Researchers of the University of Zurich (Swiss) have developed a new risk score based on the artificial intelligence that improves the personalized attention of the women who have suffered a heart attack.
Heart attacks are one of the leading causes of death worldwide, and women who have a heart attack have a higher death rate than men. This has been a concern of cardiologists for decades and has sparked controversy in the medical field about the causes and effects of possible gaps in treatment.
“Our study shows that women and men differ significantly in their risk factor profile at the time of hospital admission”
The problem starts with symptom: Unlike men, who usually experience chest pain radiating to the left arm, a heart attack in women usually manifests as a abdominal pain radiating to the back or as nausea and vomiting. Unfortunately, these symptoms are often misunderstood by patients and healthcare personnel, with disastrous consequences.
This study, published in the scientific journal ‘The Lancet’, has now investigated in more detail the biological sex role in heart attacks. “Indeed, there are notable differences in the disease phenotype observed in women and men. Our study shows that women and men differ significantly in their risk factor profile at hospital admission,” he says. Thomas F. Luscherresearch leader.
If differences in age at admission and existing risk factors, such as hypertension and the diabetes, women who suffer a heart attack have a higher mortality than men. “However, when these differences are taken into account statistically, women and men have similar mortality,” adds the cardiologist.
“The study shows that the established risk models that guide the current treatment of patients are less precise in women and favor their undertreatment”
In their study, the researchers analyzed data from 420,781 patients of all Europe who had suffered the most common type of heart attack. “The study shows that the established risk models that guide the current treatment of patients are less precise in women and favor their undertreatment”, details the first author of the work, Florian A. Wenzl.
Using an algorithm of machine learning and Europe’s largest data sets, have been able to develop a new AI-based risk score that takes into account gender-related differences in the baseline risk profile and improves prediction of mortality in both sexes.
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