Vancouver types B and C periprosthetic femur fractures and proximal femur fracture with hip joint diseases: Treatment strategies
Bibliographic record
Abstract
Objective There are quite a few similarities in the therapeutic strategies and problems to be solved for patients with Vancouver types B and C periprosthetic femur fractures or proximal femur fracture with hip joint diseases,such as femoral head necrosis,hip osteoarthritis,or femoral neck fracture,that necessitate hip replacement.This study aimed to investigate the treatment of these patients.Methods We included in this study 8 cases of periprosthetic femur fracture and 5 cases of proximal femur fracture with hip joint diseases that required total hip replacement.They were 7 males and 6 females,aged 48-78(mean 61.5) years.The patients were treated by total hip replacement and fracture fixation.Results All the 13 cases were healed clinically,and their hip function improved significantly.Conclusion Satisfactory results can be achieved in the treatment of Vancouver types B and C periprosthetic femur fractures or proximal femur fracture with hip joint diseases requiring hip replacement if adequate consideration is given to the fracture type,fracture site,local bone quality and whether the prosthesis is loose or not.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".