Technical tips and tricks for complex biplanar high tibial osteotomies
Bibliographic record
Abstract
PURPOSE: While traditional high tibial osteotomy (HTO) techniques primarily address malalignment in the coronal plane, the significance of sagittal plane alignment, particularly the posterior tibial slope (PTS), is not to be overlooked in the setting of cruciate ligament insufficiency. Combined deformities involving both the coronal plane and the sagittal plane are less common and present unique surgical challenges. This narrative review summarizes the literature and introduces tips and tricks for managing complex biplanar deformities through a case-based discussion of different techniques. METHODS: This narrative review includes preoperative planning, surgical techniques, clinical outcomes and illustrative clinical cases detailing surgical rationale and technical nuances in the correction of biplanar proximal tibial deformities. Emphasis is placed on the importance of accurate assessment and correction of biplanar deformities to optimize patient outcomes. Four representative technique presentations are included: (1) Hybrid HTO with a posterior opening wedge (POW) and anterior closing wedge (ACW), (2) asymmetrical medial closing wedge (MCW) HTO, (3) medial opening wedge (MOW) HTO with an anterolateral hinge and (4) a double HTO with both an infratuberosity ACW and high MOW. CONCLUSION: Biplanar HTO is a knee-preserving surgical option for a small cohort of patients with complex knee deformities involving both the coronal and sagittal planes. Precise preoperative planning and meticulous surgical execution are essential to address these biplanar malalignments effectively. This narrative review serves as a guide for orthopaedic surgeons, highlighting key considerations when planning biplanar HTO and serves as a practical guide for complex cases. LEVEL OF EVIDENCE: Level V.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".