A simpler way to predict heart failure

Predicting the future just got a little clearer - when it comes to the likelihood of heart failure, that is.

The levels of two biomarkers in the bloodstream were found to significantly improve our ability to identify who is at a higher risk of having heart failure in the next 10 years, said a group of researchers at Baylor College of Medicine and the Michael E. DeBakey Veterans Affairs hospital.

The findings, published in the recent edition of Clinical Chemistry, are part of the ongoing Atherosclerosis Risk in Communities (ARIC) study designed to investigate the causes of atherosclerosis and its clinical outcomes.

The clinically used models for predicting heart failure rely on a combination of lifestyle, demographic and cardiovascular risk factor information. While the biomarkers improved the clinical models, the investigators were surprised to find that a simpler design, which included age, race and the blood concentrations of two biomarkers, troponin T and N-terminal-pro-B-type natriuretic peptide (NT-proBNP), was found to be statistically no different than the more complex model.

“Heart failure already is and will continue to be a major cardiovascular public health issue in the coming decades,” said Dr. Vijay Nambi, assistant professor of medicine of the section of cardiovascular research at Baylor College of Medcine.

“Identifying simpler and better ways to predict heart failure can help clinicians and researchers improve and better target their preventive strategies,” said Nambi.

Troponin T is commonly used by doctors to diagnose a heart attack. It is an indication of damaged heart muscle, but by using improved assays (testing methods) researchers have been able to detect the protein in low levels even in individuals with no symptoms.

In fact, in the middle-older aged ARIC study, participants - approximately 2 out of every 3 individuals - had measurable levels. NT-proBNP is an inactive peptide fragment left over from the production of brain natiuretic peptide (BNP), a small neuropeptide hormone that has been shown to have value in diagnosing congestive heart failure.

The researchers used both these markers in the prediction of future heart failure (over 10 years), thereby understanding which individuals among a general population are at the highest risk of heart failure.

Applying the model to patient data from the ongoing ARIC study, the researchers found their simple heart failure risk model was comparable to more complex models that take into account age, race, systolic blood pressure, antihypertensive medication use, smoking or former smoking, diabetes, body-mass index, prevalent coronary heart disease and heart rate.

“We are now able to predict who will develop heart failure better then we can predict who will have a heart attack, so the critical issues that we must now address is what lifestyle and drug therapies can prevent the development of heart failures for individuals who are at high risk,” said Dr. Christie Ballantyne, professor of medicine and section chief of cardiology and cardiovascular research at Baylor, and of the Houston Methodist Center for Cardiovascular Disease Prevention.


Comments are subject to moderator review and may not appear immediately on the site.

Please read our commenting policy before posting.

Any comment violating the site's commenting guidelines will be removed and the user could be banned from the site.

Use the comment form below to begin a discussion about this content.

Sign in to comment