Why is my Femoral Tunnel Shorter than I Thought - Comparing Expected and Actual Femoral Tunnel Lengths for ACL Repair in a Cadaveric Model
Bibliographic record
Abstract
Introduction Graft-tunnel mismatch is a unique surgical challenge in anterior cruciate ligament reconstruction (ACLR) with bone-patellar tendon-bone (BPTB). Graft tunnel mismatch has been reported in the literature at a rate between 13% and 26% of all BPTB ACLR cases, and miscalculation can lead to inadequate graft fixation, laxity, and failure. This study aims to explore the relationship between the expected and actual femoral tunnel depths to improve surgical accuracy. Methods Twelve cadaveric legs were procured. After open arthrotomy, femoral bone tunnels were drilled through an anteromedial, transtibial, and flexible approach using a 10 mm diameter drill bit with millimeter depth markings. Measurements of anterior, posterior, superior, and inferior aspects of the bone tunnel were measured using a screw depth gauge to the nearest 0.1 mm. The mean difference between the expected and actual tunnel depths was calculated for all aspects and analyzed using a two-sample t-test with a significance of p < 0.05. Results The anteromedial approach showed statistically significantly shorter actual compared to expected depths in the posterior, superior, and inferior aspects of the femoral tunnel. The flexible approach showed statistically significantly shorter actual femoral tunnel depths in the anterior, superior, and inferior aspects compared to the expected depth. The transtibial approach showed no statistically significant differences between actual and expected depths. Conclusion This study quantitatively demonstrated that femoral tunnels are statistically significantly shorter for anteromedial and flexible approaches compared to the desired depth. The transtibial approach demonstrated shorter than expected tunnels, but this was not statistically significant. Our results suggest that femoral tunnels drilled through a transtibial approach may be the most accurate.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".