- New research found Abbott's algorithm created through machine
learning could give doctors a more individualized calculation,
leveraging factors such as age, sex and the changing dynamics of
troponin protein levels in the blood, to improve heart attack
diagnosis
- This technology is the first machine learning developed
algorithm that combines high sensitive troponin testing with other
patient details to help doctors better determine if a heart attack
is occurring
ABBOTT PARK, Illinois, Sept. 10,
2019 /PRNewswire/ -- Abbott (NYSE: ABT) announced today
that new research, published in the journal Circulation, found its
algorithm could help doctors in hospital emergency rooms more
accurately determine if someone is having a heart attack or not, so
that they can receive faster treatments or be safely
discharged.1
In this study, researchers from the U.S., Germany, U.K., Switzerland, Australia and New
Zealand looked at more than 11,000 patients to determine if
Abbott's technology developed using artificial intelligence (AI)
could provide a faster, more accurate determination that someone is
having a heart attack or not. The study found that the algorithm
provided doctors a more comprehensive analysis of the probability
that a patient was having a heart attack or not, particularly for
those who entered the hospital within the first three hours of when
their symptoms started.
"With machine learning technology, you can go from a
one-size-fits-all approach for diagnosing heart attacks to an
individualized and more precise risk assessment that looks at how
all the variables interact at that moment in time," said
Fred Apple, Ph.D., Hennepin
HealthCare/ Hennepin County Medical Center, professor of Laboratory
Medicine and Pathology at the University of
Minnesota, and one of the study authors. "This could give
doctors in the ER more personalized, timely and accurate
information to determine if their patient is having a heart attack
or not."
Removing the barriers for determining the presence of a heart
attack
A team of physicians and statisticians at Abbott developed the
algorithm* using AI tools to analyze extensive data sets and
identify the variables most predictive for determining a cardiac
event, such as age, sex and a person's specific troponin levels
(using a high sensitivity troponin-I blood test**) and blood sample
timing.
Today, when a person enters the emergency room with symptoms of
a heart attack, doctors often use a clinical assessment, an
electrocardiogram (EKG) and troponin blood tests at set intervals
to determine if the patient is having a heart attack or not. The
algorithm is designed to help address two barriers that exist today
for doctors looking for more individualized information when
diagnosing heart attacks:
- International guidelines for using high sensitive troponin
tests currently do not always account for personal factors, such as
age and sex, which could impact test results. For instance, women
may not produce as much of the troponin protein as men and their
heart attacks could go undiagnosed.
- The guidelines also recommend that doctors carry out troponin
testing at fixed times over a period of up to 12 hours. However,
these time periods do not take into consideration a person's age or
sex, and puts a patient into a one-size-fits-all algorithm, rather
than having an algorithm that accounts for factors specific to each
person.
The algorithm used in the study takes into consideration the
patient's age, sex and the dynamics of the troponin blood test
results over time. Researchers found that when this information is
combined through the power of computation, the algorithm has the
potential to give doctors more confidence in the results to help
rule out a heart attack and safely discharge that person or
diagnose that a heart attack has occurred.
"As doctors are bombarded with data and information, this new
algorithm takes several of these variables and uses computational
power to more accurately provide a probability of that person
having a heart attack," said Agim
Beshiri, M.D., one of the inventors of the algorithm and
senior medical director, global medical and scientific affairs,
Diagnostics, Abbott. "In the future, you could imagine using this
technology to develop algorithms that help doctors not only better
determine if their patient is having a heart attack or not, but
potentially before a heart attack occurs."
Abbott is continuously utilizing new technologies, such as AI
and machine learning, to create innovative solutions in
healthcare.
* The algorithm used is for research purposes only and is not
commercially available.
** Abbott's High Sensitive Troponin-I test is not commercially
available in the U.S.
About Abbott:
Abbott is a global healthcare leader that helps people live more
fully at all stages of life. Our portfolio of life-changing
technologies spans the spectrum of healthcare, with leading
businesses and products in diagnostics, medical devices,
nutritionals and branded generic medicines. Our 103,000 colleagues
serve people in more than 160 countries.
Connect with us at www.abbott.com, on LinkedIn at
www.linkedin.com/company/abbott-/, on Facebook
at www.facebook.com/Abbott and on Twitter @AbbottNews and
@AbbottGlobal.
References:
- Than, MP et al. Circulation. 2019; published
online Sept 10.
https://doi.org/10.1161/CIRCULATIONAHA.119.041980