedicineBlood pressureEssential hypertensionAcupunctureRandomized controlled trialAmbulatory blood pressureInternal medicineClinical trialPhysical therapyPathology

Abstract

fetched live from OpenAlex

Essential hypertension is a polygenic cardiovascular disease that is associated with maladaptive metabolic changes. Acupuncture as a non-pharmacologic intervention is used to lower blood pressure and improve metabolic dysfunction. However, such effects have not been clinically characterized. We will conduct a randomized clinical trial to evaluate the antihypertensive effect of acupuncture among patients with essential hypertension and determine the associated metabolic improvements. This study is a phase II, two-arm, randomized, sham-controlled trial (Trial registration: ChiCTR2100043737), in which biospecimens will be collected for metabolic profiling. A total of 64 patients with a clinical diagnosis of essential hypertension will be randomly assigned to either the acupuncture or the sham acupuncture group in a 1:1 ratio. All participants will receive 10 treatments over 4 weeks, with three sessions per week for the first 2 weeks and two sessions per week for the remaining weeks. The primary outcome is the change of the systolic and diastolic blood pressure measured by the 24-h ambulatory blood pressure monitoring from baseline to 4 weeks. Secondary outcomes include the circadian rhythm of blood pressure, sleep quality measured by the Insomnia Severity Index, cognitive function measured by the Montreal Cognitive Assessment, and others. Fasting blood serum and urine samples will be collected at baseline and 4 weeks for targeted and untargeted metabolomics analysis. We will use the mixed-effects model and other related bioinformatics approaches to analyze the clinical and metabolome data. This metabolomic-based trial will provide important clinical data regarding the efficacy of acupuncture for essential hypertension to better inform evidence-based care delivery for hypertension patients. Moreover, the findings will offer important insights into the mechanism of action of acupuncture for hypertension by revealing its effect on metabolism. The results of this study will be used to inform the design of a statistically powered, multicenter, randomized trial. We will publish the study findings in peer-reviewed journals. The ethical approval of this study has been reviewed and approved by the Sichuan Regional Ethics Review Committee on Traditional Chinese Medicine (ID: 2021KL-006). The outcomes of the trial will be disseminated through peer-reviewed publications.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.298
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.295
Teacher spread0.285 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

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