Risk factors for periprosthetic femoral fractures around total hip arthroplasty: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Periprosthetic fractures are becoming increasingly common, often leading to poor patient outcomes. The aim of this study was to identify risk factors associated with periprosthetic femoral fractures (PPFFx). METHODS: Two independent reviewers conducted a systematic review of the databases MEDLINE, Embase and Cochrane Library according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, from the earliest available date to December 2017. We included all clinical articles reporting more than 100 post-operative PPFFx around total hip arthroplasty (THA). Outcomes included demographics, fracture type, risk factors and time to fracture. RESULTS: A total of 12 868 PPFFx were reported across 18 eligible studies; 64% occurred following primary THA and 36% occurred after revision THA, and 66% of all fractures were in females. Vancouver B2 fractures were the most common type (39%). We found the odds of sustaining a PPFFx is significantly lower after a primary THA compared to revision THA (odds ratio 0.31, 95% confidence interval 0.24-0.40, P < 0.00001). The incidence of PPFFx is 2.96 per 1000 person-years following primary THA compared to 9.08 per 1000 person-years following revision THA (odds ratio 0.33, 95% confidence interval 0.27-0.40). The time to fracture was 6.03 years following primary THA and 4.08 years following revision THA. Gender and cementation did not significantly affect the odds of fracture. CONCLUSION: The odds of sustaining a PPFFx following revision THA is three times greater compared to primary THA. Other risk factors including gender and cementation did not affect the odds of fracture.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| 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".