Prospective Trial of a Treatment Algorithm for the Management of the Anterior Cruciate Ligament-Injured Knee

Abstract

Background: Specific guidelines for operative versus nonoperative management of anterior cruciate ligament injuries do not yet exist. Hypothesis: Surgical risk factors can be used to indicate whether reconstruction or conservative management is best for an individual patient. Study Design: Prospective nonrandomized controlled clinical trial; Level of evidence, 2. Methods: Patients were classified as high, moderate, or low risk using preinjury sports participation and knee laxity measurements. Early anterior cruciate ligament reconstruction (within 3 months of injury) was recommended to high-risk patients and conservative care to low-risk patients. It was recommended that moderate-risk patients have either early reconstruction or conservative care, according to the day of presentation. Assessment of subjective outcomes, activity, physical measurements, and radiographs was performed at mean follow-up of 6.6 years. Results: Early phase conservative management resulted in more late phase meniscus surgery than did early phase reconstruction at all risk levels (high risk, 25% vs 6.5%; moderate risk, 37% vs 7.7%, P =. 01; low risk, 16% vs 0%). Early- and late-reconstruction patients’ Tegner scores increased from presurgery to follow-up (P <. 001) but did not return to preinjury levels. Early-reconstruction patients had higher rates of degenerative change on radiographs than did nonreconstruction patients (P <. 05). Conclusions: Early phase reconstruction reduced late phase knee laxity, risk of symptomatic instability, and the risk of late meniscus tear and surgery. Moderate- and high-risk patients had similar rates of late phase injury and surgery. Reconstruction did not prevent the appearance of late degenerative changes on radiographs. Relationship between bone contusion on initial magnetic resonance images and the finding of degenerative changes on follow-up radiographs were not detected. The treatment algorithm used in this study was effective in predicting risk of late phase knee surgery.