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

IF 2.7 Q2 ORTHOPEDICS

Journal of Experimental Orthopaedics Pub Date : 2025-08-05 DOI:10.1002/jeo2.70280

Alberto Grassi, Kyle Borque, Martijn Dietvorst, Emanuele Altovino, Claudio Rossi, Luca Ambrosini, Alice Bondi, Stefano Zaffagnini

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Abstract

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.

Abstract Image

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基于MRI和患者特征的急性前交叉韧带损伤骨骼未成熟患者治疗算法的创建和验证

本研究旨在开发和验证一种临床决策算法，即“基于膝关节年龄的最佳ACL治疗”（BABY-Knee）算法，用于治疗骨骼未成熟患者的急性前交叉韧带（ACL）损伤。该算法整合了磁共振成像（MRI）结果和患者特异性特征，以区分适合保守治疗和需要手术干预的病例。方法对2022年2月至2024年10月在同一医院诊断为ACL破裂的75例骨骼未成熟患者（平均年龄：13.9±2.2岁）进行前瞻性队列研究。根据BABY-Knee算法将患者分类为手术或非手术候选人，该算法包含六个加权标准：mri检测的半月板撕裂，外侧胫股骨擦伤，骨骼年龄，损伤机制和旋转松弛。回顾性分析初始处理的结果以验证算法。结果75例患者中，55例（73.3%）行手术重建，20例（26.7%）行保守治疗。保守治疗失败12例（60%），需手术治疗。回顾性应用该算法识别手术候选人的阳性预测值为91.7%，对成功的保守治疗的阴性预测值为87.5%。结论BABY-Knee算法在指导骨未成熟急性前交叉韧带损伤患者的治疗决策方面具有较高的可靠性，近90%的病例预测保守治疗的结果。需要进一步的研究来证实其在其他前瞻性病例系列中的适用性。证据等级4级，案例系列。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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