Double-row repair of the distal attachment of the superficial medial collateral ligament: a basic science pilot study
Bibliographic record
Abstract
PURPOSE: To describe a novel repair for tibial-sided superficial medial collateral ligament (sMCL) lesions and determine whether it restores medial joint opening to uninjured state. Agreement among experienced knee surgeons when evaluating medial joint laxity was also explored. METHODS: On a series of eight human cadaveric knees, surgical elevation of the distal insertion of the sMCL was performed to replicate injury. The cut ligament was repaired using a novel double-row 'suture-bridge' technique. Valgus stress fluoroscopic images were taken with the ligament in three states: (I)ntact, (C)ut and (R)epaired, in two positions: 0 and 20° flexion. Joint opening was measured on calibrated fluoroscopic images (in mm) based on methods described by LaPrade. Joint space opening was also estimated by three experienced knee surgeons without fluoroscopy. RESULTS: On fluoroscopy, no significant differences in mean joint opening were observed between an intact versus repaired ligament in 0 and 20° flexion [0.5 mm (95 % CI -1.6, 0.73; n.s.) and 0.3 mm (95 % CI -1.17, 1.71; n.s.)], respectively. Agreement among surgeons was substantial (ICC = 0.622, 95 % CI 0.52, 0.73). CONCLUSION: The surgical technique adequately restored joint opening to an intact state with response to valgus stress. Agreement among surgeons when quantifying joint opening in mm was substantial. This paper addresses a technically difficult problem and provides pragmatic and practical information for surgeons who manage complicated multi-ligament knee injuries.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".