Transforming Research and Clinical Knowledge in Spinal Cord Injury

Spinal cord injury (SCI) is a major cause of morbidity worldwide with debilitating impacts on quality of life and the healthcare system. To date, a data-dense research registry specific to SCI remains to be constructed. To this end, the study will collect SCI data across five primary domains: 1) demographics and baseline history, 2) clinical course variables from the emergency department (ED) to the intensive care unit (ICU), 3) standard of care neuroimaging (CT and MRI) and intraoperative neuromonitoring, 4) blood and cerebrospinal fluid (CSF) samples for proteomic and genetic biomarkers, and 5) outcome measures of functional disability, mental health and quality of life at 3, 6, and 12 months. The investigators seek to correlate these high-density physiology data with baseline risk factors, imaging parameters, and biomarkers for a comprehensive approach to SCI diagnosis during acute care as well as prognosis across subacute and chronic phases of recovery -- in order to truly step toward the advancement of research and clinical knowledge in SCI. The main objective is to provide a comprehensive prospective analysis of multiple variables in acute SCI that impact long-term outcomes. This is intended to provide a rich resource for asking key questions related to the optimization of treatment, and the planning and execution of pivotal clinical trials in SCI. Core Hypotheses: 1. Multiple critical care variables will be predictive of both sensorimotor and autonomic outcomes, and susceptibility to infections at discharge and 6 and 12 mos after injury. 2. Quantitative MRI indices of cord damage, and biomarkers of acute immune responses to injury will predict neurological outcomes at discharge and at 6 and 12 mos. 3. The multivariate analysis of the constellation of acute variables and long-term outcome measures will yield new derived predictors of outcome that will facilitate stratification for clinical trials. Specific Aims: Aim 1. Diagnosis: Building a knowledge network for acute SCI. A detailed prospective study of critical care practices and outcomes for SCI patients admitted to TRACK-SCI sites will be conducted to build a knowledge network for acute SCI diagnostics. Aim 2. Prognosis: Predictive models and biomarkers. The research team will develop multidimensional prognostic indicators for predicting outcomes and stratifying patients using detailed physiological, imaging, and genetic datasets. Aim 3: Data analysis and sharing. The development of better predictors of outcome and methods for stratification will be advanced by allowing qualified access to our granular data. The availability to qualified users of the detailed acute 'diagnostic' dataset along with gene-expression data and functional outcomes at 6\&12 mos will leverage the project as a valuable international SCI community resource.