Negative Spinal Bone Mineral Density Changes and Subclinical Ovulatory Disturbances—Prospective Data in Healthy Premenopausal Women With Regular Menstrual Cycles
Bibliographic record
Abstract
Subclinical ovulatory disturbances (anovulation or short luteal phases within normal-length menstrual cycles) indicate lower progesterone-to-estrogen levels. Given that progesterone plays a bone formation role, subclinical ovulatory disturbances may be associated with bone loss or less than expected bone gain. Our purpose was to perform a meta-analysis of prospective studies in healthy premenopausal women to determine the overall relationship of subclinical ovulatory disturbances to change in bone mineral density. Two reviewers independently identified from serial literature searches 6 studies meeting inclusion criteria: a 2-year study in 114 young adult women, 2006-2009, Vancouver, Canada; a 2-year study in 189 premenopausal women, 2000-2005, Toronto, Canada; a single-cycle study in 14 young women, 1996-1997, Melbourne, Australia; an 18-month study in 53 women, 1990-1995, Santa Clara, California; a 4-year study in 27 women, 1988-1995, Vancouver, Canada; and a 1-year study in 66 women, 1985-1988, Vancouver, Canada. This meta-analysis included a combined sample size of 473 observations in 436 premenopausal women studied over 1-4 years and aged 14-47 years. The percentage of women with ovulatory disturbances varied significantly from 13% to 82%. Women with more frequent ovulatory disturbances had more negative percentage changes in spine bone mineral density (weighted mean difference = -0.86; P = 0.040) for random-effects analysis. There was significant heterogeneity among these 6 studies (I(2) = 80%). In summary, these data show that regularly menstruating women with more frequent ovulatory disturbances experience more negative changes in bone (approximately -0.9% per year). These cycles with silent estrogen/progesterone imbalance may be clinically important.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".