Use of the Locking Attachment Plate for Internal Fixation of Periprosthetic Femur Fractures
Bibliographic record
Abstract
Introduction The locking attachment plate (LAP) can be added to a locking compression plate (LCP) to allow the fixation of locking screws bicortically around a femoral implant. We aimed to examine surgical and fracture characteristics associated with healing for periprosthetic femur fractures (PPFFx) treated with constructs employing LAP fixation. We hypothesize that the addition of an LAP provides stable peri-implant fixation. Materials &Methods We retrospectively reviewed a consecutive series of 28 PPFFx surgically treated with LCP-LAP constructs by 4 surgeons from 2015-2020. Fractures were classified and grouped using the Vancouver Classification System and included 12 B1, 2 B2, 11 C fractures, and 3 fractures around other stemmed implants. Primary outcome measures included hardware failure such as screw pullout, broken screws, and plate fracture. Clinical complications including infection, non-union, malunion, and reoperation were recorded. Results No LAP failures, screw pullout, or broken screws were observed. Two fractured plates (7.1%) occurred in patients with Vancouver C fracture types. Overall complication rate was 17.9% and included 3 non-unions, 1 deep infection, and 1 implant loosening with painful hardware, each requiring reoperation. Differences were observed between unions and nonunions for total number of screws (12.4 vs 14.7, P = .005) and number of locking screws used (8.04 vs 11.3, P = .03). Conclusion The LAP provides adequate fixation and low failure rates where fixation is required around a well-fixed stem. When failures occur, it is from plate breakage and not due to failure of fixation at the area of plate-stem overlap.
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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 | 0.001 | 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 | 0.000 | 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) | 0.002 | 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".