RESULTS OF TREATMENT OF PERIPROSTHETIC FEMORAL FRACTURES AFTER TOTAL HIP ARTHROPLASTY
Bibliographic record
Abstract
Periprosthetic fractures are the third most common reason for revision total hip arthroplasty. Surgical treatment of periprosthetic fractures belongs to the most difficult procedures due to the extensive surgery, elderly polymorbid patients and the high frequency of other complications. The aim of this study was to evaluate the results of operatively treated periprosthetic femoral fractures after total hip arthroplasty. We evaluated 47 periprosthetic fractures in 40 patients (18 men and 22 women) operated on between January 2004 and December 2010. The mean follow-up period was 27 months (within a range of 12-45 months). For the clinical evaluation, we used modified Merle d'Aubigné scoring system. In group of Vancouver A fractures, 3 patients were treated with a mean score of 15.7 points (good result). We recorded a mean score of 14.2 points (fair result) in 6 patients with Vancouver B1 fractures, 12.4 points (fair result) in 24 patients with Vancouver B2 fractures and 12.7 points (fair result) in 7 patients with Vancouver B3 fractures. In group of Vancouver C fractures, we found a mean score of 16.2 points (good result) in 7 patients. Therapeutic algorithm based on the Vancouver classification system is, in our opinion, satisfactory. Accurate differentiation of B1 and B2 type of fractures is essential. Preoperative radiographic images may not be reliable. If in doubt, checking the stability of the prosthesis fixation during surgery should be performed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".