Ni Jiajun, Yan Shi, Li Yangxiao, Chen Zhongqiang, Zeng Yan
Department of Orthopedics, Peking University Third Hospital, Beijing, China.
Beijing Key Laboratory of Spinal Disease Research, Beijing, China.
Spine (Phila Pa 1976). 2025 Aug 15;50(16):1127-1134. doi: 10.1097/BRS.0000000000005201. Epub 2024 Oct 30.
Retrospective single-center comparative analysis.
To develop a nomogram model for predicting late-onset neurological deficits (LONDs) in patients with kyphosis or kyphoscoliosis.
Patients with kyphosis or kyphoscoliosis might suffer from LONDs, and surgical correction may improve neurological function. Nevertheless, there exists a significant gap in the identification of predictive factors for LONDs in these patients.
A consecutive series of 244 patients with kyphosis or kyphoscoliosis who underwent corrective surgery between April 2010 and June 2024 were included in our study. Relevant measurements, including the Cobb angle, deformity angular ratio, and level of the apex were assessed and calculated using x-ray imaging. Spinal cord morphology at the apex of the major curve was evaluated using preoperative axial T2-weighted magnetic resonance imaging to categorize patients into 3 types based on the spinal cord shape classification system (SCSCS). To identify independent risk factors associated with LONDs, we employed univariate analysis, followed by backward stepwise multivariate logistic regression analysis. A nomogram was established based on the identified independent risk factors to predict the likelihood of LONDs in patients with kyphosis or kyphoscoliosis.
The mean age of the 244 patients was 46.4 ± 17.8 years, with an observed incidence of LONDs at 57.8%. The backward stepwise multivariate logistic regression analysis indicated that age, etiological diagnosis, and SCSCS were independent predictors of LONDs. Utilizing these independent risk factors, we constructed a nomogram model to estimate the probability of LONDs. The concordance index of the model was 0.912 (95% CI: 0.876-0.947), indicating a satisfactory level of accuracy in predicting the likelihood of LONDs.
The predictive factors for LONDs include age, etiological diagnosis, and SCSCS. We developed a nomogram model to predict LONDs, which could be useful for patient counseling and facilitating treatment-related decision-making.
回顾性单中心比较分析。
建立一种列线图模型,用于预测脊柱后凸或脊柱侧凸患者的迟发性神经功能缺损(LONDs)。
脊柱后凸或脊柱侧凸患者可能会出现迟发性神经功能缺损,手术矫正可能会改善神经功能。然而,在这些患者中,迟发性神经功能缺损预测因素的识别存在显著差距。
本研究纳入了2010年4月至2024年6月期间连续接受矫正手术的244例脊柱后凸或脊柱侧凸患者。使用X线成像评估并计算相关测量值,包括Cobb角、畸形角比和顶点水平。使用术前轴向T2加权磁共振成像评估主曲线顶点处的脊髓形态,根据脊髓形状分类系统(SCSCS)将患者分为3种类型。为了识别与迟发性神经功能缺损相关的独立危险因素,我们进行了单因素分析,随后进行向后逐步多因素逻辑回归分析。基于识别出的独立危险因素建立列线图,以预测脊柱后凸或脊柱侧凸患者发生迟发性神经功能缺损的可能性。
244例患者的平均年龄为46.4±17.8岁,迟发性神经功能缺损的观察发病率为57.8%。向后逐步多因素逻辑回归分析表明,年龄、病因诊断和脊髓形状分类系统是迟发性神经功能缺损的独立预测因素。利用这些独立危险因素,我们构建了一个列线图模型来估计迟发性神经功能缺损的概率。该模型的一致性指数为0.912(95%CI:0.876-0.947),表明在预测迟发性神经功能缺损可能性方面具有令人满意的准确性。
迟发性神经功能缺损的预测因素包括年龄、病因诊断和脊髓形状分类系统。我们开发了一种列线图模型来预测迟发性神经功能缺损,这可能有助于患者咨询并促进与治疗相关的决策制定。