Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Am J Sports Med. 2022 Nov;50(13):3544-3556. doi: 10.1177/03635465221124258. Epub 2022 Sep 30.
Surgical and nonoperative management of anterior cruciate ligament (ACL) injuries seek to mitigate the risk of knee instability and secondary meniscal injury. However, the associated risk and timing of secondary meniscal tears have not been completely elucidated.
To compare risk and timing of secondary meniscal injury between patients receiving nonoperative management, delayed ACL reconstruction (ACLR), and early ACLR using a machine learning survival analysis.
Cohort study; Level of evidence, 3.
A geographic database was used to identify and review records of patients with a diagnosis of ACL rupture between 1990 and 2016 with minimum 2-year follow-up. Patients undergoing ACLR were matched 1:1 with nonoperatively treated controls. Rate and time to secondary meniscal tear were compared using random survival forest algorithms; independent models were developed and internally validated for predicting injury-free duration in both cohorts. Performance was measured using out-of-bag -statistic, calibration, and Brier score. Model interpretability was enhanced using global variable importance and partial dependence curves.
The study included 1369 patients who underwent ACLR and 294 patients who had nonoperative treatment. After matching, no significant differences in rates of secondary meniscal tear were found ( = .09); subgroup analysis revealed the shortest periods of meniscal survival in patients undergoing delayed ACLR. The random survival forest algorithm achieved excellent predictive performance for the ACLR cohort, with an out-of-bag -statistic of 0.80 and a Brier score of 0.11. Significant variables for risk of meniscal tear for the ACLR cohort included time to return to sports or activity ≤350 days, time to surgery ≥50 days, age at injury ≤40 years, and high-impact or rotational landing sports, whereas those in the nonoperative cohort model included time to RTS ≤200 days, visual analog scale pain score >3 at consultation, hypermobility, and noncontact sports.
Delayed ACLR demonstrated the greatest long-term risk of meniscal injury compared with nonoperative treatment or early ACLR. Risk factors for decreased meniscal survival after ACLR included increased time to surgery, shorter time to return to sports or activity, older age at injury, and involvement in high-impact or rotational landing sports. Pending careful external validation, these models may be deployed in the clinical space to provide real-time insights and enhance decision making.
前交叉韧带(ACL)损伤的手术和非手术治疗旨在降低膝关节不稳定和继发性半月板损伤的风险。然而,继发性半月板撕裂的相关风险和时间尚未完全阐明。
使用机器学习生存分析比较接受非手术治疗、延迟 ACL 重建(ACLR)和早期 ACLR 的患者之间继发性半月板损伤的风险和时间。
队列研究;证据水平,3 级。
使用地理数据库,对 1990 年至 2016 年间诊断为 ACL 破裂的患者的记录进行识别和回顾,随访时间至少 2 年。ACL 重建患者与非手术治疗的对照组 1:1 匹配。使用随机生存森林算法比较继发性半月板撕裂的发生率和时间;为两个队列分别建立和内部验证独立的预测无损伤持续时间的模型。使用袋外 -统计量、校准和 Brier 评分来衡量性能。使用全局变量重要性和部分依赖曲线来增强模型的可解释性。
该研究纳入了 1369 例接受 ACLR 的患者和 294 例接受非手术治疗的患者。匹配后,两组继发性半月板撕裂的发生率无显著差异( =.09);亚组分析显示,延迟 ACLR 的患者半月板存活时间最短。随机生存森林算法对 ACLR 队列具有出色的预测性能,袋外 -统计量为 0.80,Brier 得分为 0.11。ACL 重建队列中半月板撕裂风险的显著变量包括运动或活动恢复时间≤350 天、手术时间≥50 天、损伤时年龄≤40 岁以及高冲击或旋转着陆运动,而非手术队列模型中的变量包括 RTS 恢复时间≤200 天、就诊时视觉模拟评分(VAS)疼痛评分>3、过度活动和非接触运动。
与非手术治疗或早期 ACLR 相比,延迟 ACLR 显示出最大的长期半月板损伤风险。ACL 重建后半月板存活率降低的风险因素包括手术时间延长、运动或活动恢复时间缩短、损伤时年龄较大以及参与高冲击或旋转着陆运动。在经过仔细的外部验证之前,这些模型可以在临床环境中部署,以提供实时见解并增强决策制定。