Predictors of Patient-Reported Outcomes at 2 Years After Revision Anterior Cruciate Ligament Reconstruction
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcomes (PROs) are a valid measure of results after revision anterior cruciate ligament (ACL) reconstruction. Revision ACL reconstruction has been documented to have worse outcomes when compared with primary ACL reconstruction. Understanding positive and negative predictors of PROs will allow surgeons to modify and potentially improve outcome for patients. PURPOSE/HYPOTHESIS: The purpose was to describe PROs after revision ACL reconstruction and test the hypothesis that patient- and technique-specific variables are associated with these outcomes. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Patients undergoing revision ACL reconstruction were identified and prospectively enrolled by 83 surgeons over 52 sites. Data included baseline demographics, surgical technique and pathology, and a series of validated PRO instruments: International Knee Documentation Committee (IKDC), Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index, and Marx Activity Rating Scale. Patients were followed up at 2 years and asked to complete the identical set of outcome instruments. Multivariate regression models were used to control for a variety of demographic and surgical factors to determine the positive and negative predictors of PRO scores at 2 years after revision surgery. RESULTS: A total of 1205 patients met the inclusion criteria and were successfully enrolled: 697 (58%) were male, with a median cohort age of 26 years. The median time since their most recent previous ACL reconstruction was 3.4 years. Two-year questionnaire follow-up was obtained from 989 patients (82%). The most significant positive predictors of 2-year IKDC scores were a high baseline IKDC score, high baseline Marx activity level, male sex, and having a longer time since the most recent previous ACL reconstruction, while negative predictors included having a lateral meniscectomy before the revision ACL reconstruction or having grade 3/4 chondrosis in either the trochlear groove or the medial tibial plateau at the time of the revision surgery. For KOOS, having a high baseline score and having a longer time between the most recent previous ACL reconstruction and revision surgery were significant positive predictors for having a better (ie, higher) 2-year KOOS, while having a lateral meniscectomy before the revision ACL reconstruction was a consistent predictor for having a significantly worse (ie, lower) 2-year KOOS. Statistically significant positive predictors for 2-year Marx activity levels included higher baseline Marx activity levels, younger age, male sex, and being a nonsmoker. Negative 2-year activity level predictors included having an allograft or a biologic enhancement at the time of revision surgery. CONCLUSION: PROs after revision ACL reconstruction are associated with a variety of patient- and surgeon-related variables. Understanding positive and negative predictors of PROs will allow surgeons to guide patient expectations as well as potentially improve outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".