Bibliographic record
Abstract
BACKGROUND: Although postmenopausal African-American women are at lower risk for osteoporosis-related fractures compared with white women, fractures in African-American women are associated with significantly higher morbidity and mortality. Therefore, early diagnosis and treatment of osteoporosis in this population is just as important as it is for other ethnic groups and worthy of the attention of physicians and healthcare organizations. OBJECTIVE: The purpose of this study was to evaluate risk factors for osteoporosis in postmenopausal African-American women. DESIGN: This was a retrospective, case-control study in 201 postmenopausal African-American women at a community-based osteoporosis center. Spine and hip bone mineral density measurements were obtained by dual-energy x-ray absorptiometry. Patient and family medical history, past and present pharmaceutical use, and dietary and exercise habits were collected using a patient self-administered questionnaire. RESULTS: Using the manufacturer's African-American referent database, 56 women had osteoporosis, 99 had osteopenia, and 46 had normal bone mineral density. Risk factors more common in the osteoporotic group compared with the normal group included sedentary lifestyle (P < 0.03), family history of osteoporosis (P < 0.03), low body mass index (P < 0.05), and history of bilateral oophorectomy (P < 0.03). Polyarthritis was more prevalent in the normal versus the osteoporotic group (P < 0.001). In addition, premenopausal use of oral contraceptives (P < 0.005) and postmenopausal use of estrogen therapy (P < 0.05) were more common in the normal compared with the osteoporotic group. CONCLUSIONS: Many risk factors for osteoporosis in African-American women are similar to those in white women and can aid in the selection of patients in need of bone density testing.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".