Hip fracture prevention strategies in long-term care
Bibliographic record
Abstract
OBJECTIVE To garner Canadian physicians’ opinions on strategies to reduce hip fractures in long-term care (LTC) facilities, focusing on secondary prevention. DESIGN A cross-sectional survey using a mailed, self-administered, written questionnaire. SETTING Canada. PARTICIPANTS Family physician members of the Ontario Long-Term Care Association (n = 165) and all actively practising geriatricians registered in the Canadian Medical Directory (n = 81). MAIN OUTCOME MEASURES The strength of recommendations for fracture-reduction strategies in LTC and barriers to implementing these strategies. RESULTS Of the 246 physicians sent the questionnaire, 25 declined study materials and were excluded. Of the 221 remaining, 120 responded for a response rate of 54%. About two-thirds of respondents were family physicians (78 of 120) and the rest were mostly geriatricians. Most respondents strongly recommended the following secondary prevention strategies for use in LTC after hip fracture: calcium, vitamin D, oral aminobisphosphonates, physical therapy, and environmental modification (such as handrails). Most respondents either did not recommend or recommended limited use of etidronate, intravenous bisphosphonates, calcitonin, raloxifene, testosterone (for hypogonadal men), and teriparatide. Postmenopausal hormone therapy was discouraged or not recommended by most respondents. Support was mixed for the use of hip protectors, B vitamins, and folate. Barriers to implementation identified by most respondents included a lack of strong evidence of hip fracture reduction (for B vitamins and folate, cyclic etidronate, and testosterone), side effects (for postmenopausal hormone therapy), poor compliance (for hip protectors), and expense (for intravenous bisphosphonates and teriparatide). Some respondents cited side effects or poor compliance as barriers to using calcium and potent oral bisphosphonates. CONCLUSION Canadian physicians favour the use of calcium, vitamin D, potent oral bisphosphonates, physical therapy, and evironmental modifications for LTC residents after hip fracture. Further study at the clinical and administrative levels is required to find ways to overcome the specific barriers to implementation and effectiveness of these interventions.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".