Comparison of 2 Surgical Techniques of Posterolateral Corner Reconstruction of the Knee
Bibliographic record
Abstract
BACKGROUND: Various surgical techniques to treat posterolateral knee instability have been described. To date, the recommended treatment is an anatomical form of reconstruction, in which the 3 key structures of the posterolateral corner are addressed: the lateral collateral ligament, the popliteofibular ligament, and the popliteus tendon. HYPOTHESIS: Two methods of surgical reconstruction will restore posterolateral knee instability, in terms of static laxity as well as dynamic 6 degrees of freedom kinematics, to statistically significant levels compared with the intact state. STUDY DESIGN: Controlled laboratory study. METHODS: Two surgical techniques (A and B) were used to reconstruct the posterolateral structures in 10 cadaveric knees. Static tests were performed on the intact, sectioned, and reconstructed knees at 30 degrees and 90 degrees of flexion for anterior-posterior laxity and external rotational laxity, as well as at 0 degrees and 30 degrees of flexion for varus laxity; dynamic 6 degrees of freedom kinematic testing, through a path of motion from 90 degrees of flexion to full extension, was also performed. RESULTS: For the static varus tests, external rotation and varus laxity were significantly increased after the posterolateral structures were cut. Both reconstruction techniques restored external rotation and varus laxity to levels not significantly different from the intact state. For technique B, dynamic testing did not show any significant difference for all degrees of freedom kinematics compared with the intact state. However, for technique A, a significant internal tibial rotation was observed throughout the entire path of motion from 0 degrees to 90 degrees of knee flexion. CONCLUSIONS: Both surgical techniques for anatomical posterolateral corner reconstruction showed good results in the static laxity tests. The anatomical reconstruction of all structures, including the popliteus tendon, resulted in an abnormal internal tibial rotation during dynamic testing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".