Bibliographic record
Abstract
Objective To describe the postfracture osteoporosis management of at-risk patients presenting with low-trauma fracture in a suburban community hospital setting. Design Telephone survey. Setting Hospital emergency department serving a retirement community in White Rock and South Surrey, BC. Participants Men and women older than 40 years of age who presented with low-trauma fracture between October 1, 2004, and April 30, 2005. Main outcome measures The prevalence of bone mineral density testing, osteoporosis medication prescriptions, referrals to fall prevention programs, and calcium and vitamin D supplementation within 6 months of the index fracture, as well as patient perceptions of future risk of fracture and sources of osteoporosis information. Results A total of 181 people met the eligibility criteria and 161 were contacted; 84 (52%) people responded, of whom 53 were interviewed. At the time of their index fractures, 79% (42 of 53) of patients surveyed were not taking osteoporosis medication. After the index fracture, 30% (16 of 53) received new bone mineral density testing, and 8% (4 of 53) were starting courses of new osteoporosis medication. Sixty-eight percent (36 of 53) of all patients were taking calcium supplements and 50% (26 of 53) were taking vitamin D supplements. Eight percent (4 of 53) of patients were referred to a fall prevention program and 9% (5 of 53) were prescribed hip protectors; 19% (10 of 53) of patients thought they were at risk of having another fracture. Conclusion Osteoporosis management of patients after low-trauma fracture in this community was suboptimal; the role of the media, family and friends, and allied health professionals to prevent fractures in at-risk individuals needs to be further explored.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.312 | 0.124 |
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".