Efficacy and Safety of Human Parathyroid Hormone-(1–84) in Increasing Bone Mineral Density in Postmenopausal Osteoporosis
Bibliographic record
Abstract
Daily sc injections of N-terminal analogs of PTH increase bone mass and decrease fractures in osteoporotic women. We investigated the efficacy and safety of human PTH-(1-84) (full-length PTH) in the treatment of postmenopausal osteoporosis in a double-blind, placebo-controlled study. The women (n = 50-53/group) self-administered PTH (50, 75, or 100 microg) or placebo by daily sc injection for 12 months. PTH treatment induced time- and dose-related increases in lumbar spine bone mineral density (BMD). The 100-microg dose increased BMD significantly at 3 months (+2.0%) and 12 months (+7.8%). BMD underestimated the anabolic effect of PTH in lumbar spine (bone mineral content, +10.0%) because bone area increased significantly (+2.0%). A nonsignificant decrease (-0.9%) in total hip BMD occurred during the first 6 months with the 100-microg dose, but this trend reversed (+1.6%) during the second 6 months. Bone turnover markers increased during the first half of the study and were maintained at elevated levels during the second 6 months. Protocol compliance was excellent (95-98%), and treatment was generally safe and well tolerated. Dose-related incidences of transient hypercalcemia occurred, but only one patient (100-microg group) was withdrawn because of repeated hypercalcemia. Thus, full-length PTH was efficacious and safe over 12 months.
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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 | 0.000 |
| 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) | 0.001 | 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".