Han Bo, Hai Junrui Jonathan, Pan Aixing, Wang Yingjie, Hai Yong
Beijing Jishuitan Hospital, Affiliated with Capital Medical University, Beijing, China.
Joint Laboratory for Research and Treatment of Spinal Cord Injury in Spinal Deformity, Capital Medical University, Beijing, China.
Sci Rep. 2025 Jan 15;15(1):2024. doi: 10.1038/s41598-025-86330-2.
We aimed to analyze the cervical sagittal alignment change following the growing rod treatment in early-onset scoliosis (EOS) and identify the risk factors of sagittal cervical imbalance after growing-rod surgery of machine learning. EOS patients from our centre between 2007 and 2019 were retrospectively reviewed. Radiographic parameters include the cervical lordosis (CL), T1 slope, C2-C7 sagittal vertical axis (C2-7 SVA), primary curve Cobb angle, thoracic kyphosis (TK), C7-S1 sagittal vertical axis (C7-S1 SVA) and proximal junctional angle (PJA) were evaluated preoperatively, postoperatively and at the final follow-up. The parameters were analyzed using a t-test and χ2 test. The machine learning methodology of a sparse additive machine (SAM) was applied to identify the risk factors that caused the cervical imbalance. 138 patients were enrolled in this study (96 male and 42 female). The mean thoracic curve Cobb angle was 67.00 ± 22.74°. The mean age at the first operation was 8.5 ± 2.6yrs. The mean follow-up was 38.48 ± 10.87 months. CL, T1 slope, and C2-7 SVA increased significantly in the final follow-up compared with the pre-operative data. (P < 0.05). The CL and T1 slope increased more significantly in the group of patients who had proximal junctional kyphosis (PJK) compared with the patients without PJK (P < 0.05). The location of the upper instrumented vertebrae (UIV) and single/dual growing rod had no significant influence on the sagittal cervical parameters (P > 0.05). According to the SAM analysis of machine learning algorithms, Postoperative PJK, more improvement of kyphosis, and T1 slope angle were identified as the risk factors of cervical sagittal imbalance during the treatment of growing rod surgery. The growing rod surgery in EOS significantly affected the cervical sagittal alignment. Postoperative PJK and more improvement of kyphosis and T1 slope angle would lead to a higher incidence of cervical sagittal imbalance.
我们旨在分析早发性脊柱侧凸（EOS）患者在生长棒治疗后的颈椎矢状位对线变化，并通过机器学习确定生长棒手术后颈椎矢状面失衡的危险因素。对2007年至2019年间来自我们中心的EOS患者进行回顾性研究。影像学参数包括颈椎前凸（CL）、T1斜率、C2-C7矢状垂直轴（C2-7 SVA）、主弯Cobb角、胸椎后凸（TK）、C7-S1矢状垂直轴（C7-S1 SVA）和近端交界角（PJA），在术前、术后及末次随访时进行评估。采用t检验和χ2检验对参数进行分析。应用稀疏加法机器（SAM）的机器学习方法来确定导致颈椎失衡的危险因素。本研究共纳入138例患者（男96例，女42例）。平均胸椎弯Cobb角为67.00±22.74°。首次手术时的平均年龄为8.5±2.6岁。平均随访时间为38.48±10.87个月。与术前数据相比，末次随访时CL、T1斜率和C2-7 SVA显著增加（P<0.05）。与无近端交界后凸（PJK）的患者相比，有PJK的患者组中CL和T1斜率增加更显著（P<0.05）。上位固定椎（UIV）的位置以及单/双生长棒对颈椎矢状面参数无显著影响（P>0.05）。根据机器学习算法的SAM分析，术后PJK、后凸改善程度更大以及T1斜率角度被确定为生长棒手术治疗期间颈椎矢状面失衡的危险因素。EOS患者的生长棒手术显著影响颈椎矢状位对线。术后PJK以及后凸和T1斜率角度改善程度更大将导致颈椎矢状面失衡的发生率更高。
