Alberto Grassi, Kyle Borque, Martijn Dietvorst, Emanuele Altovino, Claudio Rossi, Luca Ambrosini, Alice Bondi, Stefano Zaffagnini
{"title":"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","authors":"Alberto Grassi, Kyle Borque, Martijn Dietvorst, Emanuele Altovino, Claudio Rossi, Luca Ambrosini, Alice Bondi, Stefano Zaffagnini","doi":"10.1002/jeo2.70280","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Purpose</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>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.</p>\n </section>\n \n <section>\n \n <h3> Level of Evidence</h3>\n \n <p>Level IV, case series.</p>\n </section>\n </div>","PeriodicalId":36909,"journal":{"name":"Journal of Experimental Orthopaedics","volume":"12 3","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jeo2.70280","citationCount":"0","resultStr":"{\"title\":\"Creation and validation of a treatment algorithm for skeletally immature patients with acute anterior cruciate ligament injury based on MRI and patient characteristics\",\"authors\":\"Alberto Grassi, Kyle Borque, Martijn Dietvorst, Emanuele Altovino, Claudio Rossi, Luca Ambrosini, Alice Bondi, Stefano Zaffagnini\",\"doi\":\"10.1002/jeo2.70280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>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.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Level of Evidence</h3>\\n \\n <p>Level IV, case series.</p>\\n </section>\\n </div>\",\"PeriodicalId\":36909,\"journal\":{\"name\":\"Journal of Experimental Orthopaedics\",\"volume\":\"12 3\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jeo2.70280\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Experimental Orthopaedics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://esskajournals.onlinelibrary.wiley.com/doi/10.1002/jeo2.70280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental Orthopaedics","FirstCategoryId":"1085","ListUrlMain":"https://esskajournals.onlinelibrary.wiley.com/doi/10.1002/jeo2.70280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
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.