Authors

Jefferson R Wilson, Department of Surgery, University of Toronto, Toronto Western Hospital
Robert G Grossman, Department of Neurosurgery, University of Texas Medical School, Houston Methodist Hospital
Ralph F Frankowski, School of Public Health, University of Texas
Alexander Kiss, Department of Research Design and Biostatistics, University of Toronto, Toronto Western Hospital
Aileen M Davis, Department of Health Policy, Management and Evaluation, University of Toronto, Toronto Western Hospital
Abhaya V Kulkarni, Department of Surgery, University of Toronto, Toronto Western Hospital; Department of Health Policy, Management and Evaluation, University of Toronto, Toronto Western Hospital
James S Harrop, Department of Neurosurgery and Orthopedic Surgery, Division of Spinal Disorders, Thomas Jefferson UniversityFollow
Bizhan Aarabi, Department of Neurosurgery, University of Maryland
Alexander Vaccaro, Department of Neurosurgery and Orthopedic Surgery, Division of Spinal Disorders, Thomas Jefferson UniversityFollow
Charles H Tator, Department of Surgery, University of Toronto, Toronto Western Hospital
Marcel Dvorak, Department of Orthopedic Surgery, University of British Columbia
Christopher I Shaffrey, Departments of Neurosurgery and Orthopedic Surgery, University of Virginia
Susan Harkema, Department of Neurosurgery, University of Kentucky
James D Guest, Department of Neurosurgery and Miami Project to Cure Paralysis, University of Miami
Michael G Fehlings, Department of Surgery, University of Toronto, Toronto Western Hospital

Document Type

Article

Publication Date

9-1-2012

Comments

This article has been peer reviewed and is published in Journal of Neurotrauma.

Volume 29, Issue 13, 1 September 2012, Pages 2263-2271.

The published version is available at DOI: 10.1089/neu.2012.2417.

© Copyright 2012, Mary Ann Liebert, Inc. 2012.

Abstract

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.

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