Heart attacks are much less common in women than in men. An AI-based risk score could help doctors in the future to avoid this undertreatment of female patients.
Heart attacks are one of the leading causes of death worldwide, and women who suffer a heart attack have a higher mortality rate than men. This has worried cardiologists for decades and has sparked controversy in the medical community about the causes and implications of potential treatment gaps. The problem starts with the symptoms: Unlike men, who usually feel chest pain radiating to the left arm, a heart attack in women often manifests itself as abdominal pain radiating to the back or as nausea and vomiting. Unfortunately, these symptoms are often misinterpreted by patients and medical staff – with fatal consequences.
Risk profile and clinical picture in women
An international research team led by Thomas F. Lüscher, Professor at the Center for Molecular Cardiology at the University of Zurich (UZH), has now examined the role of biological sex in heart attacks in more detail. “Indeed, there are striking differences in the disease phenotype of women and men. Our study shows that women and men differ significantly in terms of their risk factor profile when they are admitted to hospital,” says Lüscher.
Adjusting for age differences at admission and existing risk factors such as high blood pressure and diabetes, female heart attack patients have a higher mortality rate than male patients. “However, if these differences are taken into account statistically, women and men have a similar mortality rate,” adds the cardiologist.
Risk models favor undertreatment of patients
In their study, published in the prestigious journal The Lancet was published, researchers from Switzerland and the UK analyzed data from 420,781 patients across Europe who had suffered the most common type of heart attack. “The study shows that established risk models, which guide current patient management, are less accurate in women and encourage undertreatment of patients,” says lead author Florian A. Wenzl from the Center for Molecular Medicine at UZH.
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“Using a machine learning algorithm and the largest data sets in Europe, we were able to develop a novel, artificial intelligence-based risk score that takes into account gender-specific differences in the initial risk profile and improves the prediction of mortality in both sexes,” says Wenzl.
AI-based risk profiles improve care
Many researchers and biotech companies agree that artificial intelligence and big data analytics are the next step towards 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 to make accurate predictions about the prognosis of individual patients – the key to individualized treatments.
Thomas F. Lüscher and his team see great potential in the use of artificial intelligence for the management of heart disease in both male and female patients. “I hope that the implementation of this novel score in treatment algorithms will refine current treatment strategies, reduce gender inequalities, and ultimately improve the survival of heart attack patients – both males and females,” says Lüscher.
This article is based on a press release from the University of Zurich. You can find the study here and linked in the text.
Image source: Towfiqu barbhuiya, unsplash
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