Low bone mineral density and fracture burden in postmenopausal women
Bibliographic record
Abstract
BACKGROUND: The study objectives were to determine fracture rates in relation to bone mineral density at various central skeletal sites, using the World Health Organization definition for osteoporosis (T-score -2.5 or less), and to contrast fracture patterns among women 50 to 64 years of age with those among women 65 years of age and older. METHODS: Historical cohort study with a mean observation period of 3.2 (standard deviation [SD] 1.5) years. The study group (16,505 women 50 years of age or older) was drawn from the Manitoba Bone Density Program database, which includes all bone mineral density results for Manitoba. Baseline density measurements for the lumbar spine and hip were performed with dual-energy x-ray absorptiometry. Outcomes included the percentage of osteoporotic fractures and the rates of fracture and excess fracture (per 1000 person-years) among postmenopausal women with osteopenia and osteoporosis relative to those with normal bone mineral density (according to the classification of the World Health Organization). RESULTS: The mean age was 65 (SD 9) years, and the mean T-scores for all sites fell within the osteopenic category. There were 765 incident fractures (fracture rate 14.5 [95% confidence interval, CI, 13.5-15.6 [per 1000 person-years). Fracture rates were significantly higher among women 65 years of age or older than among women 50-64 years of age (21.6 [95% CI 19.7-23.4] v. 8.6 [95% CI 7.5-9.7] per 1000 person-years, p < 0.001). Although fracture rates were significantly higher among women with osteoporotic T-scores, most fractures occurred in women with nonosteoporotic values (min-max: 59.7%-67.8%). INTERPRETATION: In this study, most of the postmenopausal women with osteoporotic fractures had nonosteoporotic bone mineral density values. This finding highlights the importance of considering key clinical risk factors that operate independently of bone mineral density (such as age) when assessing fracture risk.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| 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 | 0.002 |
| 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 teacher head, 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".