Correlation of maximum flexion with clinical outcome after total knee replacement in Asian patients
Bibliographic record
Abstract
This study aimed to determine the correlation between the amount of maximum flexion and the clinical outcome in 207 Koreans (333 knees) undergoing total knee replacement. The association of maximum flexion with clinical outcome was evaluated one year postoperatively using three scoring systems; the American Knee Society score, Western Ontario McMaster Universities Osteoarthritis index and the Short Form-36. The mean maximum flexion decreased post-operatively at 12 months from 140.1 degrees (60 degrees to 160 degrees ) to 133.0 degrees (105 degrees to 150 degrees ). Only the social function score of the Short Form-36 correlated significantly with maximum flexion (correlation coefficient = 0.180, p = 0.039). In comparative analyses of subgroups divided by a maximum flexion of 120 degrees , we found no significant differences in any parameters except the social function score of the Short Form-36 (41.9 vs 47.3, p = 0.031). Knees with a maximum flexion of more than 135 degrees had a better functional Western Ontario McMasters Universities Osteoarthritis index score than knees with maximum flexion of 135 degrees or less (17.5 vs 14.3, p = 0.031). We found only weak correlation between the postoperative maximum flexion and the clinical parameters for pain relief, function and quality of life, even in Korean patients. Efforts to increase post-operative maximum flexion should be exercised with caution until concerns relating to high-flexion activities are sufficiently resolved.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".