Alendronate Protects Premenopausal Women from Bone Loss and Fracture Associated with High-dose Glucocorticoid Therapy
Bibliographic record
Abstract
OBJECTIVE: We assessed the efficacy of bisphosphonate in premenopausal women (n = 47) commencing high-dose glucocorticoid (GC) therapy in protection against induced bone loss and bone fracture. METHODS. Subjects had just developed systemic autoimmune diseases and were randomized to be treated with 1 mg/kg/day prednisolone and alfacalcidol 1 microg/day alone (alfacalcidol group; n = 22), or prednisolone and alfacalcidol 1 microg/day with alendronate 5 mg/day (alendronate group; n = 25), each for 18 months. RESULTS: The percentage changes in lumbar spine bone mineral density (BMD) after 6 months of the therapy were -10.5% +/- 0.8% in the alfacalcidol group, but only -2.1% +/- 1.2% in the combined group. The rate of bone loss in the lumbar spine was significantly lower in the combined group than in the alfacalcidol group at 6 months. At 12 months of treatment, the percentage change in lumbar spine BMD was increased by 1.7% +/- 1.4% in the combined group, but decreased by 9.9% +/- 1.9% in the alfacalcidol group; the difference was significant. Bone fracture occurred at 12 months or later in 4 patients of the alfacalcidol groups, but not in the combined group, even at up to 18 months. CONCLUSION: Our results indicate that alendronate with alfacalcidol can maintain BMD and protects against high-dose GC-induced bone loss and bone fracture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".