Impact of electro-acupuncture and physical exercise on hyperandrogenism and oligo/amenorrhea in women with polycystic ovary syndrome: a randomized controlled trial
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS), the most common endocrine disorder in women of reproductive age, is characterized by hyperandrogenism, oligo/amenorrhea, and polycystic ovaries. We aimed to determine whether low-frequency electro-acupuncture (EA) would decrease hyperandrogenism and improve oligo/amenorrhea more effectively than physical exercise or no intervention. We randomized 84 women with PCOS, aged 18-37 yr, to 16 wk of low-frequency EA, physical exercise, or no intervention. The primary outcome measure changes in the concentration of total testosterone (T) at week 16 determined by gas and liquid chromatography-mass spectrometry was analyzed by intention to treat. Secondary outcome measures were changes in menstrual frequency; concentrations of androgens, estrogens, androgen precursors, and glucuronidated androgen metabolites; and acne and hirsutism. Outcomes were assessed at baseline, after 16 wk of intervention, and after a 16-wk follow-up. After 16 wk of intervention, circulating T decreased by -25%, androsterone glucuronide by -30%, and androstane-3α,17β-diol-3-glucuronide by -28% in the EA group (P = 0.038, 0.030, and 0.047, respectively vs. exercise); menstrual frequency increased to 0.69/month from 0.28 at baseline in the EA group (P = 0.018 vs. exercise). After the 16-wk follow-up, the acne score decreased by -32% in the EA group (P = 0.006 vs. exercise). Both EA and exercise improved menstrual frequency and decreased the levels of several sex steroids at week 16 and at the 16-wk follow-up compared with no intervention. Low-frequency EA and physical exercise improved hyperandrogenism and menstrual frequency more effectively than no intervention in women with PCOS. Low-frequency EA was superior to physical exercise and may be useful for treating hyperandrogenism and oligo/amenorrhea.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".