Physiological versus standard sex steroid replacement in young women with premature ovarian failure: effects on bone mass acquisition and turnover
Bibliographic record
Abstract
BACKGROUND: The aim of this exploratory study was to establish whether we could improve skeletal health with a physiological regimen of SSR in young women with premature ovarian failure (POF). PATIENTS AND METHODS: In an open-label randomized controlled crossover trial, 34 women with POF were randomized to 4-week cycles of pSSR (transdermal oestradiol, 100 μg daily for week 1, 150 μg for weeks 2-4; vaginal progesterone, 200 mg twice daily for weeks 3-4) or standard hormone replacement treatment (sHRT) (oral ethinyloestradiol 30 μg and 1·5 mg norethisterone daily for weeks 1-3, week 4 'pill-free') for 12 months. Bone mineral density (BMD) was measured by DEXA at study entry and after each 12-month treatment period. Blood samples for hormones and markers of bone formation (bone alkaline phosphatase, BALP and type I collagen N-terminal propeptide, PINP) and bone resorption (CrossLaps) were collected pre-/postwashout and after 3, 6 and 12 months of each treatment. RESULTS: Eighteen women, mean 27 (range 19-39) years, completed the study. Both regimens caused similar suppression of LH and FSH. Mean baseline lumbar spine BMD z-score was -0·89 (95% CI -1·27 to -0·51) and increased by +0·17 (CI +0·07 to +0·27) in response to pSSR (P = 0·003), compared with +0·07 (CI -0·03 to +0·18) during standard HRT (P = 0·2). During pSSR, the increment in lumbar spine BMD z-score was related positively to oestradiol (r = +0·49, P = 0·04) and inversely to FSH (r = -0·65, P = 0·004). Bone formation markers, BALP and P1NP increased in the pSSR arm (anova P < 0·001) but decreased in the sHRT arm (P < 0·01). Both treatments suppressed the bone resorption marker, CrossLaps (P < 0·001). CONCLUSION: We conclude that pSSR over 12 months has a beneficial affect on bone mass acquisition on the lumbar spine in women with POF, mediated by increased bone formation and decreased bone resorption.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".