Bone health and prevalent fractures in women with polycystic ovary syndrome: a meta-analysis and endocrine-context pathophysiology review
Bibliographic record
Abstract
INTRODUCTION: Bone health in those with Polycystic Ovary Syndrome (PCOS) is complex, but the general consensus is that cortical areal bone mineral density (aBMD) sites will be higher in PCOS than in age- and BMI-similar controls. However, spine aBMD sites may be lower, especially in non-obese PCOS. Whether or not incident fracture risk is increased in PCOS is currently controversial; no meta-analysis has yet assessed prevalent fractures. AREAS COVERED: We assessed the bone effects of PCOS-related ovarian hormone alterations, e.g. androgen excess, tonically normal/higher estradiol, and lower-than-normal progesterone levels. We also highlighted evidence that common PCOS medications (e.g. combined hormonal contraceptives [CHC], metformin, and spironolactone) have important bone effects. In adolescents, meta-analysis of CHC showed significant negative aBMD changes. Inflammation has negative PCOS bone effects and is linked with CHC use. EXPERT OPINION: Is fracture risk altered by PCOS? Our meta-analysis showed a 25% increased risk of prevalent fracture in PCOS versus controls; this did not reach statistical significance. Future prospective research needs to collect and evaluate ovulation characteristics, progesterone exposure, and adolescent CHC use, in addition to the complex variables that may influence risks for prevalent or incident fragility fractures and/or for cortical and cancellous aBMD values in PCOS.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".