Rong Yi, Wang Kaixuan, Pan Yalan, Zhang Tianchi, Ma Yong, Wang Lining, Guo Yang, Chen Si, Shao Yang, Zhu Tingchen, Wu Shixiang, Hua Zhen, Wang Jianwei, Yu Hao
Department of Traumatology & Orthopedics, Wuxi Affiliated Hospital of Nanjing University of Chinese Medicine, Wuxi, China.
School of Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Front Surg. 2025 Jun 16;12:1564825. doi: 10.3389/fsurg.2025.1564825. eCollection 2025.
This study aimed to construct a nomogram to predict the likelihood of early recurrence in patients with lumbar disc herniation (LDH) following unilateral biportal endoscopic (UBE) surgery.
A retrospective analysis was conducted on LDH patients who underwent UBE surgery in our department between January 1, 2022, and December 31, 2023. The eligible cohort was randomly divided into training and validation sets in a 7:3 ratio. Key predictors for the nomogram were identified through a combination of least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis. The model's performance was assessed using the C-index, the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. The validation set was used to further evaluate the model's robustness.
A total of 289 patients were included in the study, among whom 50 experienced recurrent LDH (rLDH). Five risk factors were identified as significant predictors for rLDH: width of protrusion base (WPB), bone removal range (BRR), Modic changes, type of LDH, and middle vertebral space height (MVH). The C-index values for the training and validation sets were 0.834 and 0.804, respectively. The AUC values were 0.834 (95% CI: 0.750-0.918) in the training set and 0.804 (95% CI: 0.697-0.910) in the validation set. Calibration curves demonstrated excellent concordance between the predicted and observed outcomes. Decision curve analysis indicated that using the nomogram to predict rLDH risk provided a positive net benefit when the threshold probability was between 4% and 63%.
This study successfully developed and validated a nomogram to predict early recurrence in LDH patients following UBE surgery. The model provides a valuable tool for clinicians to assess individual rLDH risk, enabling timely interventions to improve postoperative outcomes.
本研究旨在构建一种列线图,以预测腰椎间盘突出症(LDH)患者单侧双通道内镜(UBE)手术后早期复发的可能性。
对2022年1月1日至2023年12月31日在我科接受UBE手术的LDH患者进行回顾性分析。符合条件的队列以7:3的比例随机分为训练集和验证集。通过最小绝对收缩和选择算子(LASSO)回归与多变量逻辑回归分析相结合的方法,确定列线图的关键预测因素。使用C指数、受试者操作特征曲线(AUC)下面积、校准曲线和决策曲线分析来评估模型的性能。验证集用于进一步评估模型的稳健性。
本研究共纳入289例患者,其中50例发生复发性LDH(rLDH)。确定了五个危险因素为rLDH的显著预测因素:突出基底宽度(WPB)、骨质去除范围(BRR)、Modic改变、LDH类型和中间椎间隙高度(MVH)。训练集和验证集的C指数值分别为0.834和0.804。训练集中的AUC值为0.834(95%CI:0.750-0.918),验证集中的AUC值为0.804(95%CI:0.697-0.910)。校准曲线显示预测结果与观察结果之间具有良好的一致性。决策曲线分析表明,当阈值概率在4%至63%之间时,使用列线图预测rLDH风险可提供正净效益。
本研究成功开发并验证了一种列线图,用于预测UBE手术后LDH患者的早期复发。该模型为临床医生评估个体rLDH风险提供了有价值的工具,有助于及时进行干预以改善术后结果。