Johnstone Thomas, Espiritu Joseph, Tompkins Marc, Milewski Matthew D, Nissen Carl, Shea Kevin G, Nelson Bradley, Egger Anthony, Anderson Christian, Lee Pace Jamie, Polousky John, Ellemann Jutta, Meenen Norbert, Edmonds Eric, Ellis Henry, Fabricant Peter, Krych Aaron, Myer Greg, Kocher Mininder, Carrey James
Stanford University School of Medicine, Stanford, California, USA.
Department of Orthopaedic Surgery, Stanford University School of Medicine, Stanford, California, USA.
Orthop J Sports Med. 2024 Dec 16;12(12):23259671241297145. doi: 10.1177/23259671241297145. eCollection 2024 Dec.
There are limited evidence-based guidelines to predict which osteochondritis dissecans (OCD) lesions will heal with nonoperative treatment.
To train a set of classification algorithms to predict nonoperative OCD healing while identifying new clinically meaningful predictors.
Case-control study; Level of evidence, 3.
Patients with OCD of the knee with open physes undergoing nonoperative management were prospectively queried from the Research on OCD of the Knee (ROCK) cohort (https://kneeocd.org) in April 2022. Patients were included if they met the study criteria for nonoperative treatment success or failure. Nonoperative treatment success was defined as complete healing on magnetic resonance imaging (MRI) and total return to sports participation. Failure was defined as the crossover from nonoperative management to surgery at any point at or beyond the 3-month follow-up. If a patient did not meet one of these criteria, they were not included. Normalized lesion size, lesion location, patient characteristics, and symptoms were used as clinically relevant predictors.
A total of 64 patients were included, of whom 24 (37.5%) patients successfully healed with nonoperative management. Multivariate logistic regression revealed that a 1% increase in normalized lesion width was associated with an increase in the likelihood of nonoperative failure (odds ratio [OR], 1.41 [95% CI, 1.17-1.81]; < .01). By contrast, lesions in the posterior sagittal zone (OR, 0.08 [95% CI, 0.009-0.43]; < .01) or the medial-most coronal zone (for lesions of the medial femoral) and lateral-most coronal zone (for lesions of the lateral femoral condyle) on MRI (OR, 0.05 [95% CI, 0.004-0.44]; < .01) were associated with a decrease in the likelihood of nonoperative treatment failure. Support vector machines had a cross-validated area under the receiver operating characteristic curve of 0.89 and a classification accuracy of 83.3%.
Lesion location in the posterior aspect of the condyle on sagittal MRI and lesion location in the medial-most or lateral-most locations on coronal MRI were identified as statistically significant predictors of increased nonoperative treatment success on multivariate analysis. Machine learning models can predict which OCD lesions will heal with nonoperative management with superior accuracy compared with previously published models.
预测哪些剥脱性骨软骨炎（OCD）病变可通过非手术治疗愈合的循证指南有限。
训练一组分类算法以预测OCD非手术治疗的愈合情况，同时识别新的具有临床意义的预测因素。
病例对照研究；证据等级，3级。
2022年4月，从膝关节OCD研究（ROCK）队列（https://kneeocd.org）中前瞻性查询正在接受非手术治疗且骨骺未闭的膝关节OCD患者。符合非手术治疗成功或失败研究标准的患者纳入研究。非手术治疗成功定义为磁共振成像（MRI）显示完全愈合且完全恢复运动参与。失败定义为在3个月及以后的任何时间从非手术治疗转为手术治疗。如果患者不符合上述标准之一，则不纳入。将标准化病变大小、病变位置、患者特征和症状用作临床相关预测因素。
共纳入64例患者，其中24例（37.5%）通过非手术治疗成功愈合。多因素逻辑回归显示，标准化病变宽度每增加1%，非手术治疗失败的可能性增加（比值比[OR]，1.41[95%可信区间，1.17 - 1.81]；P <.01）。相比之下，矢状位MRI上后矢状区的病变（OR，0.08[95%可信区间，0.009 - 0.43]；P <.01）或内侧股骨髁病变的最内侧冠状区以及外侧股骨髁病变的最外侧冠状区（OR，0.05[95%可信区间，0.004 - 0.44]；P <.01）与非手术治疗失败可能性降低相关。支持向量机的受试者操作特征曲线下交叉验证面积为0.89，分类准确率为83.3%。
矢状位MRI上髁后部的病变位置以及冠状位MRI上最内侧或最外侧的病变位置在多因素分析中被确定为非手术治疗成功率增加的统计学显著预测因素。与先前发表的模型相比，机器学习模型能够更准确地预测哪些OCD病变可通过非手术治疗愈合。
