The Epidemiology of Revision Anterior Cruciate Ligament Reconstruction in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Knowledge of the rate of and risk factors for re-revision, reoperation, and readmission after revision anterior cruciate ligament reconstruction (ACLR) is limited. PURPOSE: To determine the rate of and risk factors for re-revision, reoperation, and readmission after revision ACLR. STUDY DESIGN: Descriptive epidemiology study. METHODS: All patients who underwent first revision ACLR in Ontario, Canada, from January 2004 to December 2010 were identified and followed until December 2012. Exclusions included age <16 years, previous osteotomy, or multiligament knee reconstruction. The main outcome was re-revision ACLR. Secondary outcomes included reoperation (irrigation and debridement [I&D], meniscectomy, manipulation under anesthesia, contralateral ACLR, and total knee arthroplasty) and readmission. Survival to re-revision was determined using the Kaplan-Meier approach. A Cox proportional hazards model or logistic regression were used to determine the influence of patient, surgical, and provider factors on outcomes. A post hoc analysis was performed to determine the influence of the aforementioned factors on postoperative infection risk. RESULTS: Overall, 827 patients were included (median age, 30 years; 58.8% males). Single-stage revisions comprised 92.9% of cases, and a meniscal procedure (repair or debridement) was performed in 45.3% of cases. The re-revision rate at a mean follow-up of 4.8 ± 2.2 years was 4.4%, and the 5-year survival rate was 95.4%. The rates of I&D, meniscectomy, contralateral ACLR, and readmission were 0.8%, 3.1%, 3.4%, and 4.1%, respectively. Manipulation under anesthesia and total knee arthroplasty were rare. Young age significantly increased contralateral ACLR risk (risk decreased by 5.1% with each year of age >16 years; P = .02) but not re-revision ACLR risk. Low surgeon's annual volume of revision ACLR (<4 revisions/year: odds ratio, 1.2; P = .02) and male sex (odds ratio, 13.3; P = .01) significantly increased overall infection risk; male sex also influenced I&D risk. CONCLUSION: Re-revision, reoperation, and readmission rates after revision ACLR were low, and the risk for I&D, infection, and contralateral ACLR were influenced by male sex, low surgeon volume, and young age, respectively. CLINICAL RELEVANCE: This is the first study to determine morbidity rates and risk factors after revision ACLR, providing reference data from the general population.
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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 | 0.004 | 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) | 0.000 | 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".