The effect of strength training combined with bisphosphonate (etidronate) therapy on bone mineral, lean tissue, and fat mass in postmenopausal women
Bibliographic record
Abstract
The combined and separate effects of exercise training and bisphosphonate (etidronate) therapy on bone mineral in postmenopausal women were compared. Forty-eight postmenopausal women were randomly assigned (double blind) to groups that took intermittent cyclical etidronate; performed strength training (3 d/week) and received matched placebo; combined strength training with etidronate; or took placebo and served as nonexercising controls. Bone mineral, lean tissue, and fat mass were assessed by dual-energy X-ray absorptiometry before and after 12 months of intervention. After removal of outlier results, changes in bone mineral density (BMD) of the lumbar spine and bone mineral content (BMC) of the whole body were greater in the subjects given etidronate (+2.5 and +1.4%, respectively) compared with placebo (-0.32 and 0%, respectively) (p < 0.05), while exercise had no effect. There was no effect of etidronate or exercise on the proximal femur and there was no interaction between exercise and etidronate at any bone site. Exercise training resulted in significantly greater increases in muscular strength and lean tissue mass and greater loss of fat mass compared with controls. We conclude that etidronate significantly increases lumbar spine BMD and whole-body BMC and that strength training has no additional effect. Strength training favourably affects body composition and muscular strength, which may be important for prevention of falls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".