PW 1932 Biomechanical determinants of hip fracture in older adults: evidence from video capture of falls in long-term care
Bibliographic record
Abstract
Over 95% of hip fractures in older adults are caused by falls. Understanding the circumstances of falls involving hip fracture should guide prevention efforts. This study examined falls captured on video in long-term care and compared the mechanics of falls that resulted in hip fracture to falls that did not. Between 2008 and 2017, we video-captured 1730 falls by 534 individuals. Hip fracture was documented in 34 falls (age=85±8 years, 65% female). We analysed each video with a structured questionnaire to determine the biomechanical characteristics of falls. Generalized Estimating Equation statistical models were used to calculate risk ratios (RRs) for hip fracture associated with each factor. All 34 falls involving hip fracture were from standing height and involved the pelvis striking the floor. Falls during walking or standing were more likely to result in hip fracture (RR=7.38; 95% CI: 2.27–24.02) than other activities. When comparing to other directions, hip fracture was more common in falls initially directed sideways (2.70; 1.39–5.21) and for sideways landing configurations (5.55; 2.61–11.78). Impact to the lateral aspect of pelvis created higher risk (3.34; 1.55–7.17) compared to an impact to the anterior or posterior pelvis. Among hip fracture cases, pelvis was among the first three sites of impact. Impact to pelvis occurred on the posterolateral aspect in 70% of cases, lateral in 18%, posterior in 6%, and anterolateral in 6%. Hip protectors were worn in 66% of cases that did not involve hip fracture and in 47% involving hip fracture, which showed a decreased risk for fractures (0.46; 0.23–0.95). In summary, the mechanics of falls involving hip fracture were different than non-fracture falls regarding fall height, fall direction, impact locations, and use of hip protectors. The high prevalence of impact to the posterolateral aspect of pelvis may be important to the design of wearable hip protectors.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".