Delayed mobilization following admission for hip fracture is associated with increased morbidity and length of hospital stay
Bibliographic record
Abstract
Background: Current national guidelines on caring for hip fractures recommend early mobilization. However, this recommendation does not account for time spent immobilized waiting for surgery. We sought to determine timing of mobilization following hip fracture, beginning at hospital admission, and evaluate its association with medical complications and length of hospital stay (LOS). Methods: We performed a retrospective review of prospectively collected data for 470 consecutive patients who underwent surgery for a hip fracture between September 2019 and August 2020 at an academic, tertiary-referral hospital. Outcomes of interest included time from hospital admission to mobilization, complication rate and LOS. We used a binary regression analysis to determine the effect of different surgical and patient factors on the risk of a postoperative medical complication. Results: The mean time from admission to mobilization was 2.8 ± 2.3 days (range 3 h–14 d). There were 125 (26.6%) patients who experienced at least 1 complication. The odds of developing a complication began to increase steadily once a patient waited more than 3 days from admission to mobilization (odds ratio 2.15, 95% confidence interval 1.42–3.25). Multivariate regression analysis showed that prefracture frailty (β = 0.276, p = 0.05), and timing from hospital admission to mobilization (β = 0.156, p < 0.001) and from surgery to mobilization (β = 1.195, p < 0.001) were associated with complications. The mean LOS was 12.2 ± 10.7 days (range 1–90 d). Prolonged wait to mobilization was associated with longer LOS (p = 0.01). Conclusion: Comprehensive guidelines on timing of mobilization following hip fracture should account for cumulative time spent immobilized.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".