Bibliographic record
Abstract
Objective To analyze the causes and results of treatment of periprosthetic femoral frac-tures after total hip arthroplasty and to explore the best operative methods for fractures. Methods 11 cases treated for periprosthetic femoral fracture after total hip arthroplasty were subjected to a retrospective fol-low-up study from December 1998 to March 2003. There were 8 men and 3 women, the mean age was 56 years (range, 43 to 75 years). There were 2 Vancouver A type fractures, 7 B2 type, 1 B3 type, 1 C type. 5 fractures were treated by nonoperative methods and other 6 by operative methods, including one fracture malunion treated initially by skin traction. There were 5 revisions using long stem supplemented with cortical allograft strut, including 4 uncemented stems with distal fixation and one cemented stem; the remaining one fracture treated by open reduction and internal fixation. Results None was lost for follow-up. The mean follow-up period was 25.6 months (range, 7 to 50 months). 9 fractures united at a mean of 4 months (range, 3 to 6 months). Nonunion was found in 2 fractures, both were treated nonoperatively. All the 6 fractures treated by operative methods united. Up to now, 7 stems were well-fixed, continuous radiolucent line was seen in one revision case, 3 stems were loosened. The function of the patients with well-fixed stems was bet-ter than those with loosened stems, the mean Harris score of the former was 91. All the cortical allograft struts were incorporated with host bone within one year. No strut fracture happened. Conclusion Type A fractures with well-fixed stems can be treated by nonoperative methods, while type B1 and type C fractures should be treated by open reduction and internal fixation, on condition there is no surgical contraindication. For fractures with loosened stems, use of an uncemented long stem with distal fixation supplemented with cortical allograft strut is the best choice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".