Bibliographic record
Abstract
Objective The purpose of this study is to retrospect the results of management of periprosthetic fracture around the hip treatment options.Methods 31 periprosthetic fractures were treated in our hospital from 1990.4 to 2008.12. 12 patients were male and 19 were female. The average age was 71 (60-81). Among them, 5 were type B1, 7 were type B2, 12 were type B3 and 7 were type C fracture according to Vancouver classification. Wire cerclage, clamp, strut of cortical allograft, shape memory alloy sleeve clamp, cable-plate, long stem revision and LISS plate based on the site of fracture, stablility of implant and quality of bone.Results The mean follow-up was 9.5 years. The fracture united healed in type B1 and type C without malalignment. One case of Type B1 fracture was treated with cable-plate initially, the fixation was failed 8 month later, the hardware was revised with LISS plate after 6 month uneventful in those 80 year woman. Another two failure cases, one B1case all implants were removed after several debridement because severe infection, one B3 fracture, LISS plate was used twice and failed finally, the next surgery was anticipated.Conclusions The methods applied for periprosthetic fractures depend upon the site of fracture, stability of implant and quality of bone. Treatment of periprosthetic fracture is still a hard work, prevention is the best manipulation for these fractures. The key of the management is to choose the appropriate therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".