A Clinical Prediction Model for Long-Term Functional Outcome after Traumatic Spinal Cord Injury Based on Acute Clinical and Imaging Factors

作者:Wilson Jefferson R; Grossman Robert G; Frankowski Ralph F; Kiss Alexander; Davis Aileen M; Kulkarni Abhaya V; Harrop James S; Aarabi Bizhan; Vaccaro Alexander; Tator Charles H; Dvorak Marcel; Shaffrey Christopher I; Harkema Susan; Guest James D; Fehlings Michael G*
来源:Journal of Neurotrauma, 2012, 29(13): 2263-2271.
DOI:10.1089/neu.2012.2417

摘要

To improve clinicians%26apos; 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 %26gt;= 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 %26gt;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.

  • 出版日期2012-9