Radiographic osteoporotic vertebral fractures in elderly men: a brief review focusing on differences between the sexes
Bibliographic record
Abstract
Bone loss occurs in both sexes as a result of ageing but is exacerbated in women by the hormonal changes associated with menopause. Unlike in women, secondary osteoporosis occurs in almost half of men diagnosed with osteoporosis. Moreover, vertebral fractures (VFs) seen in elderly men may more likely be the result of high energy trauma. The osteoporotic vertebral fracture (OVF) radiograph diagnosis criteria for women may not be directly applicable for men. Particular attention should be paid to the mid-thoracic level where over-diagnosis commonly occurs. For wedge-shaped vertebral deformities (VDs) or VDs with anterior height reduction only, a diagnosis of OVF requires great caution, as they are poorly correlated to bone mineral density (BMD). For age-matched subjects, it is likely that elderly men's prevalent radiographic OVFs are approximately half of the elderly women's. This male-female ratio is very similar to other clinical fractures such as those occurring at the hip. Even so, the clinical relevance of OVF in elderly men may be less than that of elderly women. On the other hand, for elderly men with hip BMD-based osteoporosis, the OVF risk is as high as that of osteoporotic women. Elderly Chinese men have a lower OVF prevalence than age-matched Caucasian men.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".