The Commonest Indication for Performing a Slope‐Reducing Osteotomy With an Anterior Cruciate Ligament Reconstruction Is Graft Failure With a Posterior Tibial Slope of 12° or Greater: A Systematic Review of Indications, Techniques, and Outcomes
Bibliographic record
Abstract
PURPOSE: To (1) summarize indications/inclusion criteria and contraindications/exclusion criteria, operative techniques and details, and rehabilitation timelines for slope-reducing osteotomies with concomitant primary or revision anterior cruciate ligament (ACLR) and (2) summarize the radiographic and clinical outcomes that follow these types of surgeries. METHODS: Three databases (MEDLINE, PubMed, and EMBASE) were searched on December 22, 2024, for studies with patients undergoing ACLR with concomitant slope-reducing osteotomy. The authors adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Revised Assessment of Multiple Systematic Reviews guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. RESULTS: Six case series (Level IV) comprising 193 patients (27.5% female) with a mean age of 28.5 (range of means, 26.9-29.6) years were included. Four of 6 studies (66.7%) reported an indication for slope-reducing osteotomy, being a posterior tibial slope of 12° in revision or re-revision cases. Typical exclusion criteria for osteotomy reported by 5 studies included hyperextension of 5° to 10° or hypermobility (4 studies) and concomitant osteoarthritis (3 studies). Lysholm, Tegner, and visual analog scale scores all statistically increased postoperatively. Rates of return to sport at any level ranged from 81.3% to 100% and 25% to 100%, respectively. Graft failure rates in all studies ranged from 0% to 13%. Rates of recurvatum postoperatively ranged from 15% to 44%. Rates of hardware irritation/removal ranged from 0% to 46.2%. CONCLUSIONS: The most common indication for slope-reducing osteotomies with concurrent ACLR is in the revision setting in patients with a posterior tibial slope above 12°. Slope-reducing osteotomies with ACLR improve patient-reported outcome measures postoperatively and have low rates of instability and retear rates. Complications with osteotomy include postoperative recurvatum, postoperative hyperextension, and hardware removal. LEVEL OF EVIDENCE: Level IV, systematic review of Level IV studies.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".