Physical Examination and Imaging of the Lateral Collateral Ligament and Posterolateral Corner of the Knee
Bibliographic record
Abstract
The initial assessment of injury to the lateral collateral ligament and posterolateral corner is often challenging, particularly in the context of a multiligamentous injury. Although advanced imaging techniques have enhanced the evaluation of knee injuries, the significant, and often unique, contribution of clinical examination should not be overlooked. Clinical examination starts with a thorough history, which is instrumental in elucidating not only the patient's symptomatology but also the mechanism of injury. Differentiating between acute and chronic injury and teasing out the patient's functional limitations are instructive in defining the appropriate treatment plan. The treating physician needs patience, vigilance, and a variety of diagnostic tools to reach a precise diagnosis. Each injury should be approached in a methodical and systematic manner to ensure an accurate initial assessment. This review provides a step-wise approach to the clinical assessment of the lateral collateral ligament and posterolateral corner injured knee. Adjunctive imaging modalities and investigations are also discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".