Retrospective Population-Based Cohort Study of Incidence, Complications, and Survival of 202 Operatively Treated Periprosthetic Femoral Fractures
Bibliographic record
Abstract
Abstract Background The aim of this study is to investigate the population and primary total hip arthroplasty (THA)-based incidences, fracture types, complications, and survival of operatively treated periprosthetic femoral fracture (PFF). Methods This retrospective study reviewed 202 cases of operatively treated PFFs in a study period from January 2004 to December 2016. The Vancouver classification was used to classify PFFs. Results The incidence of PFF related to 1000 primary THAs per year was 2.7 (standard deviation 1.0, range 0.9-4.5) at a defined hospital district area during the study period. The mean population-based incidence of operatively treated PFFs raised from 1.6 to 4.5 per 100,000 person-years during the study period. The B1-type fracture was the most common fracture type in 71 of 202 (35%) of these PFFs. The cumulative incidence of re-revision was 10.9% at 1 year and 15.6% at 15 years (95% confidence interval [CI] 10.9-21.0). The cumulative incidence for other major complications was 6.4% at 1 year and 9.9% at 15 years (95% CI 5.9-15.0). The cumulative incidence of death after PFF was 7.4% at 1 year and 56.3% at 15 years (95% CI 41.3-68.8) during the follow-up time from January 1, 2004 to December 31, 2019. Conclusion This country-specific study showed a 3-fold increasing trend in the incidence of operatively treated PFFs from 2004 to 2016 per 1000 THAs. The Vancouver type B1 fracture was the most common type. A high number of complications were associated with PFFs and 7.4% of the patients had died within 1 year after PFF surgery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".