Characterization of Perimenopausal Bone Loss: A Prospective Study
Bibliographic record
Abstract
This study characterized the change in bone mass, bone markers, pituitary/gonadal hormones, vitamin D, parathyroid hormone, and anthropometric variables in a cohort of healthy women as they passed through normal menopause. We recruited 75 women > 46 years old who had premenopausal estradiol (E2) and gonadotropin levels and regular menses. During 9.5 years of observation, 54 experienced normal menopause (PM group) and 21 remained estrogen replete (ER group). Before the beginning of the menopausal drop and after its completion, the slope of bone mass on time in the PM group was 0% for the spine, -0.61% per year for the total body, and -0.45 % per year for the femoral neck. Designating these losses as "age related," there were 0, 4.88, and 3.40% losses for spine, total body bone mineral (TBBM), and femoral neck, respectively, in the 8-year period for which the data were analyzed. Across menopause, we found a sigmoid pattern of bone loss in the PM group beginning about 2-3 years before the last menses and ending about 3-4 years after the last menses. The total estrogen-deprivation bone losses were 10.50, 7.73, and 5.30% for the spine, TBBM, and femoral neck, respectively. In the ER group, we found a 0, 0.59, and 0.93% per year loss in spine, TBBM, and femoral neck, respectively. Serum osteocalcin rose 77%, serum total alkaline phosphatase rose 34%, and urinary hydroxyproline/creatinine (Hypro/Cr) ratio rose 44% in the PM group, while remaining stable in the ER group. We conclude that menopausal bone loss is a composite of loss caused by estrogen deprivation and age per se for the hip and total body, but is caused by estrogen deprivation alone for the spine.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".