Perioperative periprosthetic femur fracture associated with direct anterior total hip arthroplasty using metaphyseal fit and fill stem
Bibliographic record
Abstract
INTRODUCTION: This study aims to identify radiographic and clinical risk factors of perioperative periprosthetic femur fracture associated with the direct anterior approach (DAA) using a metaphyseal fit and fill stem. We hypothesize stem malalignment with this femoral implant places increased stress on the medial calcar region, which leads to an increased risk of periprosthetic fracture. METHODS: We compared patients with periprosthetic femur fractures following DAA total hip arthroplasty (THA) utilizing the Echo Bi-Metric Microplasty Stem (Zimmer Biomet, Warsaw, IN) to a cohort of patients who did not sustain a periprosthetic fracture from five orthopedic surgeons over four years. Postoperative radiographs were evaluated for stem alignment, neck cut level, Dorr classification, and the presence of radiographic pannus. Univariate and logistic regression analyses were performed. Demographic and categorical variables were also analyzed. RESULTS: Fourteen hips sustained femur fractures, including nine Vancouver B2 and five AG fractures. Valgus stem malalignment, proud stems, extended offset, and patients with enlarged radiographic pannus reached statistical significance for increased fracture risk. Low femoral neck cut showed a trend toward statistical significance. CONCLUSION: Patients undergoing DAA THA using a metaphyseal fit and fill stem may be at increased risk of perioperative periprosthetic fracture when the femoral stem sits proudly in valgus malalignment with extended offset and when an enlarged pannus is seen radiographically. This study identifies a specific pattern in the Vancouver B2 fracture cohort with regard to injury mechanism, time of injury, and fracture pattern, which may be attributed to coronal malalignment of the implant.
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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 | 0.000 |
| 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".