Bibliographic record
Abstract
PURPOSE OF REVIEW: To summarize the recently published studies that provide insights into the changing epidemiology of osteoporosis and fractures. RECENT FINDINGS: The main themes reviewed are fracture outcomes; trends in fractures rates; fracture risk assessment and monitoring; atypical femoral fractures; male osteoporosis; falls and physical activity; and sarcopenia, obesity, and metabolic syndrome. SUMMARY: Osteoporotic fractures were found to have long-term consequences on excess mortality (10 years) and economic costs (5 years). The large burden of nonhip nonvertebral fractures has been underestimated. Divergent (but mostly declining) trends in fracture rates were confirmed in several cohorts from around the world. This has significant implications for healthcare planners and clinicians responsible for the care of individuals with osteoporosis, and also impacts on the calibration of fracture prediction tools. Although fracture prediction tools differ in their complexity, performance characteristics are similar when applied to the general population. Large, high-quality comparative studies with different case mixes are needed. Fracture probability does not appear to be responsive enough to support goal-directed treatment at this time. A consensus on the diagnosis of osteoporosis in men has emerged, based upon the same absolute bone density cutoff for both men and women. Finally, a plethora of new data highlight the importance of falls, physical activity, and body composition as contributors to skeletal health.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.018 |
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".