Scientists Develop a Software Tool for Estimating Heart Disease Risk

University of Granada researchers have developed a software tool that makes an accurate estimation of the risk that a person has to suffer a heart disease. In addition, this software tool allows the performance of massive risk estimations, i.e. it helps estimating the risk that a specific population group has of suffering a heart condition. The researchers employed a sample including 3 000 patients.

Heart conditions increasingly affect working age population, which can make individuals loss potential years of work and productivity.

Understanding the risk for heart conditions by simultaneously using different equations is a key factor in heart disease prevention, which would reduce health spending in the short and long term.

According to the researchers, "during the last decade, the approaches to cardiovascular disease prevention have evolved from isolated interventions on modifiable risk factors to an integral model of intervention strategies based on previous risk quantification and stratification."

One of the factors enabling this change is the increasing availability of tools for the quantification and stratification of the risk of suffering a cardiovascular disease; these tools evaluate a set of individual characteristics, the so-called risk factors. This is the framework of the study conducted at the University of Granada and recently published in the Journal of Evaluation in Clinical Practice.

In the field of epidemiologic studies aimed at predicting cardiovascular risk, a set of mathematical models had been developed in previous studies in the USA. The purpose of these models was to provide an estimation of the risk of suffering a cardiovascular event in the short term, i.e. 5-10 years, by assessing exposure to risk factors. University of Granada researchers used this model in their study.

The researchers performed a comparative study of the behavior of different equations applied to a group of "at-risk" patients referred to an Endocrinology Service from a primary care center in Granada, Spain. Risk factors were obesity, high blood pressure, diabetes and lipid profile alterations.

The authors of this study are University of Granada professors Jesús María Ramírez Rodrigo, José Antonio Moreno Vázquez, Alberto Ruiz Villaverde, María de los Ángeles Sánchez Caravaca, Martín López de la Torre Casares and Carmen Villaverde Gutiérrez.

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

New AI Tool Illuminates "Dark Side…

Proteins sustain life as we know it, serving many important structural and functional roles throughout the body. But these large molecules have cast a long shadow over a smaller subclass...

Deep Learning-Based Model Enables Fast a…

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for definitive diagnosis. However, conventional...