Acupuncture for chronic stable angina pectoris based on the theory of Meridian-Viscera Association: study protocol for a multicenter randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Acupuncture has long been used to treat chronic stable angina pectoris (CSAP), but the acupuncture prescription for CSAP varies. This trial will compare the therapeutic effects between the acupoints on the Heart Meridian and the acupoints on the Lung Meridian for treating CSAP, so as to provide a better prescription for acupuncture treatment of CSAP. METHODS: This is a multicenter randomized controlled trial. A total of 148 CSAP patients will be randomly allocated into two groups through central randomization in a 1:1 ratio. This trial will include a 2-week screening period, a 4-week treatment period, and a 4-week follow-up period. The primary outcome is the frequency of angina attacks from baseline to 4 weeks after inclusion. Secondary outcomes include the frequency of angina attacks from baseline to 4 weeks after acupuncture treatment, the pain intensity of angina, total ischemia burden, heart rate variability, QT dispersion, the score of Seattle Angina Questionnaire, and the score of Short-Form of McGill Pain Questionnaire. These outcome measures will be evaluated at baseline, at the end of acupuncture treatment, and at the end of follow-up. DISCUSSION: We hypothesize that the effectiveness of puncturing at acupoints on the Heart Meridian will not be the same as those on the Lung Meridian. The results will provide further evidence of Meridian-Viscera Association theory and references for acupoints selection in the clinical practice. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR1900025804 . Registered on September 9, 2019.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.023 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.052 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".