Surgical Predictors of Clinical Outcomes After Revision Anterior Cruciate Ligament Reconstruction
Bibliographic record
Abstract
BACKGROUND: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have worse outcomes compared with primary ACL reconstruction. HYPOTHESIS: Certain factors under the control of the surgeon at the time of revision surgery can both negatively and positively affect outcomes. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: Patients undergoing revision ACL reconstruction were identified and prospectively enrolled between 2006 and 2011. Data collected included baseline demographics, intraoperative surgical technique and joint disorders, and a series of validated patient-reported outcome instruments (International Knee Documentation Committee [IKDC] subjective form, Knee Injury and Osteoarthritis Outcome Score [KOOS], Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC], and Marx activity rating scale) completed before surgery. Patients were followed up for 2 years and asked to complete an identical set of outcome instruments. Regression analysis was used to control for age, sex, body mass index (BMI), activity level, baseline outcome scores, revision number, time since last ACL reconstruction, and a variety of previous and current surgical variables to assess the surgical risk factors for clinical outcomes 2 years after revision ACL reconstruction. RESULTS: A total of 1205 patients (697 male [58%]) met the inclusion criteria and were successfully enrolled. The median age was 26 years, and the median time since their last ACL reconstruction was 3.4 years. Two-year follow-up was obtained on 82% (989/1205). Both previous and current surgical factors were found to be significant contributors toward poorer clinical outcomes at 2 years. Having undergone previous arthrotomy (nonarthroscopic open approach) for ACL reconstruction compared with the 1-incision technique resulted in significantly poorer outcomes for the 2-year IKDC ( P = .037; odds ratio [OR], 2.43; 95% CI, 1.05-5.88) and KOOS pain, sports/recreation, and quality of life (QOL) subscales ( P ≤ .05; OR range, 2.38-4.35; 95% CI, 1.03-10.00). The use of a metal interference screw for current femoral fixation resulted in significantly better outcomes for the 2-year KOOS symptoms, pain, and QOL subscales ( P ≤ .05; OR range, 1.70-1.96; 95% CI, 1.00-3.33) as well as WOMAC stiffness subscale ( P = .041; OR, 1.75; 95% CI, 1.02-3.03). Not performing notchplasty at revision significantly improved 2-year outcomes for the IKDC ( P = .013; OR, 1.47; 95% CI, 1.08-1.99), KOOS activities of daily living (ADL) and QOL subscales ( P ≤ .04; OR range, 1.40-1.41; 95% CI, 1.03-1.93), and WOMAC stiffness and ADL subscales ( P ≤ .04; OR range, 1.41-1.49; 95% CI, 1.03-2.05). Factors before revision ACL reconstruction that increased the risk of poorer clinical outcomes at 2 years included lower baseline outcome scores, a lower Marx activity score at the time of revision, a higher BMI, female sex, and a shorter time since the patient's last ACL reconstruction. Prior femoral fixation, prior femoral tunnel aperture position, and knee flexion angle at the time of revision graft fixation were not found to affect 2-year outcomes in this revision cohort. CONCLUSION: There are certain surgical variables that the physician can control at the time of revision ACL reconstruction that can modify clinical outcomes at 2 years. Whenever possible, opting for an anteromedial portal or transtibial surgical exposure, choosing a metal interference screw for femoral fixation, and not performing notchplasty are associated with significantly better 2-year clinical outcomes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".