Fracturas periprotésicas del fémur
Bibliographic record
Abstract
Background: Femoral fractures associated with total hip arthroplasty are uncommon. The incidence of postoperative fractures reported in the literature ranges from 0.1% in primary surgery to 4.2% after revision surgery. Their treatment, however, poses a significant challenge owing to numerous factors: e.g. patients are usually elderly, with poor bone quality. Methods: We present 59 patients operated in our hospital for periprosthetic fractures. The mean follow up was 7.3 years. Twenty of the cases were Vancouver Type A, 24 were type B, and 15 were type C. The fractures were treated as follows: revision arthroplasty, 24 cases; internal fixation, 33 cases; Girdlestone arthroplasty: 1 case; and conservative treatment, 1 case. Bone-graft was used in 21 cases. Results: After the treatment we had 7 complications: 3 non-unions, 2 infections, and 2 re-fractures. At the end of the follow up, results were as follows: 35 good or excellent, 17 fair, and 7 poor (Merle D'Aubigne score). The results were better in the cases treated with revision arthroplasty than with internal fixation. Conclusions: Good results were obtained in revision arthroplasty, and poor in the cases treated with internal fixation. The Vancouver classification is the best to select the right treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".