A Scoping Review of Strategies for the Prevention of Hip Fracture in Elderly Nursing Home Residents
Bibliographic record
Abstract
BACKGROUND: Elderly nursing home residents are at increased risk of hip fracture; however, the efficacy of fracture prevention strategies in this population is unclear. OBJECTIVE: We performed a scoping review of randomized controlled trials of interventions tested in the long-term care (LTC) setting, examining hip fracture outcomes. METHODS: We searched for citations in 6 respective electronic searches, supplemented by hand searches. Two reviewers independently reviewed all citations and full-text papers; consensus was achieved on final inclusion. Data was abstracted in duplicate. FINDINGS: We reviewed 22,349 abstracts or citations and 949 full-text papers. Data from 20 trials were included: 7--vitamin D (n = 12,875 participants), 2--sunlight exposure (n = 522), 1--alendronate (n = 327), 1--fluoride (n = 460), 4--exercise or multimodal interventions (n = 8,165), and 5--hip protectors (n = 2,594). Vitamin D, particularly vitamin D(3) > or = 800 IU orally daily, reduced hip fracture risk. Hip protectors reduced hip fractures in included studies, although a recent large study not meeting inclusion criteria was negative. Fluoride and sunlight exposure did not significantly reduce hip fractures. Falls were reduced in three studies of exercise or multimodal interventions, with one study suggesting reduced hip fractures in a secondary analysis. A staff education and risk assessment strategy did not significantly reduce falls or hip fractures. In a study underpowered for fracture outcomes, alendronate did not significantly reduce hip fractures in LTC. CONCLUSIONS: The intervention with the strongest evidence for reduction of hip fractures in LTC is Vitamin D supplementation; more research on other interventions is needed.
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 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 | 0.025 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.021 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".