[Surgical treatment of periprosthetic femur fracture after hip arthroplasty].
Bibliographic record
Abstract
OBJECTIVE: To investigate the surgical treatment results of periprosthetic femur fracture after hip arthroplasty. METHODS: In the study, 10 patients from Oct. 2006 to Jan. 2012 were treated surgically according to Vancouver classification, and their fracture union, hip function, pain in fracture site and lower extremity length were evaluated postoperatively. RESULTS: All the patients had full follow-up for 6 to 69 months (mean time: 35.1 months). All fractures were united well with good alignment and no prosthesis loosing or internal fixation failure was discovered. Harris scores to assess hip function were 71 to 90 (mean: 79.8) and the excellent and good rate was 70%. VAS scores to evaluate pain in fracture site when walking were 0 to 3 (mean: 1.4). The lengths of injured lower extremity were shorter by 0 to 2.5 cm than those of the contralateral side preoperatively [mean (1.6±0.9) cm]. The shortened lengths were reduced to 0 to 1.8 cm postoperatively [mean (0.6±0.6) cm], which were statistically different from those of preoperation (P=0.002). CONCLUSION: Although treatment of periprosthetic femur fracture after hip arthroplasty is a hard work, we can make individual therapy regiment based on the patient's age, general condition, function demand and Vancouver classification. Surgical treatment can bring good results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".