New research shows that routine blood tests, analysed using AI, can help predict the severity and survival chances of spinal cord injuries. This low-cost method offers faster, more accurate assessments for better health care.
New research from the University of Waterloo suggests that routine blood tests could help doctors in estimating how severe spinal cord injury is and even determine a patient’s likelihood of surviving the injury. The study was published in NPJ Digital Medicine, a reputable scientific journal.
Spinal cord injuries impact millions across the globe. These injuries occur when the nerves in the spine are damaged. According to the World Health Organization, more than 20 million people worldwide were living with spinal cord injuries in 2019. These injuries usually require urgent medical care and close monitoring in hospitals. However, it is challenging for doctors to accurately determine the extent of the injury or the patient’s recovery potential.
Doctors assess spinal injuries by observing a patient’s ability to move or sense touch. However, this method relies on the patient’s level on responsiveness, which may not be reliable immediately after an injury, especially during emergencies.
Leveraging AI to Analyze Blood Tests
The research team used AI machine learning to examine routine blood test results from over 2,600 spinal injury patients in the United States. These tests measure standard blood elements such as minerals and immune cells.
By analyzing millions of data points from blood tests collected in the first three weeks following injury, the AI identified hidden patterns that can help predict the severity of the injury and the risk of mortality.
Multiple Tests Provide More Insight
Dr Marzieh Mussavi Rizi, a member of the research team, explained that while a single blood test can offer some useful information, the true value lies in tracking multiple tests over time. Changes in several blood markers together provide a more accurate picture of the patient’s condition.
The AI models were able to predict the severity of injuries. They also predicted the survival chances as early as one to three days after hospital admission. It’s quicker and sometimes more accurate than traditional assessments used in intensive care, which often only provide a general idea of injury seriousness.
Routine blood tests are low-cost, simple, and conducted in most medical facilities. This means the AI approach can be applied broadly, allowing for more effective use of blood tests already taken regularly.
A New Possibility in Clinical Care
Dr Abel Torres Espín, who led the research, emphasized that early prediction of injury severity is essential for determining treatment plans and managing hospital resources. This research introduces new ways for doctors to care for patients with spinal injuries and potentially other serious physical injuries.