Treatment of periprosthetic femoral fractures after total hip arthroplasty
Bibliographic record
Abstract
Objective To discuss the causes and treatment methods for periprosthetic femoral fractures following total hip arthroplasty.Methods Totally 16 cases of femoral periprosthetic fracture after hip replacement were subjected to a retrospective study from 2002 to 2008,Fractures occurred 3 months to 7 years after hip replacement.According to the classification for periprosthetic fracture of Vancouver,there were 2 cases of type A,6 cases of type B1,3 cases of type B2,3 cases of type B3 and 2 cases of type C.Three cases were treated by non-operative methods,8 cases by shape memory alloy embracing fixator,and 1 case(type B2)by long-shaft prosthesis revision at the same time.One case was fixed with shape memory alloy embracing fixator or the cable plate supplemented with cortical allograft and 1 case only with the cable plate.Fracture healing was evaluated by X ray films,and joint function by Harris Score.Results Fifteen cases were followed up for 1-4 years and 1 case died of pulmonary embolism.Hip joint range of motion was 100° by flexion one year after surgery.All fractures were proved to be healed with no complications such as infection,nonunion or fixator breakage by X-ray evaluation.Harris Score increased significantly(from 35 pre-operatively to more than 70 post-operatively).Conclusion According to different Vancouver types of periprosthetic femoral fractures,we should select different operation methods.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".