The Influence of Sagittal Proximal Tibial Anatomy in Tibial Intramedullary Nailing
Bibliographic record
Abstract
OBJECTIVES: To quantify anatomic variation in sagittal proximal tibial anatomy and determine if anatomy or nail insertion method influences the radiographic nail position. DESIGN: Retrospective cohort of prospectively collected data. SETTING: Level 1 trauma center. PATIENTS/PARTICIPANTS: Forty-five patients with 46 tibia fractures (OTA/AO 41A, 42, and 43) treated with infrapatellar (IP) or suprapatellar (SP) nailing. The average patient age was 40.6 years (range 19-62 years). INTERVENTION: Patients received IP or SP nailing. Cohorts were analyzed based on the nailing technique and proximal tibial anatomy. MAIN OUTCOME MEASUREMENTS: Proximal tibial radiographic anatomy was quantified using novel measurements [anterior tubercle angle (ATA) and entry point position (EPP)]. Nail entry point, entry point displacement after reaming, nail position, and quality of reduction was measured and compared between groups. RESULTS: ATA was highly variable between patients. ATA was strongly correlated with EPP with a higher ATA associated with EPP more colinear with the intramedullary canal. Patients with low ATA treated with IP nailing had significantly longer operative times (60.0 vs. 45.7 minutes). Low ATA tibias had a higher incidence of entry point displacement due to eccentric reaming compared with high ATA tibias (70% vs. 38%) with the highest incidence of entry point displacement and absolute displacement in low ATA tibias treated with IP nailing (86%, 2.8 mm). SP nailing demonstrated shorter operative times relative to IP nailing (45.5 vs. 55.6 minutes). CONCLUSIONS: There is considerable variability in proximal tibial anatomy and these features influences the nail position within the tibia. These differences in anatomy should be considered to potentially reduce operative times, entry point displacement and anteriorization of tibial nails. LEVEL OF EVIDENCE: Prognostic 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".