Infections can lead to various and multiple reactions in the human body, including sepsis, or sepsis, whose complications threaten human life. This disease causes the death of more than 11 million people around the world every year, according to World Health Organization statistics.
early warning
According to New Atlas, citing Nature Digital Medicine, a new AI system developed at Johns Hopkins University promises to make a real difference in the field, by detecting key symptoms early.
Diagnostic difficulty
Sepsis, or sepsis, is caused by an infection that triggers a severe immune response in the body. This begins with a chain of events that begins with widespread inflammation and can end with blood clots, leaking blood vessels, organ failure, or death.
Obvious symptoms such as a fever or a cold can be misinterpreted or misinterpreted as symptoms of other conditions, making the condition difficult to diagnose in its early stages.
Deterioration rate
Early diagnosis of sepsis is critical, as a patient with sepsis can rapidly deteriorate, which explains why about 30% of people with sepsis die. Some promising technologies have already emerged that aim to improve the odds in these situations by clearly and quickly detecting sepsis, with devices that pick up key biomarkers in the blood within minutes and tools to detect the pathogens behind the initial infection right away.
A different and innovative approach
The Johns Hopkins team of researchers has taken a different approach, looking to take advantage of advanced artificial intelligence to identify patients at risk. The smart system analyzes data including the patient’s medical history and combines it with current symptoms, clinical notes and laboratory results. The new technology is described as a targeted, real-time early warning system, where artificial intelligence tracks patients from the moment they enter the hospital until the moment they leave the hospital. The technology is designed to ensure that no important or potentially life-threatening medical details are missed.
high accuracy ratio
The technology has been used in five hospitals as part of a two-year trial involving more than 700,000 patients. According to the researchers, the system has proven very effective, as it led to the detection of sepsis on average about six hours before traditional methods, with a sensitivity of 82%.
promising results
Implementation of the innovative technology resulted in a significant reduction in morbidity, shorter in-hospital treatment and, most importantly, an 18.2% reduction in mortality.
Sores and breathing problems
Johns Hopkins researchers are also adapting the innovative technology for use in detecting other conditions, such as ulcers or acute respiratory failure.
“It is an extraordinary leap that will save the lives of thousands of sepsis patients annually. This approach is currently being applied to improve outcomes in other important problem areas beyond sepsis,” said Sochi Sarya, lead researcher on the study.