High tibial osteotomy in the ACL-deficient knee with medial compartment osteoarthritis
Bibliographic record
Abstract
High tibial osteotomy (HTO) has traditionally been used to treat varus gonarthrosis in younger, active patients. Varus malalignment increases the risk of progression of medial compartment osteoarthritis and an HTO can be performed to realign the mechanical axis of the lower limb towards the lateral compartment, thereby decreasing contact pressures in the medial compartment. Anterior cruciate ligament (ACL) insufficiency may lead to post-traumatic arthritis due to altered joint loading and associated injuries to the menisci and articular cartilage. Understanding the importance of posterior tibial slope and its role in sagittal knee stability has led to the development of biplane osteotomies designed to flatten the posterior tibial slope in the ACL deficient knee. Altering the alignment in both the sagittal and coronal planes helps improve stability as well as alter the load in the medial compartment. Detailed history, physical exam and radiographic analysis guide treatment decisions in this high demand patient population. Lateral closing wedge (LCW) and medial opening wedge (MOW) HTOs have been performed and their potential advantages and disadvantages have been well described. Given the triangular shape of the proximal tibia, it is imperative that the surgeon pay close attention to the geometry of the osteotomy "gap" when performing MOW HTO to avoid inadvertently increasing the posterior tibial slope. Simultaneous ACL reconstruction may require technique modifications depending on the type of HTO and ACL graft chosen. With appropriate patient selection and good surgical technique, it is reasonable to expect patients to return to activities of daily living and recreational sports without debilitating pain or instability.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".