Creation and validation of a treatment algorithm for skeletally immature patients with acute anterior cruciate ligament injury based on MRI and patient characteristics.

Purpose: This study aimed to develop and validate a clinical decision-making algorithm, the 'Best ACL-treatment Based on the Years of the Knee' (BABY-Knee) Algorithm, for treating acute anterior cruciate ligament (ACL) injuries in skeletally immature patients. The algorithm integrates magnetic resonance imaging (MRI) findings and patient-specific characteristics to differentiate cases suitable for conservative management from those requiring surgical intervention. Methods: A prospective cohort of 75 skeletally immature patients (mean age: 13.9 ± 2.2 years) diagnosed with ACL rupture at a single institution between February 2022 and October 2024 was evaluated. Patients were categorized as surgical or non-surgical candidates based on the BABY-Knee Algorithm, which incorporates six weighted criteria: MRI-detected meniscal tears, lateral tibiofemoral bone bruises, skeletal age, injury mechanism and rotatory laxity. Outcomes of initial management were retrospectively analyzed for algorithm validation. Results: Of the 75 patients, 55 (73.3%) underwent surgical reconstruction, while 20 (26.7%) were managed conservatively. Conservative treatment failed in 12 cases (60%), necessitating surgical intervention. Retrospective application of the algorithm yielded a positive predictive value of 91.7% for identifying surgical candidates and a negative predictive value of 87.5% for successful conservative treatment. Conclusion: The BABY-Knee Algorithm demonstrated high reliability in guiding treatment decisions for skeletally immature patients with acute ACL injuries, predicting outcomes of conservative treatment in nearly 90% of cases. Further studies are required to confirm its applicability in additional prospective case series. Level of Evidence: Level IV, case series.