Current status of patients with hip fracture in Japan: A nationwide survey
Bibliographic record
Abstract
BACKGROUND: Although surgical treatment is the standard of care for most hip fractures, the post-fracture management of osteoporosis remains challenging. This study aimed to elucidate the status of osteoporosis treatment, subsequent fracture rates, mortality rates, and changes in residential status and care levels among hip fracture patients in Japan, and to explore strategies for fracture prevention and extension of healthy life expectancy. METHODS: This study included patients with hip fractures treated at approximately 3000 orthopaedic facilities nationwide during July 2020. Data was collected via web-based surveys at the time of injury and 6 and 12 months post-injury. RESULTS: A total of 6705 patients were registered from 1309 facilities (mean age: 82.9 ± 0.7 years; 86.4 % were female). The surgery rate was 94.8 %, with 62.1 % undergoing osteosynthesis and 37.9 % receiving hemiarthroplasty or total hip arthroplasty. Osteoporosis treatment rates gradually increased from 23.0 % at the time of injury to 44.8 % at 6 months and 47.3 % at 12 months, although the rates remained suboptimal. Active vitamin D3-based medications were the most commonly used medications, accounting for approximately 60 % of cases. The cumulative 12-month mortality rate was 10.0 %, and the incidence of new fractures was 11.0 %. The main fracture sites were the contralateral proximal femur, vertebral, and proximal humerus. The most common reason for non-treatment was "patient's decision." Among patients who were not enrolled in long-term care insurance at the time of injury, 66.1 % had newly obtained care level certification by 12 months after injury. The proportion of patients who returned home among those living at home at the time of injury was 80.7 % at 6 months and 96.8 % at 12 months, respectively. CONCLUSIONS: Osteoporosis treatment rates after hip fractures remain low, indicating the need for more proactive intervention, including secondary fracture prevention. This study also highlights the importance of early rehabilitation and continuous support.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".