THE USE OF THE INVERTED FEMORAL LISS PLATE AS A METHOD FIXATION OF PERI-PROSTHETIC HIP FRACTURES
Bibliographic record
Abstract
Vancouver B type peri-prosthetic hip fractures are increasingly common and represent a very complex and challenging problem in terms of management. Plate fixation has not always succeeded, and revision hip arthroplasty on a suboptimal trauma list can be a daunting prospect. Our technique is to use the opposite sided distal femoral LISS plate, inserted from proximally to distally in an inverted manner. Vastus lateralis is elevated off the trochanteric ridge, and a small amount of bone is removed from the ridge to get the plate to sit snugly. The fracture is opened only enough to achieve reduction, and fixation with locking screws are placed percutaneously distal to the fracture. Bone grafting or cable fixation can also be applied at the fracture site. 20 consecutive patients with Vancouver B peri-prosthetic hip fractures were reviewed. The average patient age was 78 yrs. 14 fractures occurred in cemented and 6 in uncemented femoral stems. 12 fractures occurred in primary THR and 8 in bipolar hip hemiarthroplasty. Six were managed using the inverted LISS plate, 6 using other methods of fixation, and 8 with revision THR. In terms of mortality at 12 months, there was no difference between the treatment arms, with 1 death in the LISS and other fixation group respectively and 0 deaths in the revision THR group. From a morbidity perspective there was no difference with respect to post-op medical complications, weight bearing status and length of hospital stay. There was, however, a difference between the inverted LISS plate group and other fixation methods group compared with the revision THR group in terms of average transfusion requirement (2 units and 3 units vs 8 units) and average operative time (80 mins and 100 mins vs 465 mins). 1 LISS plate failed in the 12 month period, with 1 Revision THR and 2 from the other fixation group. This study suggests that it is a stable method of fixation, particularly in the type B1 and B2 subtypes. It may also be used in patients with multiple co-morbidities who cannot undergo a revision procedure and in patients who are minimally/non ambulant. In one patient, we used it to stabilize the fracture before progressing to a later, more controlled, revision hip replacement situation. LISS fixation has a short operative time, low transfusion requirement, low failure rate and is technically easier to perform than revision surgery.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".