中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2019, Vol. 14 ›› Issue (4): 713-720.doi: 10.4103/1673-5374.247480

• 原著:脊髓损伤修复保护与再生 • 上一篇    下一篇

无骨折脱位型颈脊髓损伤预后模型的建立与验证

  

  • 出版日期:2019-04-15 发布日期:2019-04-15
  • 基金资助:

    中国国家自然科学基金项目（30672136）

Establishment and verification of a surgical prognostic model for cervical spinal cord injury without radiological abnormality

Jie Wang 1 , Shuai Guo 1 , Xuan Cai 1 , Jia-Wei Xu 1 , Hao-Peng Li 1, 2   

  1. 1 Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
    2 Health Science Center, Xi’an Jiaotong University, Xi’an, Shaanxi Province, China
  • Online:2019-04-15 Published:2019-04-15
  • Contact: Hao-Peng Li, MD, lhp-3993@163.com.
  • Supported by:

    This study was supported by the National Natural Science Foundation of China, No. 30672136 (to HPL).

PDF

206

摘要：

有研究认为尽早地进行手术治疗可以有效地改善无骨折脱位型颈脊髓损伤的预后，但目前缺少无骨折脱位型颈脊髓损伤预后模型的研究。此次回顾性分析纳入了43例无骨折脱位型颈脊髓损伤患者，收集患者年龄、性别、引起损伤的外力强度、疾病持续时间、颈椎管狭窄程度、JOA评分和生理性颈椎曲度共7项潜在因素，使用多因素二元逻辑回归分析建立模型，以一致性分析和特征曲线下面积评估模型，使用Bootstrapping法进行验证。试验结果的预后模型为logit（P）= - 25.4545 + 21.2576VALUE + 1.2160SCORE-3.4224TIME，其中VALUE指Pavlov比率，表明颈椎管狭窄程度，SCORE指术后JOA评分，TIME指病程。所有参与者的特征曲线下面积为0.8941（95％CI：0.7930-0.9952）。模型中评估的3个因素与患者预后相关：严重的颈椎管狭窄、较差的术前神经状态以及较长病程，都可使患者预后恶化；而当logit（P）≥-2.5105时，预后良好。结果提示此种无骨折脱位型颈脊髓损伤预后模型具有一定的临床价值。试验于2018-5-8经西安交通大学第二附属医院医学伦理委员会批准，批准号：2018063。

orcid: 0000-0002-2162-6358(Hao-Peng Li)

关键词: 手术预后模型, 无骨折脱位型颈脊髓损伤, 回顾性研究, 多因素二元Logistic回归分析, Bootstrapping算法, 验证, 多重填补法, 颈椎管狭窄, 病程, Pavlov比率

Abstract:

Some studies have suggested that early surgical treatment can effectively improve the prognosis of cervical spinal cord injury without radiological abnormality, but no research has focused on the development of a prognostic model of cervical spinal cord injury without radiological abnormality. This retrospective analysis included 43 patients with cervical spinal cord injury without radiological abnormal¬ity. Seven potential factors were assessed: age, sex, external force strength causing damage, duration of disease, degree of cervical spinal stenosis, Japanese Orthopaedic Association score, and physiological cervical curvature. A model was established using multiple binary lo¬gistic regression analysis. The model was evaluated by concordant profiling and the area under the receiver operating characteristic curve. Bootstrapping was used for internal validation. The prognostic model was as follows: logit(P) = −25.4545 + 21.2576VALUE + 1.2160SCORE − 3.4224TIME, where VALUE refers to the Pavlov ratio indicating the extent of cervical spinal stenosis, SCORE refers to the Japanese Or-thopaedic Association score (0–17) after the operation, and TIME refers to the disease duration (from injury to operation). The area under the receiver operating characteristic curve for all patients was 0.8941 (95% confidence interval, 0.7930–0.9952). Three factors assessed in the predictive model were associated with patient outcomes: a great extent of cervical stenosis, a poor preoperative neurological status, and a long disease duration. These three factors could worsen patient outcomes. Moreover, the disease prognosis was considered good when logit(P) ≥ −2.5105. Overall, the model displayed a certain clinical value. This study was approved by the Biomedical Ethics Committee of the Second Affiliated Hospital of Xi’an Jiaotong University, China (approval number: 2018063) on May 8, 2018.

Key words: nerve regeneration, surgical prognostic model, cervical spinal cord injury, retrospective study, multiple binary logistic regression analysis, bootstrapping, internal validation, multiple imputations, cervical spinal stenosis, duration of disease, Pavlov ratio, neural regeneration