Effect of Enhanced Recovery After Surgery on the Prognosis of Patients With Hip Fractures: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Hip fractures, predominantly occurring in the elderly, are a significant public health concern due to associated morbidity, disability, and mortality. Prolonged bed rest following the fracture often leads to complications, further threatening patient health. Enhanced recovery after surgery, a modern approach to postoperative care, is being explored for its potential to improve outcomes and quality of life in hip fracture patients. OBJECTIVE: This study investigates the impact of enhanced recovery after surgery on hip fracture patients. METHODS: In this systematic review, we addressed the PICO question: Does the enhanced recovery after surgery program reduce 1-year mortality, readmissions, and postoperative pain and improve Harris Hip Score compared with traditional care in elderly hip fracture patients? We searched key databases and gray literature and analyzed outcomes through a meta-analysis using RevMan, Stata, and the Newcastle-Ottawa Scale for quality assessment. RESULTS: Nine studies involving 10,359 patients were included. Compared with the control group, the enhanced recovery after surgery group showed significant reduction in length of stay (mean difference [MD] = -2.00; 95% confidence interval [CI] [-2.87, -1.14]; p < .0001) and overall complication rate (risk ratio [RR] = 0.76; 95% CI [0.67, 0.85]; p < .0001), with a lower delirium rate (RR = 0.42; 95% CI [0.26, 0.68]; p = .004). No significant differences were observed in Harris Hip Score, pain score, 1-year mortality, readmission rate, or incidences of urinary tract infection, respiratory tract infection, and deep vein thrombosis. CONCLUSION: Enhanced recovery after surgery is associated with reduced length of stay, complication rate, and delirium rate in hip fracture patients.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.032 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".