Early Complications of a Novel Retrograde Intramedullary Femoral Nail in the Treatment of Femur Fractures
Bibliographic record
Abstract
OBJECTIVES: To determine the early implant failure rate of a novel retrograde intramedullary femoral nail. DESIGN: Retrospective cohort study. SETTING: Academic level 1 trauma center. PATIENTS SELECTION CRITERIA: Patients aged 18 years and older with an acute OTA/AO 32-A, 32-B, 32-C, and 33-A fractures or periprosthetic distal femur fracture from April 2018 to April 2022 were included in the study. The 2 interventions compared were the Synthes Expert retrograde/antegrade femoral nail (or control implant) versus the next-generation retrograde femoral nail (RFN)-advanced retrograde femoral nail (RFNA or experimental implant) (Synthes, West Chester, PA). OUTCOME MEASURES AND COMPARISONS: Early implant-related complications between the experimental and control implants were assessed including locking screw back out, screw breakage, intramedullary nail failure, need for secondary surgery, and loss of fracture reduction. RESULTS: Three hundred fourteen patients were identified with a mean age of 31.0 years, and 62.4% of the patients being male. Open fractures occurred in 32.5% of patients with 3.8% of injuries being distal femur periprosthetic fractures. Fifty-six patients were in the experimental group and 258 patients in the control group. Mean follow-up was 46.8 weeks for the control cohort and 21.0 weeks for the experimental cohort. Distal interlocking screw back out occurred in 23.2% (13 of 56) of the experimental group patients and 1.9% (5 of 258) of the control group patients ( P < 0.0001). Initial diagnosis of interlocking screw back out occurred at an average of 3.2 weeks postoperatively (range, 2-12 weeks). Fifty-four percent of patients who sustained screw back out underwent a secondary operation to remove the symptomatic screws (12.5% of all patients treated with the experimental implant required an unplanned secondary operation due to screw back out). A logistic regression model was used to predict screw back out and found the experimental implant group was 4.3 times as likely to experience distal locking screw back out compared with the control group ( P = 0.01). CONCLUSIONS: The retrograde femoral nail-advanced implant was associated with a significantly higher rate of screw back out with a substantial number of unplanned secondary surgeries compared with the previous generation of this implant. LEVEL OF EVIDENCE: Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".