• Travis E Marion, Carly S Rivers, Dilnur Kurban, Christiana L Cheng, Nader Fallah, Juliet Batke, Marcel F Dvorak, Charles G Fisher, Brian K Kwon, Vanessa K Noonan, and John T Street.
• 1 Department of Orthopaedics, Vancouver Spine Surgery Institute, University of British Columbia , Vancouver, British Columbia, Canada .
• J. Neurotrauma. 2017 Oct 15; 34 (20): 2883-2891.

AbstractAdverse events (AEs) are common during care in patients with traumatic spinal cord injury (tSCI). Increased risk of AEs is linked to patient factors including pre-existing comorbidities. Our aim was to examine the relationships between patient factors and common post-injury AEs, and identify potentially modifiable comorbidities. Adults with tSCI admitted to a Level I acute specialized spine center between 2006 and 2014 who were enrolled in the Rick Hansen SCI Registry (RHSCIR) and had AE data collected using the Spine Adverse Events Severity system were included. Patient demographic, neurological injury, and comorbidities data were obtained from RHSCIR. Potentially modifiable comorbidities were grouped into health-related conditions, substance use/withdrawal, and psychiatric conditions. Negative binomial regression and multiple logistic regression were used to model the impact of patient factors on the number of AEs experienced and the occurrence of the five previously identified common AEs, respectively. Of the 444 patients included in the study, 24.8% reported a health-related condition, 15.3% had a substance use/withdrawal condition, 8% reported having a psychiatric condition; and 79.3% experienced one or more AEs. Older age (p = 0.004) and more severe injuries (p < 0.001) were nonmodifiable independent variables significantly associated with increased AEs. The AEs experienced by patients were urinary tract infections (42.8%), pneumonia (39.2%), neuropathic pain (31.5%), delirium (18.2%), and pressure ulcers (11.0%). Risk of delirium increased in those with substance use/withdrawal; and pneumonia risk increased with psychiatric comorbidities. Opportunity exists to develop clinical algorithms that include these types of risk factors to reduce the incidence and impact of AEs.

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