New Delhi, April 23 (IANS) As cardiovascular disease in women remain underdiagnosed compared to men, new machine learning models that use sex-specific criteria may help overcome this as well as boost treatment outcomes, according to a study.
Although anatomical differences exist between male and female hearts as women have smaller hearts with thinner walls, yet, the diagnostic criteria for certain heart diseases have been the same for both.
“This means that women’s hearts must increase disproportionately more than men’s before the same risk criteria are met,” argued the researchers in the paper published in the journal Frontiers in Physiology.
They said this sex-neutral approach leads to severe underdiagnosis of women, especially during “first-degree atrioventricular block (AV) block, a disorder affecting the heartbeat, and dilated cardiomyopathy, a heart muscle disease, twice and 1.4 times more than men, respectively.”
“We found that that sex-neutral criteria fail to diagnose women adequately. If sex-specific criteria were used, this underdiagnosis would be less severe,” said Skyler St Pierre, a researcher at Stanford University’s Living Matter Lab, US.
“We also found the best exam to improve detection of cardiovascular disease in both men and women is the electrocardiogram (EKG),” he added.
To build more accurate heart risk models based on sex-specific criteria, the team added four metrics not considered in the popular Framingham Risk Score – cardiac magnetic resonance imaging, pulse wave analysis, EKGs, and carotid ultrasounds.
The Framingham Risk Score is a popular system to diagnose heart risks based on age, sex, cholesterol levels, and blood pressure. The diagnostic system can estimate how likely a person is to develop a heart disease within the next 10 years.
The team used data from more than 20,000 individuals in the UK Biobank who had undergone these tests.
Using machine learning, the researchers determined that of the tested metrics, EKGs were most effective at improving the detection of cardiovascular disease in both men and women. This, however, does not mean that traditional risk factors are not important tools for risk assessment, the researchers said.
“We propose that clinicians first screen people using a simple survey with traditional risk factors, and then do a second stage screening using EKGs for higher risk patients,” they added.
–IANS
rvt/sd/kvd
Disclaimer
The information contained in this website is for general information purposes only. The information is provided by TodayIndia.news and while we endeavour to keep the information up to date and correct, we make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability or availability with respect to the website or the information, products, services, or related graphics contained on the website for any purpose. Any reliance you place on such information is therefore strictly at your own risk.
In no event will we be liable for any loss or damage including without limitation, indirect or consequential loss or damage, or any loss or damage whatsoever arising from loss of data or profits arising out of, or in connection with, the use of this website.
Through this website you are able to link to other websites which are not under the control of TodayIndia.news We have no control over the nature, content and availability of those sites. The inclusion of any links does not necessarily imply a recommendation or endorse the views expressed within them.
Every effort is made to keep the website up and running smoothly. However, TodayIndia.news takes no responsibility for, and will not be liable for, the website being temporarily unavailable due to technical issues beyond our control.
For any legal details or query please visit original source link given with news or click on Go to Source.
Our translation service aims to offer the most accurate translation possible and we rarely experience any issues with news post. However, as the translation is carried out by third part tool there is a possibility for error to cause the occasional inaccuracy. We therefore require you to accept this disclaimer before confirming any translation news with us.
If you are not willing to accept this disclaimer then we recommend reading news post in its original language.
