Patients With Failed Anterior Cruciate Ligament Reconstruction Have an Increased Posterior Lateral Tibial Plateau Slope: A Case-Controlled Study
Bibliographic record
Abstract
PURPOSE: To compare knee anatomical parameters of patients with failed anterior cruciate ligament reconstruction (ACL-R) with those of a control group of sex-matched patients with successful ACL-R. METHODS: Forty-three patients (34 male, 9 female) who experienced graft failure after ACL-R were enrolled in the failed group. These patients were matched to a control group of 43 patients who underwent primary ACL-R with a minimum follow-up of 24 months. On magnetic resonance imaging, the following parameters were evaluated: transepicondylar distance, lateral and medial femoral condyle widths, tibial plateau width, notch width index, and the ratio of width and height of the femoral notch, ratio between the height and depth of the lateral and medial femoral condyle, lateral and medial posterior tibial slopes, and anterior subluxation of the lateral and medial tibial plateau. Multivariate regression with backward elimination, including only the previously identified significant variables, defined the independent predictors for revision surgery. RESULTS: The anatomical variables that were significantly different between the 2 study groups were lateral and medial posterior tibial slopes, anterior subluxation of the lateral and medial tibial plateau, medial tibial plateau width, lateral tibial plateau width, medial femoral condyle width, and transepicondylar distance; however, the multivariate regression analysis identified the lateral posterior tibial slope (LTPs), the anterior subluxation of the medial tibial plateau, and the medial femoral condyle width as significant independent predictors (P < .05). The LPTs had the highest coefficient and the highest sensitivity (88%) and specificity (84%) to identify failures when considering the optimal cutoff value of 7.4°. CONCLUSIONS: Several anatomical parameters have been identified that differ significantly between patients with failed ACL-R and those without a documented failure. The most accurate predictor of ACL failure was an LTPs >7.4°, with a sensitivity of 88% and specificity of 84%. Surgeons should consider measuring LTPs during preoperative assessment of ACL-injured patients, and patients with values >7.4° should be considered at high risk of ACL-R failure. LEVEL OF EVIDENCE: Level III retrospective prognostic trial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".