AI Improves Treatment in Women with Heart Attacks

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 been a matter of concern to cardiologists for decades and has led to controversy in the medical field about the causes and effects of possible gaps in treatment. The problem starts with the symptoms: unlike men, who usually experience chest pain with radiation to the left arm, a heart attack in women often manifests as abdominal pain radiating to the back or as nausea and vomiting. These symptoms are unfortunately often misinterpreted by the patients and healthcare personnel - with disastrous consequences.

Risk profile and clinical picture is different 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 investigated the role of biological sex in heart attacks in more detail. "Indeed, there are notable differences in the disease phenotype observed in females and males. Our study shows that women and men differ significantly in their risk factor profile at hospital admission,” says Lüscher. When age differences at admission and existing risk factors such as hypertension and diabetes are disregarded, female heart-attack patients have higher mortality than male patients. “However, when these differences are taken into account statistically, women and men have similar mortality," the cardiologist adds.

Current risk models favor under-treatment of female patients

In their study, published in the prestigious journal The Lancet, researchers from Switzerland and the United Kingdom 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 females and favor the undertreatment of female patients," says first author Florian A. Wenzl of the Center for Molecular Medicine at UZH. "Using a machine learning algorithm and the largest datasets in Europe we were able to develop a novel artificial- intelligence-based risk score which accounts for sex-related differences in the baseline risk profile and improves the prediction of mortality in both sexes," Wenzl says.

AI-based risk profiling improves individualized care

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 to make accurate predictions about the prognosis of individual patients - the key to individualized treatments.

Thomas F. Lüscher and his team see huge potential in the application of artificial intelligence for the management of heart disease both in male and female patients. "I hope the implementation of this novel score in treatment algorithms will refine current treatment strategies, reduce sex inequalities, and eventually improve the survival of patients with heart attacks - both male and female," says Lüscher.

Florian A Wenzl, Simon Kraler, Gareth Ambler, Clive Weston, Sereina A Herzog, Lorenz Räber, Olivier Muller, Giovanni G Camici, Marco Roffi, Hans Rickli, Keith A A Fox, Mark de Belder, Dragana Radovanovic, John Deanfield, Thomas F Lüscher.
Sex-specific evaluation and redevelopment of the GRACE score in non-ST-segment elevation acute coronary syndromes in populations from the UK and Switzerland: a multinational analysis with external cohort validation.
The Lancet, 2022. doi: 10.1016/S0140-6736(22)01483-0

Most Popular Now

ANregiomed Puts Siemens Healthineers and…

This new technology partnership kicked off September 1, 2022, marks the first time that Siemens Healthineers is collaborating with a municipal medical service provider to implement a concept it has...

Consortium to Develop Fully Implantable …

A research consortium led by the UMC Utrecht Brain Center (the Netherlands) in collaboration with Graz University of Technology (Austria), the Wyss Center for Bio and Neuroengineering (Switzerland) and CorTec...

AI Model Outperforms Clinicians in Diagn…

An artificial-intelligence (AI) model built at Mass Eye and Ear was shown to be significantly more accurate than doctors at diagnosing pediatric ear infections in the first head-to-head evaluation of...

Creating the Digital Health Workforce of…

How are trusts and health tech suppliers going to find the people they need to develop deploy and optimise critical clinical information systems in the future? Highland Marketing's advisory board...

Philips Foundation and RAD-AID Internati…

Philips Foundation, with its mission to provide access to quality healthcare for 100 million people a year in underserved communities by 2030, together with Philips and RAD-AID International, today announced...

New Tool Overcomes Major Hurdle in Clini…

Harvard Medical School scientists and colleagues at Stanford University have developed an artificial intelligence (AI) diagnostic tool that can detect diseases on chest X-rays directly from natural-language descriptions contained in...

AI Tool could Reduce Common Drug Side Ef…

Research led by the University of Exeter and Kent and Medway NHS and Social Care Partnership Trust, published in Age and Ageing, assessed a new tool designed to calculate which...

CHOP Study Explores the Use of Telemedic…

Researchers from the Epilepsy Neurogenetics Initiative (ENGIN) at Children's Hospital of Philadelphia (CHOP) found that across nearly 50,000 visits, patients continued to use telemedicine effectively even with the reopening of...

A Smartphone's Camera and Flash could He…

First, pause and take a deep breath. When we breathe in, our lungs fill with oxygen, which is distributed to our red blood cells for transportation throughout our bodies. Our bodies...

Users Trust AI as Much as Humans for Fla…

Social media users may trust artificial intelligence (AI) as much as human editors to flag hate speech and harmful content, according to researchers at Penn State. The researchers said that...