AI could close gaps in care for women with heart attacks

AI could close gaps in care for women with heart attacks

Researchers have developed a new risk score based on artificial intelligence that improves personalized care for heart attack patients.

Heart attacks are one of the leading causes of death worldwide, and women who experience a heart attack have a higher mortality rate than men. This has worried cardiologists for decades and led to controversy in the medical field about the causes and effects of potential treatment gaps.

The problem starts with the symptoms: unlike men, who usually experience chest pain radiating to the left arm, heart attacks in women often present as abdominal pain radiating to the back or as nausea and vomiting.

Unfortunately, these symptoms are often misinterpreted by patients and medical staff – with disastrous consequences.

Scientists led by Thomas F. Lüscher, professor at the Center for Molecular Cardiology at the University of Zurich, have now investigated the role of biological sex in heart attack in more detail.

“In fact, there are marked differences in the disease phenotype observed in males and females. Our study shows that women and men differ significantly in the profile of risk factors at hospital admission,” says Lüscher. When age differences at admission and existing risk factors such as hypertension and diabetes are not taken into account, women have a higher death rate after heart attack than men.

“However, when these differences are taken into account statistically, women and men have similar mortality rates,” adds Lüscher.

In their study, the researchers analyzed data from 420,781 patients from across Europe who had suffered the most common type of heart attack.

“The study shows that established risk models that guide current patient management are less accurate in women and favor undertreatment of female patients,” says first author Florian A. Wenzl of the Center for Molecular Medicine.

“Using a machine learning algorithm and the largest datasets in Europe, we were able to develop a new AI-based risk score that takes into account gender-related differences in the underlying risk profile and improves the prediction of mortality in both sexes,” Wenzl says.

Many researchers and biotech companies agree that artificial intelligence and big data analytics are the next step on the road to personalized patient care.

“Our study heralds the era of artificial intelligence in the treatment of heart attacks,” says Wenzl.

Modern computer algorithms can learn from large data sets and make accurate predictions about the prognosis of individual patients – the key to personalized treatment.

Lüscher and his team see huge potential in applying artificial intelligence to the management of heart disease in both male and female patients.

“I hope that the implementation of this new score into treatment algorithms will improve current treatment strategies, reduce gender disparities and ultimately improve the survival of heart attack patients – both men and women,” says Lüscher.

This article was originally published in Futurity. It has been republished under an Attribution 4.0 International License.

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