Hormone replacement therapy improves distal radius bone structure by endocortical mineral deposition
Bibliographic record
Abstract
Hormone replacement therapy (HRT) produces a small increase in bone mineral density (BMD) when measured by dual energy X-ray absorptiometry (DXA). The corresponding decrease in fracture risk is more impressive, implying that other factors that contribute to bone strength are favourably modified by HRT. We investigated, using peripheral quantitated computed tomography (pQCT), the changes produced by HRT in both the distribution of mineral between cortical and trabecular bone and the changes produced by HRT in the apparent structure of trabecular bone, expressed as average hole area and apparent connectivity. Twenty-one postmenopausal women starting HRT and 32 control women were followed for 2 years, with distal radius pQCT measurements every 6 months. HRT prevented the loss of total bone mass seen in controls (p < 0.02). HRT also produced an apparent rapid loss of trabecular bone mass within the first 6 months of the study (p < 0.02), with an associated rapid loss in the apparent connectivity (p = 0.034). Average hole area also increased but not to a statistically significant extent. Exogenous estrogen apparently fills small marrow pores close to the endocortical surface, such that the pQCT-defined boundary between trabecular and cortical bone is shifted in favour of cortical bone. Trabecular bone structure indices are adversely affected, as the central, poorly interconnected trabecular bone with greater than average marrow spaces constitutes a greater fraction of the remaining trabecular bone. This study suggests that the improvements in fracture risk resulting from HRT are explained by a reversal of net endocortical resorption of bone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".