Effects of Gyejibongnyeong-hwan on dysmenorrhea caused by blood stagnation: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Gyejibongnyeong-hwan (GJBNH) is one of the most popular Korean medicine formulas for menstrual pain of dysmenorrhea. The concept of blood stagnation in Korean medicine is considered the main factor of causing abdominal pain, or cramps, during menstrual periods. To treat the symptoms, GJBNH is used to fluidify the stagnated blood and induce the blood flow to be smooth, reducing pain as the result. The purpose of this trial is to identify the efficacy of GJBNH in dysmenorrhea caused by blood stagnation. METHODS: This study is a multi-centre, randomised, double-blind, controlled trial with two parallel arms: the group taking GJBNH and the group taking placebo. 100 patients (women from age 18 to 35) will be enrolled to the trial. Through randomization 50 patients will be in experiment arm, and the other 50 patients will be in control arm. At the second visit (baseline), all participants who were already screened that they fulfil both the inclusion and the exclusion criteria will be randomised into two groups. Each group will take the intervention three times per day during two menstrual cycles. After the treatment for two cycles, each patient will be followed up during their 3rd, 4th and 5th menstrual cycles. From the screening (Visit 1) through the second follow-up (Visit 6) the entire process will take 25 weeks. DISCUSSION: This trial will provide evidence for the effectiveness of GJBNH in treating periodical pain due to dysmenorrhea that is caused by blood stagnation. The primary outcome between the two groups will be measured by changes in the Visual Analogue Score (VAS) of pain. The secondary outcome will be measured by the Blood Stagnation Scale, the Short-form McGill questionnaire and the COX menstrual symptom scale. Analysis of covariance (ANCOVA) and repeated measured ANOVA will be used to analyze the data analysis. TRIAL REGISTRATION: Current Controlled Trials: ISRCTN30426947.
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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 | 0.023 | 0.021 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.007 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.063 | 0.010 |
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".