Object: While the majority of existing reports focus on complications sustained during the chronic stages after traumatic spinal cord injury (SCI), the objective in the current study was to characterize and quantify acute inpatient complications. In addition, the authors sought to create a prediction model using clinical variables documented at hospital admission to predict acute complication development.
Methods: Analyses were based on data from the Surgical Timing in Acute Spinal Cord Injury Study (STASCIS) data registry, which contains prospective information on adult patients with cervical SCIs who were enrolled at 6 North American centers over a 7-year period. All patients who underwent a standardized American Spinal Injury Association (ASIA) neurological examination within 24 hours of injury and whose follow-up information was available at the acute hospital discharge were included in the study. For purposes of classification, complications were divided into 5 major categories: 1) cardiopulmonary, 2) surgical, 3) thrombotic, 4) infectious, and 5) decubitus ulcer development. Univariate statistical analyses were performed to determine the relationship between complication occurrence and individual demographic, injury, and treatment variables. Multivariate logistic regression was subsequently performed to create a complication prediction model. Model discrimination was judged according to the area under the receiver operating characteristic curve.
Results: Complete complication information was available for 411 patients at the acute care discharge. One hundred sixty patients (38.9%) experienced 240 complications. The mean age among those who experienced at least one complication was 45.9 years, as compared with 43.5 years among those who did not have a complication (p = 0.18). In the univariate analysis, patients with complications were less likely to receive steroids at admission (p = 0.01), had a greater severity of neurological injury as indicated by the ASIA Impairment Scale (AIS) grade at presentation (p < 0.01), and a higher frequency of significant comorbidity (p = 0.04). In a multivariate logistic regression model, a severe initial AIS grade (p < 0.01), a high-energy injury mechanism (p = 0.07), an older age (p = 0.05), the absence of steroid administration (p = 0.02), and the presence of comorbid illness (p = 0.02) were associated with a greater likelihood of complication development during the period of acute hospitalization. The area under the curve value for the full model was 0.75, indicating acceptable predictive discrimination.
Conclusions: These results will help clinicians to identify patients with cervical SCIs at greatest risk for complication development and thus allowing for the institution of aggressive complication prevention measures.