Anterolateral Ligament Injury in Knee Dislocations
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to describe the prevalence and associated factors of anterolateral ligament (ALL) injury in knee dislocation (KD). METHODS: A retrospective review of charts and radiological images was done for patients who underwent multiligamentous knee reconstruction surgery for KD in the authors' institution from May 2008 to December 2016. The inclusion criteria were both genders, skeletally mature, and first dislocation. Previous anterior cruciate ligament injury or surgery were the exclusion criteria. Magnetic resonance imaging was used to describe the ALL injury. The association of ALL injury with other variables related to the injury and the patient's background features was examined. RESULTS: Forty-eight patients (49 knees) were included. The mean age of the patients was 32.3 ± 10.6 years. High-energy trauma was the mechanism of dislocation in 28 (57.1%) knees. Thirty-one knees (63.3%) were classified as KD type IV. Forty-five (91.8%) knees had a complete ALL injury, and 3 (6.1%) knees had incomplete ALL injury. Forty (81.6%) knees had a complete ALL injury at the proximal fibers of the ALL, while 23 (46.9%) knees had complete distal ALL injury. None of the 46 (93.9%) knees with lateral collateral ligament injury had normal proximal ALL fibers (P = .012). Injury to the distal fibers of the ALL, as well as overall ALL injury, was not associated with any other variables (P > .05). Moreover, all patients with associated tibial plateau fractures (9; 18.4%) had abnormality of the proximal fibers of the ALL (P = .033). CONCLUSIONS: ALL injury is highly prevalent among dislocated knees. Most of the injuries are of high grade and involve the proximal, suprameniscal, fibers of the ligament. LEVEL OF EVIDENCE: Level IV, retrospective case series with no comparison group.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".