Importance of patellofemoral and tibiofemoral cartilage lesions on trajectory of self-reported outcomes in patients at high risk of knee OA: 4–6 years follow-up of patients undergoing meniscal surgery
Bibliographic record
Abstract
Objective We evaluated whether patient-reported outcome trajectories (i.e., changes over time) differed by intraoperative compartmental cartilage lesion pattern over 4–6 years following arthroscopic meniscal surgery. Methods In this ancillary study of the Knee Arthroscopy Cohort Southern Denmark cohort, we intraoperatively categorized cartilage lesions as isolated patellofemoral, isolated tibiofemoral, or combined patellofemoral/tibiofemoral. Participants completed the Knee injury and Osteoarthritis Outcome Score (KOOS) pre-operatively, at 3 and 12 months, and at 4–6 years post-operatively and reported overall satisfaction at final follow-up. Our main outcome was KOOS 4 (grand mean of four subscale means). We evaluated whether KOOS 4 scores changed over time according to cartilage lesion patterns using adjusted mixed linear regression. We also estimated probability of treatment satisfaction using logistic regression. Results Of 630 participants with complete cartilage scores, 280 (44%) were women, mean (standard deviation) age was 49 (13) years, and BMI was 27.3 (4.4) kg/m 2 . KOOS 4 scores at baseline were slightly lower in all lesion groups compared to the no lesion group, yet only the combined group was statistically significantly lower. KOOS 4 trajectories were similar across cartilage lesion patterns, but by final follow-up, adjusted mean KOOS 4 scores were 6.8 (95% CI 2.2, 11.4) to 9.8 (1.1, 18.5) points lower in groups with cartilage lesions compared to the no lesion group. Probability of patient-reported satisfaction did not differ statistically by group. Conclusions Though KOOS 4 scores were slightly lower in groups with arthroscopically assessed cartilage lesions compared to the no lesion group, trajectories were similar across all groups.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".