Incidence and Risk Factors for Fracture-Related Infection After Peri-Prosthetic Femoral Fractures: A Multicenter Retrospective Study (TRON Group Study)
Bibliographic record
Abstract
Background: Fracture-related infection (FRI) sometimes occurs with peri-prosthetic femoral fracture (PPF) treatment. Fracture-related infection often leads to multiple re-operations, possible non-union, a decreased clinical function, and long-term antibiotic treatment. In this multicenter study, we aimed to clarify the incidence of FRI, the causative organisms of wound infection, and the risk factors associated with post-operative infection for PPF. Patients and Methods: Among 197 patients diagnosed with peri-prosthetic femoral fracture who received surgical treatment in 11 institutions (named the TRON group) from 2010 to 2019, 163 patients were included as subjects. Thirty-four patients were excluded because of insufficient follow-up (less than six months) or data loss. We extracted the following risk factors for FRI: gender, body mass index, smoking history, diabetes mellitus, chronic hepatitis, rheumatoid arthritis, dialysis, history of osteoporosis treatment, injury mechanism (high- or low-energy), Vancouver type, and operative information (waiting period for surgery, operation time, amount of blood loss, and surgical procedure). We conducted a logistic regression analysis to investigate the risk factors for FRI using these extracted items as explanatory variables and the presence or absence of FRI as the response variable. Results: Fracture-related infection occurred after surgery for PPF in 12 of 163 patients (7.3%). The most common causative organism was Staphylococcus aureus (n = 7). The univariable analysis showed differences for dialysis (p = 0.001), Vancouver type (p = 0.036), blood loss during surgery (p = 0.001), and operative time (p = 0.001). The multivariable logistic-regression analysis revealed that the patient background factor of dialysis (odds ratio [OR], 22.9; p = 0.0005), and the operative factor of Vancouver type A fracture (OR, 0.039–1.18; p = 0.018–0.19) were risk factors for FRI. Conclusions: The rate of post-operative wound infection in patients with a PPF was 7.3%. Staphylococcus was the most frequent causative organism. The surgeon should pay attention to infection after surgery for patients with Vancouver type A fractures and those undergoing dialysis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".