V. Meta-Analysis of the Efficacy of Hormone Replacement Therapy in Treating and Preventing Osteoporosis in Postmenopausal Women
Bibliographic record
Abstract
OBJECTIVE: To review the effect of hormone replacement therapy (HRT) on bone density and fractures in postmenopausal women. DATA SOURCE: We searched MEDLINE and EMBASE from 1966 to 1999, the Cochrane Controlled Register, citations of relevant articles, and proceedings of international meetings for eligible randomized controlled trials. We contacted osteoporosis investigators to identify additional studies, and primary authors for unpublished data. STUDY SELECTION: We included 57 studies that randomized postmenopausal women to HRT or a control (placebo or calcium/vitamin D) and were of at least 1 yr in duration. Seven of these studies reported fractures. DATA ABSTRACTION: For each study, three independent reviewers assessed the methodological quality and abstracted the data. DATA SYNTHESIS: HRT showed a trend toward reduced incidence of vertebral fractures [relative risk (RR) 0.66, 95% confidence interval (CI) 0.41-1.07; 5 trials] and nonvertebral fractures (RR 0.87, 95% CI 0.71-1.08; 6 trials). HRT had a consistent effect on bone mineral density (BMD) at all sites. The difference between HRT and control in the percent change in bone density at 2 yr was 6.76 (5.83, 7.89; 21 trials) at the lumbar spine and 4.53 (3.68, 5.36; 14 trials) and 4.12 (3.45, 4.80; 9 trials) at the forearm and femoral neck, respectively. CONCLUSIONS: HRT has a consistent, favorable and large effect on bone density at all sites. The data show a nonsignificant trend toward a reduced incidence in vertebral and nonvertebral fractures.
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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 | 0.022 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.041 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".