Objective

Cervical spondylotic myelopathy (CSM) is caused by cervical spine degeneration and surgery may be beneficial, but selection for surgery might be challenging. We performed a multimodal analysis to assess predicting factors that may be useful to help surgeons in this choice.

Patients and methods

We retrospectively evaluated clinical, motor evoked potentials (MEP), and MRI data of patients who undergone surgery for CSM. Seventy-six consecutive patients (46 males) were enrolled. The median age was 65.5 [IQR: 57–71] years, and the duration of symptoms was 11 [8–13] months. A multivariate analysis in order to assess predictors of outcome and ROC curve analysis were performed.

Results

Thirty patients (M:18, 39.5%) gained 6 or more points on mJOA and they were collected in good recovery group, whereas 46 patients (60.5%, M:28) showed a fair recovery. We developed a comprehensive score system (CSS) taking into account clinical, neurophysiological, and neuroradiological data. ROC curve analysis was performed to determine the discriminative power of four models derived from the multivariate logistic regression analysis for predictors of good outcome considering only clinical variables, MRI variables, and MEP variables or considering the comprehensive model, demonstrating a good accuracy of CSS model to predict outcome.

Conclusion

This study demonstrates that CSS model taking into consideration functional assessment by mJOA score, neurologic evaluation, cervical MRI, and MEP may be a feasible method to predict outcome in patients candidate to surgery, supporting surgeon’s decisions both for those patients candidate to surgery and for patients in whom a “wait and see” approach could be proposed.

中文翻译：

---

颈椎病脊髓病患者的多维评估。全面评分系统的实用性。

目的

颈椎变性引起的颈椎病（CSM），手术可能是有益的，但手术的选择可能具有挑战性。我们进行了多模式分析，以评估可能有助于这种选择的外科医生的预测因素。

患者和方法

我们回顾性评估了接受CSM手术的患者的临床，运动诱发电位（MEP）和MRI数据。连续纳入76例患者（46例男性）。中位年龄为65.5 [IQR：57-71]岁，症状持续时间为11 [8-13]个月。为了评估结果的预测因子和ROC曲线分析，进行了多变量分析。

结果

30例患者（m：18，39.5％）在mJOA上获得6分以上，并被归入良好恢复组，而46例患者（60.5％，M：28）表现出良好的恢复。我们开发了一种综合评分系统（CSS），其中考虑了临床，神经生理学和神经放射学数据。进行了ROC曲线分析，以确定从多元logistic回归分析得出的四个模型的判别力，这些模型对于仅考虑临床变量，MRI变量和MEP变量或考虑综合模型的预后良好的预测指标，表明CSS模型具有较高的准确性预测结果。

结论

这项研究表明，考虑通过mJOA评分，神经系统评估，颈椎MRI和MEP进行功能评估的CSS模型可能是一种预测手术患者预后的可行方法，支持外科医生对手术患者和患者的决策可以提出“等待和观察”的方法。