Comparison of the Prophylactic Effect Between Acupuncture and Acupressure on Menstrual Migraine: Results of a Pilot Study
Bibliographic record
Abstract
OBJECTIVES: To compare between acupuncture and acupressure for preventing menstrual migraine (MM). METHODS: MM is one kind of migraine associated with menses in female. It is often associated with increased menstrual distress and disability, leading to decreased daily activity and quality of life. A randomized and controlled pilot study was conducted with three groups: verum acupuncture (VA) group, acupressure (AP) group, and control acupuncture (CA) group. The study lasted for 7 cycle-months, with a 1 cycle-month baseline observation (T1), a 3 cycle-month intervention (3 times per cycle-month) (T2-T4), and a 3 cycle-month follow-up (T5-T7). Outcome measures were number of migraine days, average and peak pain, total duration period of MM, and percentage of patients with ≥50% reduction in the number of MM days. RESULTS: A total of 18 participants were included in the analysis (VA, n = 7; AP, n = 6; CA, n = 5). Both VA and AP were significantly more effective than CA for reducing MM days during the intervention period. Both VA and AP tended to be more effective than CA for reducing peak pain during the intervention period. No significant differences for the outcomes were observed among VA, AP, and CA during the follow-up period. No serious adverse events were reported. DISCUSSION: Results of the pilot study suggest that both VA and AP could be considered as alternative and safe prophylactic interventions for MM. Register ClinicalTrials.gov Identifier: NCT02592681.
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 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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".