Early Definitive Fixation of an Open Periprosthetic Femur Fracture in the Polytraumatized Patient: A Case Report and Review of the Literature.
Bibliographic record
Abstract
INTRODUCTION: Periprosthetic fractures of the femur after total hip arthroplasty are increasing in frequency. In the polytraumatized patient with long-bone fracture, an ongoing debate exists regarding early definitive stabilization versus initial damage control orthopaedics, followed by delayed fixation. It remains to be seen whether this rationale applies to the polytraumatized patient with periprosthetic fracture. CASE PRESENTATION: We present the case of a 73-years old Caucasian woman who sustained bilateral Gustillo-Anderson grade III open femur fractures; the fracture on the right was a Vancouver C open periprosthetic fracture after cemented total hip arthroplasty. After massive fluid resuscitation in the trauma bay she was taken to the intensive care unit in a hemodynamically unstable condition. She was subsequently operated and underwent early definitive fixation of both femurs with the rationale of potentially reducing pulmonary complications and promoting early mobilization. CONCLUSION: Early definitive stabilization versus delayed fixation in the polytraumatized patient with an open periprosthetic femur fracture is reviewed. Although several treatment algorithms based on fracture classification and implant stability exist, further study is required to delineate the preferred method and timeline of fixation for this growing cohort of patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".