Effects of Noninvasive Electroacupuncture at <i>Hegu</i> (LI4) and <i>Sanyinjiao</i> (SP6) Acupoints on Dysmenorrhea: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: This study aimed to evaluate the effects of noninvasive acupoint stimulation therapy with middle-frequency electrical waves on dysmenorrhea in young women. METHODS: This randomized controlled trial enrolled 66 gynecology patients who had primary dysmenorrhea, which was defined as painful menstruation without pelvic pathology (secondary dysmenorrhea). Pathology was ruled out by gynecological ultrasound examination and serum concentration of CA-125. Subjects were randomly assigned to an experimental group (n=34) and control group (n=32). Main outcome measures included McGill Questionnaire Short-form and numerical rating scale for pain intensity. Acupuncture-like trancutaneous electrical nerve stimulation (AL-TENS) of middle-frequency (1000 Hz-10,000 Hz) was applied at Hegu (LI4) and Sanyinjiao (SP6) points in the experimental group twice weekly for 8 weeks; the control group received AL-TENS on nonacupoints. Pre- and postintervention results were recorded. RESULTS: Prior to AL-TENS intervention, no significant differences were found in pain scale and pain intensity between experimental and control groups. After AL-TENS intervention, average total pain score in the experimental group was significantly lower than in the control group (experimental group 2.9±1.2, control group 5.4±2.2; p<0.001). Significant differences were observed between experimental and control groups in average change in pain scores between pre- and postintervention (experimental group 4.5±1.9, control group 1.39±2.0; p<0.001). Pain severity at postintervention was also significantly different between groups (p<0.001). CONCLUSIONS: Noninvasive electro-acupuncture stimulation therapy with middle-frequency electric waves applied at both Hegu (LI4) and Sanyinjiao (SP6) acupoints mitigates pain in dysmenorrhea.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".