Clinical analysis of peri-prosthetic femoral fractures after total hip arthroplasty
Bibliographic record
Abstract
Objective To study the etiology and treatment of peri-prosthetic femur fracture(PFF) after total hip arthroplasty (THA). Methods Retrospective analyze 13 peri-prosthetic femur fracture patients treated in Sun Yat-sen Memorrial hospital since Jan. 2011 to Jan. 2017. The mean age was (68±19) years. Five were males and eight were females. The reasons for primary THA were femoral neck fractures (n=6), avascular necrosis of femoral head(n=5), ankylosing spondylitis(n=1) and rheumatoid arthritis(n=1). Five cemented and eight cementless prostheses were used in primary THA. The causes of PFF were trauma (n=7) and intraoperative fractures (n=6). According to Vancouver classification, there was one case type AG, one case type AL, four cases type B2, three cases type B3 and two cases type C. Great trochanter reattachment was used to fix the fraction in 5, cable plate was applied in seven cases and allograft cortical bone plate was used in one case. Among them, two cases of type C PFF were conducted fracture fixation. The rest prostheses of 11 patients’ were all unstable, one used cement fixation and 10 used extensively porous-coated implants. The function of the hip was assessed through Harris score and the healing of fracture was evaluated by X-ray and CT. Mann-Whitney test was used to compare Harris scores and VAS scores before and after operation. Results All the implants were stable at the last visit, with an average follow-up time of (29±189) months (range, 9 to 73 months). The average healing time of fracture were (4.5±1.1) months. Harris score improved from 13.0(4.0, 25.0)to 87.0(82.3, 93.3)(Z=-4.34, P<0.05). No sign of implant loosening, dislocation, deep infection or other complications occurred during follow-up. Conclusions For peri-prosthetic femur fracture patients with unstable fracture or prosthetic loosening, surgical treatment could restore intrinsic hip stability, provide excellent pain relief and improve the walking capacity. According to different types of fraction, different kinds of fixation are chosen. Using cable plate could restore the stability effectively. For the patients with bone loss, allograft of cortical bone plate would be useful to increase bone volume. Key words: Arthroplasty, replacement, hip; Periprosthetic fractures; Postoperative complications
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.003 | 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".