Surgical procedure. Image by Pfree2014 – Own work, CC BY-SA 4.0
Traumatic spinal cord injury often requires intensive care and is characterised by variable clinical presentations and recovery trajectories, complicating diagnosis and prognosis, especially in emergency departments and intensive care units.
Prediction of injury severity in the first days is clinically relevant for decision-making, yet it is a challenging task through standard neurological assessment alone (being limited by limited by dependence on patient responsiveness and the presence of comorbid injuries).
A new study shows routine blood samples may give doctors early insights into injury severity and patient survival after spinal cord damage. This can occur through by utilising advances with artificial intelligence.
AI-powered analysis of routine blood tests can reveal hidden patterns can also predict recovery after spinal cord injuries. This breakthrough could make life-saving predictions affordable and accessible in hospitals worldwide.
Researchers from the University of Waterloo, Canada utilized advanced analytics and machine learning, a type of artificial intelligence, to assess whether routine blood tests could serve as early warning signs for spinal cord injury patient outcomes.
The Canadian researchers sampled hospital data from more than 2,600 patients in the U.S. They used machine learning to analyse millions of data points and discover hidden patterns in common blood measurements, such as electrolytes and immune cells, taken during the first three weeks after a spinal cord injury.
The scientists found that these patterns could help forecast recovery and injury severity, even without early neurological exams, which are not always reliable as they depend on a patient’s responsiveness.
The models were found to be accurate in predicting mortality and the severity of injury as early as one to three days after admission to the hospital, compared to standard non-specific severity measures that are often performed during the first day of arrival to intensive care.
The research additionally found that accuracy increased over time as more blood tests became available. Although other measures, such as MRI and fluid omics-based biomarkers, can also provide objective data, they are not always readily accessible across medical settings. Routine blood tests, on the other hand, are economical, easy to obtain, and available in every hospital.
The researchers hope this foundational work can open new possibilities in clinical practice, allowing for better-informed decisions about treatment priorities and resource allocation in critical care settings for many physical injuries.
The research appears in the journal npj Digital Medicine, titled “Modeling trajectories of routine blood tests as dynamic biomarkers for outcome in spinal cord injury.”