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A £5 blood test could help prevent thousands of heart attacks and strokes, study finds
BY THE OPTIMIST DAILY EDITORIAL TEAM
This year’s top Health stories celebrate the kind of progress that hits close to home: advances that help us live longer, feel better, and take care of one another. From mental health wins to medical innovations, these 2025 highlights are all about healing, hope, and human potential.
A modest £5 ($6.30) blood test could be the key to preventing thousands of heart attacks and strokes, according to new research that could reshape the way doctors assess cardiovascular risk.
Funded by the British Heart Foundation and published in the Journal of the American College of Cardiology, the study highlights how testing troponin levels, a protein released when the heart is damaged, can offer vital clues long before a heart attack strikes.
While troponin tests are currently used to diagnose heart attacks after they occur, the research suggests their value could be even greater when used proactively.
“Troponin, even in the normal range, is a powerful indicator of silent heart muscle damage,” explained Professor Anoop Shah, lead author of the study and professor of cardiovascular medicine at the London School of Hygiene & Tropical Medicine. “As such, the test provides an extra layer of information that we can use to boost our accuracy when predicting people’s risk.”
Predicting the invisible: silent heart damage
The study analyzed data from over 62,000 individuals across Europe and the United States. Researchers measured troponin levels alongside conventional risk factors such as cholesterol, blood pressure, smoking status, age, and history of diabetes. Participants were followed for a decade to track incidences of heart attacks and strokes.
Adding troponin levels to traditional risk algorithms currently based on factors like cholesterol alone boosted their predictive accuracy by up to four times. In practical terms, this means clinicians could better identify patients most in need of preventative care, especially those who fall into a gray area of risk.
“This intermediate risk group can be particularly challenging,” noted Shah. “They are not deemed low-risk, but their risk is not high enough to justify preventive treatment under current guidelines.”
The findings show that troponin testing could help reclassify up to eight percent of patients in the intermediate-risk group as high-risk. For these individuals, early intervention with treatments like statins could prevent serious cardiovascular events.
A cost-effective solution to a pressing problem
With roughly 100,000 people hospitalized for heart attacks in the UK each year, the stakes are high. The ability to identify those at risk earlier and more accurately could relieve strain on healthcare systems and save lives.
“Developments in risk prediction have helped doctors to build effective algorithms that can spot those most at risk,” said Professor Bryan Williams, chief scientific and medical officer at the British Heart Foundation. “But… it’s clear that there is still plenty of room for improvement.”
This research suggests that the solution might be surprisingly simple and affordable. At just £5 ($6.30) per test, adding troponin screening to routine cholesterol checks in GP clinics could become a game-changer.
Prevention with precision
Modeling from the study indicates that for every 500 intermediate-risk patients tested with this method, one heart attack or stroke could be prevented. That may sound modest on the surface, but scaled across national health systems, it translates to thousands of lives potentially saved.
“Ultimately, we want to identify as many high-risk people as possible,” Shah emphasized, “so that no one misses out on the opportunity to get preventative treatment.”
As the healthcare field continues to search for more precise and equitable ways to deliver care, this low-cost, high-impact approach offers a hopeful step forward.
Source study: Journal of the American College of Cardiology— Cardiac troponins and cardiovascular disease risk prediction: an individual-participant-data meta-analysis
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