Bibliographic record
Abstract
Purpose: To determine the treatment results according to the guideline of the Vancouver classification in peri prosthetic femoral fractures. Materials and Methods: Thirty-five peri prosthetic femoral fractures treated between May 1981 and February 2003 were assessed. The mean age of the patients was 56 years (30-83 years). The outcomes were estimated according to the Reals and Tower's criteria. Results: The overall incidence of postoperative peri prosthetic femoral fracture was 0.91%. The frequency of the fracture types in decreasing order was B1, B2, B3, C, AG and AL. The treatment outcomes according to the Vancouver guidelines were excellent in 27 hips, good in 5 hips and poor in 3 hips. Suspicious risk factors of periprosthetic fractures were found in 6 hips (osteoporosis in 4 hips, osteolysis in 1 hip and loosening of femoral stem in 1 hip). Complications related to the treatment included a bony defect in 1 hip and an infection with non-union in 1 hip. The complications related to treatment for an implant were loosening in 2 hips and subsidence of stem in 1 hip. Conclusion: In order to obtain favorable results, in addition to following the Vancouver treatment guideline, consideration should be made to the basic principles such as the stability of the fractures, the stability of the implant and restoration of the bone stock.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".