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 hp
Sign In
Advertise with Us
ZeptoMetrix an Antylia scientific company

Download Mobile App




Novel Blood-Based Risk Score Based on Lipids Improves Prediction of Heart Disease

By LabMedica International staff writers
Posted on 26 Aug 2024
Print article
Image: The new tool can reclassify heart risk and reduce heart attacks (Photo courtesy of Adobe Stock)
Image: The new tool can reclassify heart risk and reduce heart attacks (Photo courtesy of Adobe Stock)

In the field of cardiovascular health, some individuals fall into an ambiguous "intermediate zone" of risk for heart attacks or strokes—neither distinctly low nor high-risk, yet potentially on the cusp of heart disease. This grey area calls for improved methodologies for accurate risk prediction. Traditionally, risk assessments like the widely recognized Framingham Risk Score have utilized factors such as levels of 'good' and 'bad' cholesterol to categorize individuals into risk groups. However, these conventional tools have several limitations, especially in identifying the risks for those in this intermediate category. This oversight is particularly critical as heart disease can progress silently, making early detection crucial to avoid late-stage interventions that are less effective. Now, scientists have developed and validated a novel, blood-based risk score based on lipids (fats in the blood).

The tool, outlined in a paper published in the Journal of the American College of Cardiology, was developed by scientists at the Baker Heart and Diabetes Institute (Melbourne, VC, Australia) and La Trobe University (Melbourne, VC, Australia) to improve the precision of risk predictions for individuals within the intermediate risk group, potentially necessitating more aggressive preventive measures or, conversely, suggesting less intensive interventions like lifestyle changes.

This lipidomic risk score offers a refined approach to assessing intermediate risk, addressing the limitations of traditional models. The score has been adapted for clinical use, suggesting its integration into regular blood testing protocols to better predict heart disease risks based on arterial plaque accumulation. This advancement could enable healthcare providers to more effectively determine which patients might benefit from further diagnostic imaging, such as Coronary Artery Calcium Scoring, thus optimizing strategies for heart disease prevention and management.

“This approach aims to ensure that we are making efficient use of our health resources and that resources are directed at those who really need them, including treating those at high risk while avoiding overtreating those who don’t need it,” said Professor Peter Meikle, lipidomics expert at the Baker Institute and head of the Baker Department of Cardiovascular Research, Translation and Implementation at La Trobe University. “We want to continue to push the boundaries, to make things easier for clinicians, to make better use of limited health resources and to ensure better outcomes for people who may be at high risk of heart disease but unrecognized.”

Related Links:
Baker Heart and Diabetes Institute 
La Trobe University

Gold Member
Troponin T QC
Troponin T Quality Control
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Malondialdehyde HPLC Test
Malondialdehyde in Serum/Plasma – HPLC
New
Epstein-Barr Virus Test
Mononucleosis Rapid Test

Print article

Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.