A new analysis from researchers at Mount Sinai published in JACC: Advances indicates that tools routinely used in primary care to estimate 10-year heart-attack risk may leave out a substantial number of patients who already have significant, symptom-free disease.
The findings compared traditional atherosclerotic cardiovascular disease (ASCVD) scoring with the newer PREVENT model, which incorporates a broader range of clinical factors.
According to the study team, nearly half of the individuals who later experienced their first heart attack would have been labeled “low” or “borderline” risk just 48 hours earlier.
PREVENT missed an even larger share. The researchers argue that these gaps show how population-based tools can struggle when applied to individual patients.
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Most symptoms appeared only shortly before hospitalization
The review included 474 adults under age 66 who had no prior diagnosis of coronary artery disease and were treated for their first heart attack at two Mount Sinai hospitals between 2020 and 2025.
The majority noticed warning signs, if they had any, less than two days before seeking care.
Many reported no chest pain or shortness of breath during earlier routine visits, leaving little reason for clinicians to order advanced testing.
Because their calculated risk appeared low, many would not have been considered for preventive treatment such as statins or additional imaging.
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Researchers say this timing underscores a central challenge: symptoms often emerge only after plaque has already become unstable.
Researchers call for earlier identification
Study authors, Dr. Amir Ahmadi and Dr. Anna Mueller of Mount Sinai, suggest that prevention strategies may need to shift toward identifying plaque directly through imaging rather than relying primarily on symptom-based pathways.
While the team notes that more research is needed, they argue that catching disease earlier could give clinicians more time to intervene before a heart attack is imminent.
Sources: Science Daily, and JACC: Advances.
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This article is made and published by Ida-Marie Palm Varbæk, who may have used AI in the preparation.