Department of Surgery, Division of Neurosurgery and Spinal Program, University of Toronto, Toronto Western Hospital, Toronto, Ontario, Canada.
J Neurotrauma. 2012 Sep;29(13):2263-71. doi: 10.1089/neu.2012.2417. Epub 2012 Jul 31.
To improve clinicians' ability to predict outcome after spinal cord injury (SCI) and to help classify patients within clinical trials, we have created a novel prediction model relating acute clinical and imaging information to functional outcome at 1 year. Data were obtained from two large prospective SCI datasets. Functional independence measure (FIM) motor score at 1 year follow-up was the primary outcome, and functional independence (score ≥ 6 for each FIM motor item) was the secondary outcome. A linear regression model was created with the primary outcome modeled relative to clinical and imaging predictors obtained within 3 days of injury. A logistic model was then created using the dichotomized secondary outcome and the same predictor variables. Model validation was performed using a bootstrap resampling procedure. Of 729 patients, 376 met the inclusion criteria. The mean FIM motor score at 1 year was 62.9 (±28.6). Better functional status was predicted by less severe initial American Spinal Injury Association (ASIA) Impairment Scale grade, and by an ASIA motor score >50 at admission. In contrast, older age and magnetic resonance imaging (MRI) signal characteristics consistent with spinal cord edema or hemorrhage predicted worse functional outcome. The linear model predicting FIM motor score demonstrated an R-square of 0.52 in the original dataset, and 0.52 (95% CI 0.52,0.53) across the 200 bootstraps. Functional independence was achieved by 148 patients (39.4%). For the logistic model, the area under the curve was 0.93 in the original dataset, and 0.92 (95% CI 0.92,0.93) across the bootstraps, indicating excellent predictive discrimination. These models will have important clinical impact to guide decision making and to counsel patients and families.
为了提高临床医生预测脊髓损伤（SCI）后结果的能力，并帮助在临床试验中对患者进行分类，我们创建了一个新的预测模型，将急性临床和影像学信息与 1 年时的功能结果相关联。数据来自两个大型前瞻性 SCI 数据集。1 年随访时的功能独立性测量（FIM）运动评分是主要结局，功能独立性（每个 FIM 运动项目得分≥6）是次要结局。使用线性回归模型，将主要结局相对于损伤后 3 天内获得的临床和影像学预测因素进行建模。然后使用二分类次要结局和相同的预测变量创建逻辑模型。使用自举重采样程序进行模型验证。在 729 名患者中，有 376 名符合纳入标准。1 年时的平均 FIM 运动评分是 62.9（±28.6）。初始美国脊髓损伤协会（ASIA）损伤量表分级较轻，入院时 ASIA 运动评分＞50 预测功能状态较好。相比之下，年龄较大和磁共振成像（MRI）信号特征与脊髓水肿或出血一致，预测功能结果较差。预测 FIM 运动评分的线性模型在原始数据集中的 R 平方为 0.52，在 200 次自举中为 0.52（95%CI 0.52,0.53）。148 名患者（39.4%）实现了功能独立。对于逻辑模型，原始数据集中的曲线下面积为 0.93，自举中为 0.92（95%CI 0.92,0.93），表明具有出色的预测区分能力。这些模型将对指导决策以及为患者和家属提供咨询具有重要的临床影响。
