Li Xiaochuan, Bai Xuedong, Wu Yaohong, Ruan Dike
Department of Orthopedic, Navy General Hospital, NO. 6 Fucheng Road, Beijing, 100048, China.
Department of Orthopedic, Gaozhou people's Hospital, Guangdong, China.
BMC Musculoskelet Disord. 2016 Mar 15;17:128. doi: 10.1186/s12891-016-0973-3.
To construct and validate a model to predict responsible nerve roots in lumbar degenerative disease with diagnostic doubt (DD).
From January 2009-January 2013, 163 patients with DD were assigned to the construction (n = 106) or validation sample (n = 57) according to different admission times to hospital. Outcome was assessed according to the Japanese Orthopedic Association (JOA) recovery rate as excellent, good, fair, and poor. The first two results were considered as effective clinical outcome (ECO). Baseline patient and clinical characteristics were considered as secondary variables. A multivariate logistic regression model was used to construct a model with the ECO as a dependent variable and other factors as explanatory variables. The odds ratios (ORs) of each risk factor were adjusted and transformed into a scoring system. Area under the curve (AUC) was calculated and validated in both internal and external samples. Moreover, calibration plot and predictive ability of this scoring system were also tested for further validation.
Patients with DD with ECOs in both construction and validation models were around 76 % (76.4 and 75.5 % respectively).
more preoperative visual analog pain scale (VAS) score (OR = 1.56, p < 0.01), stenosis levels of L4/5 or L5/S1 (OR = 1.44, p = 0.04), stenosis locations with neuroforamen (OR = 1.95, p = 0.01), neurological deficit (OR = 1.62, p = 0.01), and more VAS improvement of selective nerve route block (SNRB) (OR = 3.42, p = 0.02).
the internal area under the curve (AUC) was 0.85, and the external AUC was 0.72, with a good calibration plot of prediction accuracy. Besides, the predictive ability of ECOs was not different from the actual results (p = 0.532).
We have constructed and validated a predictive model for confirming responsible nerve roots in patients with DD. The associated risk factors were preoperative VAS score, stenosis levels of L4/5 or L5/S1, stenosis locations with neuroforamen, neurological deficit, and VAS improvement of SNRB. A tool such as this is beneficial in the preoperative counseling of patients, shared surgical decision making, and ultimately improving safety in spine surgery.
构建并验证一个用于预测存在诊断疑问（DD）的腰椎退行性疾病中责任神经根的模型。
从2009年1月至2013年1月，163例DD患者根据不同的入院时间被分配至构建样本（n = 106）或验证样本（n = 57）。根据日本骨科协会（JOA）恢复率将结果评估为优、良、中、差。前两个结果被视为有效临床结局（ECO）。患者的基线特征和临床特征被视为次要变量。使用多因素逻辑回归模型构建一个以ECO为因变量、其他因素为解释变量的模型。对每个风险因素的比值比（OR）进行调整并转化为评分系统。计算曲线下面积（AUC）并在内部和外部样本中进行验证。此外，还测试了该评分系统的校准图和预测能力以进行进一步验证。
构建模型和验证模型中具有ECO的DD患者均约为76%（分别为76.4%和75.5%）。
术前视觉模拟疼痛量表（VAS）评分更高（OR = 1.56，p < 0.01）、L4/5或L5/S1节段狭窄（OR = 1.44，p = 0.04）、伴有神经孔的狭窄部位（OR = 1.95，p = 0.01）、神经功能缺损（OR = 1.62，p = 0.01）以及选择性神经阻滞（SNRB）后VAS改善更明显（OR = 3.42，p = 0.02）。
内部曲线下面积（AUC）为0.85，外部AUC为0.72，预测准确性校准图良好。此外，ECO的预测能力与实际结果无差异（p = 0.532）。
我们构建并验证了一个用于确定DD患者责任神经根的预测模型。相关风险因素为术前VAS评分、L4/5或L5/S1节段狭窄、伴有神经孔的狭窄部位、神经功能缺损以及SNRB后VAS改善。这样一种工具有助于患者的术前咨询、共同的手术决策制定，并最终提高脊柱手术的安全性。
