PREDICTORS OF RADIOLOGICAL OSTEOARTHRITIS AT FIVE YEARS AFTER ANTERIOR CRUCIATE LIGAMENT RECONSTRUCTION
Bibliographic record
Abstract
To evaluate the predictive factors of post-traumatic knee osteoarthritis (OA) in the medial, lateral, and patellofemoral compartments at 5-years post-ACL reconstruction, within a large randomized clinical trial. Three-hundred-and-thirty patients (110 patients/group), ages 14–50 years, were randomized intra-operatively to ACL reconstruction with either a patellar tendon, single-bundle semitendinosus/gracilis tendon, or double-bundle semitendinosus and gracilis tendon autograft. Two- and 5-year clinical and quality-of-life outcomes have been previously published. Standardized radiographs (bilateral P-A weight-bearing, lateral, and bilateral skyline patella views) were performed on all patients at baseline, 2-years and 5-years follow-up. Radiographic OA was graded separately in the medial, lateral, and patellofemoral compartments, using the International Knee Documentation Committee (IKDC) radiographic grading scale. An independent, fellowship-trained orthopaedic surgeon graded the radiographs for absence (A–Normal, B–Nearly Normal) or presence (C–Abnormal, D–Severely Abnormal) of OA. Three separate multi-variable logistic regression analyses were performed with medial, lateral, and patellofemoral radiographic OA as the dependent outcome variable. The independent predictor variables included: demographics (age and sex), knee alignment, stability (Lachman and pivot shift tests), meniscal treatment and chondral condition at index surgery, graft type, graft failure, re-injury, and secondary surgery. A bivariate logistic regression was performed for each individual predictor. For each knee compartment, individual predictor variables with p<0.1 in a bivariate regression analysis were added to a multi-variable logistic regression model if the event rate was adequate. Odds ratios (OR) and 95% confidence intervals (95%CI) were reported. IKDC grades for radiographic OA were available for 302 patients (91.5%) at 5-years post-operative. Medial OA was assessed in 35 patients (10.6%). Varus alignment, medial meniscectomy, medial compartment chondral damage, age > 35 years and male sex were identified as individual predictors of radiographic OA. However, only medial meniscectomy (OR 5.8 (95%CI 2.7–12.6, p<0.01)) and varus knee alignment (OR 2.4 (95%CI 1.1–5.1; p=0.03)) significantly predicted medial OA. Lateral OA was assessed in 67 patients (20.3%). Graft type, pivot shift, valgus alignment, lateral meniscectomy, lateral meniscal repair, and lateral compartment chondral damage were identified as individual predictors of radiographic OA. However, only patellar tendon graft (OR 2.4 (95%CI 1.2–4.8 p=0.02)), lateral meniscectomy (OR 2.6 (95%CI 1.3–5.2, p≤0.01)), lateral meniscal repair (OR 3.3 (95%CI 1.5–7.4, p≤0.01)) and lateral compartment chondral damage (OR 2.0 (95%CI 1.0 – 3.9, p=0.04)) significantly predicted lateral OA. Based on a bivariate analysis with 9 patients (2.7%) with patellofemoral OA, only patellofemoral chondral damage (OR 5.7 (95%CI 1.5–21.8, p=0.01)) was a significant predictor of OA. Graft failure, traumatic re-injury, and secondary surgery did not predict presence of radiographic OA at 5-years post-operative in any compartment. Graft failure, traumatic re-injury, and secondary surgery did not predict presence of radiographic OA at 5-years post-operative in any compartment. At 5-years post-ACL reconstruction, varus alignment and medial meniscectomy significantly increase the risk of developing medial OA. Use of a patellar tendon graft, lateral meniscectomy, lateral meniscal repair, and chondral damage significantly increase the risk of developing lateral OA. Graft failure, traumatic re-injury, or secondary surgery were not predictive of radiographic OA in any compartment. Higher proportions of patients with OA are required to increase confidence in these associations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".