Avinainder Singh , Arthur Shiyovich , Camila Veronica Freire , Gary Peng , Stephanie A. Besser , Adam N. Berman , Brittany N. Weber , Daniel M. Huck , Rhanderson Cardoso , Cian P. McCarthy , Khurram Nasir , Marcelo F. DiCarli , Deepak L. Bhatt , Ron Blankstein
{"title":"预防方程在年轻心肌梗死患者心血管风险预测中的表现:来自MGB young - mi登记","authors":"Avinainder Singh , Arthur Shiyovich , Camila Veronica Freire , Gary Peng , Stephanie A. Besser , Adam N. Berman , Brittany N. Weber , Daniel M. Huck , Rhanderson Cardoso , Cian P. McCarthy , Khurram Nasir , Marcelo F. DiCarli , Deepak L. Bhatt , Ron Blankstein","doi":"10.1016/j.ajpc.2025.100992","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Predicting cardiovascular risk in young adults remains challenging. The newly developed PREVENT equations offers several advantages for short and long-term cardiovascular risk prediction.</div></div><div><h3>Objective</h3><div>To determine how often PREVENT equations identify increased cardiovascular risk among young adults who experience premature myocardial infarction compared with existing risk calculators</div></div><div><h3>Methods</h3><div>The YOUNG-MI registry is a retrospective cohort from two large academic centers, which included individuals who experienced an MI at age ≤ 50 years. Study physicians adjudicated diagnosis of Type 1 MI. Cardiovascular risk was estimated by pooled cohort equations and PREVENT equations based on data available prior to MI or at the time of presentation.</div></div><div><h3>Results</h3><div>The study cohort included 1149 individuals with a median age of 45 years and 19 % women. The median 10-year ASCVD risk calculated by pooled cohort equations and 2023 PREVENT equations was 4.6 % and 2.3 %, respectively. Using the 10-year ASCVD risk estimates from the 2023 PREVENT equations, only 33 (3 %) individuals met the 7.5 % threshold while 93 (8 %) met the 5 % threshold and 333 (29 %) met the 3 % threshold. For 30-year ASCVD risk using PREVENT, 827 (72 %) met a threshold of ≥ 10 %.</div></div><div><h3>Conclusion</h3><div>The PREVENT equations may lead to undertreatment of young adults who experienced an MI. Using the 30-year risk PREVENT equations may improve long-term risk assessment in this population.</div></div>","PeriodicalId":72173,"journal":{"name":"American journal of preventive cardiology","volume":"22 ","pages":"Article 100992"},"PeriodicalIF":4.3000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of PREVENT equations for cardiovascular risk prediction in young patients with myocardial infarction: From the MGB YOUNG-MI registry\",\"authors\":\"Avinainder Singh , Arthur Shiyovich , Camila Veronica Freire , Gary Peng , Stephanie A. Besser , Adam N. Berman , Brittany N. Weber , Daniel M. Huck , Rhanderson Cardoso , Cian P. McCarthy , Khurram Nasir , Marcelo F. DiCarli , Deepak L. Bhatt , Ron Blankstein\",\"doi\":\"10.1016/j.ajpc.2025.100992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Predicting cardiovascular risk in young adults remains challenging. The newly developed PREVENT equations offers several advantages for short and long-term cardiovascular risk prediction.</div></div><div><h3>Objective</h3><div>To determine how often PREVENT equations identify increased cardiovascular risk among young adults who experience premature myocardial infarction compared with existing risk calculators</div></div><div><h3>Methods</h3><div>The YOUNG-MI registry is a retrospective cohort from two large academic centers, which included individuals who experienced an MI at age ≤ 50 years. Study physicians adjudicated diagnosis of Type 1 MI. Cardiovascular risk was estimated by pooled cohort equations and PREVENT equations based on data available prior to MI or at the time of presentation.</div></div><div><h3>Results</h3><div>The study cohort included 1149 individuals with a median age of 45 years and 19 % women. The median 10-year ASCVD risk calculated by pooled cohort equations and 2023 PREVENT equations was 4.6 % and 2.3 %, respectively. Using the 10-year ASCVD risk estimates from the 2023 PREVENT equations, only 33 (3 %) individuals met the 7.5 % threshold while 93 (8 %) met the 5 % threshold and 333 (29 %) met the 3 % threshold. For 30-year ASCVD risk using PREVENT, 827 (72 %) met a threshold of ≥ 10 %.</div></div><div><h3>Conclusion</h3><div>The PREVENT equations may lead to undertreatment of young adults who experienced an MI. Using the 30-year risk PREVENT equations may improve long-term risk assessment in this population.</div></div>\",\"PeriodicalId\":72173,\"journal\":{\"name\":\"American journal of preventive cardiology\",\"volume\":\"22 \",\"pages\":\"Article 100992\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American journal of preventive cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666667725000674\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of preventive cardiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666667725000674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Performance of PREVENT equations for cardiovascular risk prediction in young patients with myocardial infarction: From the MGB YOUNG-MI registry
Background
Predicting cardiovascular risk in young adults remains challenging. The newly developed PREVENT equations offers several advantages for short and long-term cardiovascular risk prediction.
Objective
To determine how often PREVENT equations identify increased cardiovascular risk among young adults who experience premature myocardial infarction compared with existing risk calculators
Methods
The YOUNG-MI registry is a retrospective cohort from two large academic centers, which included individuals who experienced an MI at age ≤ 50 years. Study physicians adjudicated diagnosis of Type 1 MI. Cardiovascular risk was estimated by pooled cohort equations and PREVENT equations based on data available prior to MI or at the time of presentation.
Results
The study cohort included 1149 individuals with a median age of 45 years and 19 % women. The median 10-year ASCVD risk calculated by pooled cohort equations and 2023 PREVENT equations was 4.6 % and 2.3 %, respectively. Using the 10-year ASCVD risk estimates from the 2023 PREVENT equations, only 33 (3 %) individuals met the 7.5 % threshold while 93 (8 %) met the 5 % threshold and 333 (29 %) met the 3 % threshold. For 30-year ASCVD risk using PREVENT, 827 (72 %) met a threshold of ≥ 10 %.
Conclusion
The PREVENT equations may lead to undertreatment of young adults who experienced an MI. Using the 30-year risk PREVENT equations may improve long-term risk assessment in this population.