We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App




AI Algorithm Combined With Blood Test Quickly and Accurately Diagnoses Heart Attacks in Women

By HospiMedica International staff writers
Posted on 05 Sep 2022
Print article
Image: Artificial intelligence could help narrow heart attack gender gap (Photo courtesy of Unsplash)
Image: Artificial intelligence could help narrow heart attack gender gap (Photo courtesy of Unsplash)

Previous research has shown that women in the UK who have a heart attack receive poorer care than men at every stage. Women were 50% more likely to receive a wrong initial diagnosis, highlighting the need for innovations to help close the heart attack gender gap. Measuring the protein troponin in the blood is the current gold standard for diagnosing a heart attack. However, the levels of troponin released by the heart vary between men and women, with age and other health conditions. Current guidelines use the same threshold for all patients, meaning current tests are not as accurate as they could be. Now, an algorithm developed using artificial intelligence (AI) could help doctors to diagnose heart attacks in women more accurately and quicker than ever before.

Researchers at the University of Edinburgh (Edinburgh, Scotland) combined data from 10,038 people (48% women) who went to hospital with a suspected heart attack to develop an AI-based tool to help clinicians diagnose heart attacks more accurately. They then validated it on a further 3,035 people (31% women) outside of the UK. The tool, called CoDE-ACS, uses AI to combine routinely collected patient information when they arrive at hospital (including sex, age, observations, ECG findings and medical history) with the results from the troponin blood test. This then produces a score of 0 to 100.

The team found that CoDE-ACS was able to rule out a heart attack with 99.5% accuracy, confirming they were safe to go home. It also identified those who would benefit from staying in hospital for further tests, in whom the final diagnosis was a heart attack, with an accuracy of 83.7%. This compares to an accuracy of just 49.4% with current tests. Fewer than half of those identified for further testing using current approaches had a diagnosis of heart attack. The performance of the tool was consistent regardless of sex, age and pre-existing health conditions. Current tests mean that some patients’ troponin levels do not fit into the ‘rule in’ or ‘rule out’ thresholds, making clinical decisions more challenging. However, with a second troponin measurement, CoDE-ACS was able refine risk in the 29.5% of people who did not fit the simple ‘rule in’ or ‘rule out’ criteria allowing accurate determination if further action was needed.

“This is a huge step forward which promises to ensure everyone is on a level playing field when it comes to heart attack diagnosis and treatment,” said Professor James Leiper, our Associate Medical Director. “We know that women are more likely to receive a misdiagnosis, but by harnessing the power of AI, this team could provide one solution that helps to make that an issue of the past.”

“We’ve now embedded our algorithm into an easy-to-use mobile app to support doctors in guiding treatment decisions,” said Dimitrios Doudesis, data scientist at the BHF Centre for Cardiovascular Science, University of Edinburgh. “Whilst the troponin test takes 30 minutes to process, we take an array of other health information and add it into the app alongside the troponin measurement. This provides doctors with a precise and instantaneous score to confirm if they can reassure their patient that they haven’t had a heart attack and send them home, or if they require further tests.”

Related Links:
University of Edinburgh

Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Silver Member
Compact 14-Day Uninterrupted Holter ECG
NR-314P
New
Self-Driving Mobile C-arm
CIARTIC Move

Print article

Channels

Critical Care

view channel
Image: The permeable wearable electronics developed for long-term biosignal monitoring (Photo courtesy of CityUHK)

Super Permeable Wearable Electronics Enable Long-Term Biosignal Monitoring

Wearable electronics have become integral to enhancing health and fitness by offering continuous tracking of physiological signals over extended periods. This monitoring is crucial for understanding an... Read more

Surgical Techniques

view channel
Image: NTT and Olympus have begun the world\'s first joint demonstration experiment of a cloud endoscopy system (Photo courtesy of Olympus)

Cloud Endoscopy System Enables Real-Time Image Processing on the Cloud

Endoscopes, which are flexible tubes inserted into the body's natural openings for internal examination and biopsy collection, are becoming increasingly vital in medical diagnostics. Their minimal invasiveness... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The PATHFAST hs-cTnI-II high-sensitivity troponin assay has been developed for the PATHFAST Biomarker Analyzer (Photo courtesy of Polymedco)

POC Myocardial Infarction Test Delivers Results in 17 Minutes

Chest pain is the second leading cause of emergency department (ED) visits by adults in the United States, generating over 7 million visits annually. In the event of a suspected heart attack, physicians... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.