Enhancement of Bone Mass in Osteoporotic Women with Parathyroid Hormone followed by Alendronate<sup>1</sup>
Bibliographic record
Abstract
Treatment of osteoporosis with PTH causes a marked increase in vertebral bone mineral density (BMD). However, this effect is rapidly reversed when the treatment is stopped. The purpose of the present study was to determine whether the bisphosphonate alendronate could preserve or enhance bone density in patients previously treated with PTH. Sixty-six postmenopausal osteoporotic women were treated for 1 yr with 50, 75, or 100 microg recombinant human PTH-(1-84) or placebo, and then were given 10 mg alendronate daily for an additional year. BMD was measured in the femoral neck, lumbar spine, and whole body. Markers of bone turnover included skeletal alkaline phosphatase, osteocalcin, and N-telopeptide. During the first year, changes in BMD (mean +/- SD) in women receiving PTH (all doses combined) were 7.1 +/- 5.6% (spine), 0.3 +/- 6.2% (femoral neck), and -2.3 +/- 3.3% (total body). After switching to alendronate for 1 yr in women who previously had received PTH, mean changes in BMD were 13.4 +/- 6.4% (spine), 4.4 +/- 7.2% (femoral neck), and 2.6 +/- 3.1% (whole body). In the subgroup of patients who had received the highest dose of PTH, the mean increase in vertebral BMD was 14.6 +/- 7.9%. All markers of bone turnover increased during treatment with PTH and decreased to below baseline after 1 yr of alendronate. In conclusion, sequential treatment of osteoporosis with PTH and alendronate results in an increase in vertebral bone density that is considerably more than has been reported with alendronate or estrogens alone. This combination of drugs may be a useful approach to maximizing bone density in women with vertebral osteoporosis.
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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) | 0.000 | 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".