How Does the Presence of Unstable Chondral Lesions Affect Patient Outcomes After Partial Meniscectomy? The ChAMP Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Chondral lesions are commonly encountered during arthroscopic partial meniscectomy (APM); however, it is unknown how these lesions affect postoperative outcomes. PURPOSE: The authors compared postoperative outcomes among patients with and without unstable chondral lesions 1 year after APM. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: The authors conducted a secondary analysis of data from the ChAMP (Chondral Lesions and Meniscus Procedures) randomized controlled trial. They compared the following outcomes for patients with unstable chondral lesions that were left in situ and observed (CL-noDeb) versus patients without unstable chondral lesions (NoCL) at 1 year after APM: Western Ontario and McMaster Universities Osteoarthritis Index, Knee injury and Osteoarthritis Outcome Score, visual analog scale for pain, the Short Form Health Survey, range of motion, quadriceps circumference, and effusion. Multivariate linear regression was used to obtain mean differences (MDs) with corresponding 95% CIs adjusted for age, body mass index, and preoperative score (for postoperative scores). RESULTS: Compared with the CL-noDeb group, the NoCL group had greater improvement in Western Ontario and McMaster Universities Osteoarthritis Index for pain (MD, 7.9, 95% CI: 2.7-13.1), stiffness (MD, 9.1, 95% CI: 1.9-16.3), and physical function (MD, 4.6, 95% CI: 0.1-9.0) and Knee injury and Osteoarthritis Outcome Score for pain (MD, 8.4, 95% CI: 2.7-14.0), function in sport and recreation (MD, 11, 95% CI: 3.0-19.1), and quality of life (MD, 10.4, 95% CI: 2.3-18.5). The NoCL group was less likely than the CL-noDeb group to have an effusion ( P = .02) 1 year after surgery. CONCLUSION: Patients undergoing APM without unstable chondral lesions had better outcomes than patients with unstable chondral lesions.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".