Hypnotomous intelligence finds lifestyle visions in daily blood

The research team used advanced analyzes and machine learning, a type of artificial intelligence, to assess whether routine blood tests could serve as early warning signs of the results of spinal cord injury.

More than 20 million people around the world were affected by the spinal cord injury in 2019, with 930,000 new cases each year, according to the World Health Organization. Painful spinal cord injury often requires intensive care and is characterized by changing clinical performances and recovery paths, which complicates diagnosis and diagnosis, especially in emergency departments and intensive care units.

“Routine blood tests can provide important information and affordable prices to help predict the risk of death, the presence of injury and the severity of the matter,” said Dr. Abel Torres Espin, a professor at Waterllo College of Public Sciences in Public Health Sciences.

The researchers took samples of hospital data from more than 2,600 patients in the United States, who used machine learning to analyze millions of data points and discover hidden patterns in common blood blood measurements, such as electrolytes and immune cells, which are taken during the first three weeks after the spinal cord injury.

They found that these patterns can help predict the freshness and severity of the injury, even without early nervous tests, which cannot always be relied upon because they depend on the patient’s response.

“While a single vital sign is measured at one point can have a predictive power, the broader story lies in many vital indicators and changes that show it over time,” said Dr. Marzier Mossafi Rizi, a post -PhD researcher at the Torres Espino Laboratory in Waterlo.

The models, which are not dependent on early nervous evaluation, were accurate in predicting deaths and the severity of the injury early in three days after accepting the hospital, compared to unlimited severity measures that are often implemented during the first day of reaching intensive care.

The research also found that the accuracy increased over time with more blood tests. Although other measures, such as MRI and OMics -based vital signs, can also provide objective data, they cannot always be accessible through medical settings. Routine blood tests, on the other hand, are economic, easy to obtain and available in each hospital.

Torres Esbin said: “The severe prediction in the first days is clinically related to making decisions, yet it is a difficult task through nervous evaluation alone.” “We show the ability to predict whether the infection is a full or incomplete motor with routine blood data early after the injury, and increased prediction performance with time.

“This founding work can open new possibilities in clinical practice, allowing better decisions on treatment priorities and allocating resources in critical care places for many physical injuries.”

The study was published, routine blood testing paths as dynamic vital signs of results in spinal cord injury, in nature Digital medicine npj magazine.