Exercise training and reproductive outcomes in women with polycystic ovary syndrome: A pilot randomized controlled trial
Bibliographic record
Abstract
Abstract Objective Exercise is recommended for polycystic ovary syndrome (PCOS), but the most effective exercise prescription is unclear. This trial compared effects of high‐intensity interval training (HIIT), continuous aerobic exercise training (CAET) and no‐exercise control on reproductive, anthropometric and cardiometabolic outcomes in PCOS. Design Pilot randomized controlled trial. Participants Previously inactive women aged 18–40 years with PCOS. Measurements Feasibility outcomes included recruitment, retention, adherence to exercise and daily ovulation prediction kit (OPK) testing. Preliminary efficacy outcomes included reproductive, anthropometric and cardiometabolic health markers. Results Forty‐seven women were randomized to no‐exercise control (n = 17), HIIT (n = 16), or CAET (n = 14). Forty (85%) participants completed the trial. Median exercise adherence was 68% (IQR 53%, 86%). Median daily OPK‐testing adherence in the first half of the intervention was 87% (IQR 61%, 97%) compared with 65% (IQR 0%, 96%) in the second half. Body mass index decreased significantly in CAET compared with control (−1.0 kg/m2, p = .01) and HIIT (−0.9 kg/m2, p = .04). Mean waist circumference decreased in all groups (−7.3 cm, −6.9 cm, −4.5 cm in HIIT, CAET and control) with no significant between‐group differences. Mean LDL‐C was significantly reduced for HIIT compared to CAET (−0.33 mmol/L, p = .03). HDL‐C increased in HIIT compared with control (0.18 mmol/L, p = .04). Conclusions There were feasibility challenges with adherence to daily ovulation assessment limiting the ability to analyse the effect of the exercise interventions on ovulation. CAET and HIIT were both effective at improving anthropometrics and some cardiometabolic health markers. Further studies need to determine optimal and acceptable exercise prescriptions for this population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".