New Study Shows Clinical Rule May Offer Accurate Prognosis in Spinal Cord Injuries

Sarasota, FL (WorkersCompensation.com) – According to statistics from the National Spinal Cord Injury Statistics Center (NSCISC), there are around 18,000 new traumatic spinal cord injuries per year, averaging out to 54 cases per one million people. There are approximately 299,000 people in the U.S. living with a spinal cord injury. 

Automobile accidents are the leading cause of spinal cord injuries, and falls are a close leading second. Acts of violence, primarily gunshot wounds, and sports injuries are subsequent leading causes of spine juries. The leading causes of death in patients with spine injuries according to the NSCISC data is pneumonia and septicemia.

Tetraplegia, also known as quadriplegia, is paralysis of both legs and both arms and has recently become the most frequent neurological category. Less than 1 percent of those with a traumatic spinal cord injury experience a complete neurological recovery at the time of hospital discharge, according to data from the NSCISC.

Approximately 50 percent of spinal cord injuries occur at the cervical level. The level of injury can potentially be a predictor of costs, according to NSCISC. For instance, the average cost for a high cervical injury is $1,218,106 the first year. By comparison, the first year cost for a low cervical injury averages $880,188. 

A recent study from researchers at Washington University in St. Louis, Missouri suggests that early clinical and neurological metrics within 30 days of a spinal cord injury could potentially predict upper limb functional dependency within a year after the injury. The findings may be beneficial in patient counseling, as well as management of reconstructions for tetraplegia cases. 

Researchers reviewed cases from the Spinal Cord Injury Model Systems (SCIMS) database, which captures data from around 6 to 13 percent of new spine cases since its inception in 1973. Candidates pulled in the study had undergone a neurological exam and a 1-year follow up that included motor and sensory scores from each spinal segment. Patients were limited to those that had a cervical injury to spinal levels between C1 and C8, and an American Spinal Injury Association Impairment Scale (AIS) score between A and D. 

Using the data from SCIMS, the researchers were able to create a prediction model that was able to identify patients that would eventually need reconstructive or rehabilitative interventions to regenerate upper limb function. Additionally, the model scored better than the AIS grading at predicting dependency in tetraplegic patients. The model was accurate for both low and high injuries, and performed well when evaluating both accidental and fall related spinal injuries. 

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