With this algorithm, which eliminates the possibility of having a heart attack in more than twice as many patients as existing methods, it is planned to prevent the intensity of the emergency services.
The new study, led by the University of Edinburgh in Scotland, shows the risk of heart attack in more than double the number of patients with 99.6 percent accuracy when compared with current testing methods.
The current gold standard for heart attack diagnosis involves measuring levels of the protein troponin in the blood. However, the same threshold value is used for each patient, meaning that factors such as age, gender, and other health conditions that affect troponin levels are not taken into account, which affects how accurate heart attack diagnoses are.
PREVENTS WRONG DIAGNOSIS
Previous research has shown that women are 50 percent more likely to get a wrong initial diagnosis, and people who are misdiagnosed have a 70 percent higher risk of dying after 30 days.
The team said that the new algorithm, called CoDE-ACS, developed using data from 10,038 patients in Scotland who came to the hospital with suspected heart attacks, is an opportunity to prevent this.
The algorithm uses routinely collected patient information such as age, gender, ECG findings and medical history, as well as troponin levels, to predict a person’s likelihood of having a heart attack.
Professor Nicholas Mills, who led the research, said: “Early diagnosis and treatment saves lives in patients suffering from acute chest pain due to a heart attack.”
