A Matched-Cohort Population Study of Reoperation After Meniscal Repair With and Without Concomitant Anterior Cruciate Ligament Reconstruction
Bibliographic record
Abstract
BACKGROUND: Evidence for the success of a meniscal repair performed alone versus combined with anterior cruciate ligament reconstruction (ACLR) is equivocal. No large-scale comparative studies exist regarding this issue. HYPOTHESIS: In the general population, meniscal repair in a presumed stable knee has the same rate of reoperation as meniscal repair performed with ACLR. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: All meniscal repairs performed with ACLR in Ontario, Canada, between July 2003 and March 2008 in patients aged 15 to 60 years were identified using administrative billing, diagnostics, and procedural coding. This cohort was matched 1:1 for sex, age, and calendar year of surgery with a cohort of patients who underwent meniscal repair alone. The McNemar test of matched pairs was used to compare reoperation rates (debridement or repair) within 2 years of the index procedure. Conditional logistic regression analysis was used to identify potential risk factors for reoperation among unmatched patient (socioeconomic status surrogate, comorbidity) and provider (surgeon volume, academic hospital status) factors. RESULTS: Of 1332 patients who underwent meniscal repair and ACLR, 1239 (93%) were matched with patients who underwent meniscal repair alone. The rate of meniscal reoperation was 9.7% in the combined cohort compared with 16.7% in the repair alone cohort (P < .0001). In the regression analysis, only ACLR was protective against meniscal reoperation (odds ratio, 0.57; P < .0001). Surgeon volume of meniscal repair did not influence outcome. CONCLUSION: A meniscal repair performed in conjunction with ACLR carries a 7% absolute and 42% relative risk reduction of reoperation after 2 years compared with isolated meniscal repair.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".