JACC advancesPub Date : 2025-06-01DOI: 10.1016/j.jacadv.2025.101773
Hongmei Yan MD , Hridhay Karthikeyan MS , Wenjun Fan MD, PhD , Qin Yang MD, PhD , Nathan D. Wong PhD, MPH
{"title":"U.S. Eligibility and Preventable Cardiovascular, Diabetes, and Kidney Outcomes From Semaglutide in the SELECT Trial","authors":"Hongmei Yan MD , Hridhay Karthikeyan MS , Wenjun Fan MD, PhD , Qin Yang MD, PhD , Nathan D. Wong PhD, MPH","doi":"10.1016/j.jacadv.2025.101773","DOIUrl":"10.1016/j.jacadv.2025.101773","url":null,"abstract":"","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 6","pages":"Article 101773"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144120373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JACC advancesPub Date : 2025-06-01DOI: 10.1016/j.jacadv.2025.101700
Om P. Ganda MD
{"title":"Impact of Lipid and ASCVD-Modulating Agents on Glycemia and New-Onset Diabetes or Prediabetes","authors":"Om P. Ganda MD","doi":"10.1016/j.jacadv.2025.101700","DOIUrl":"10.1016/j.jacadv.2025.101700","url":null,"abstract":"","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 6","pages":"Article 101700"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144014361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JACC advancesPub Date : 2025-06-01DOI: 10.1016/j.jacadv.2025.101838
Alexandre Altes MD , Vincent Hanet MD , David Vancraeynest MD, PhD , Agnès Pasquet MD, PhD , Achwaq Lebouazda MSc , François Delelis MD , Hélène Dumortier MD , Valentina Silvestri MD , Manuel Toledano MD , Jean-Louis Vanoverschelde MD, PhD , Sylvestre Maréchaux MD, PhD , Bernhard L. Gerber MD, PhD
{"title":"Prognostic Implications of Cardiac Magnetic Resonance Imaging Characteristics in Primary Mitral Regurgitation","authors":"Alexandre Altes MD , Vincent Hanet MD , David Vancraeynest MD, PhD , Agnès Pasquet MD, PhD , Achwaq Lebouazda MSc , François Delelis MD , Hélène Dumortier MD , Valentina Silvestri MD , Manuel Toledano MD , Jean-Louis Vanoverschelde MD, PhD , Sylvestre Maréchaux MD, PhD , Bernhard L. Gerber MD, PhD","doi":"10.1016/j.jacadv.2025.101838","DOIUrl":"10.1016/j.jacadv.2025.101838","url":null,"abstract":"<div><h3>Background</h3><div>Knowledge remains limited regarding the relationship between cardiac magnetic resonance (CMR) preoperative characteristics and postoperative clinical outcomes in primary mitral regurgitation (MR).</div></div><div><h3>Objectives</h3><div>The authors assessed the prognostic value of CMR preoperative characteristics in patients with primary MR due to prolapse or flail undergoing mitral valve surgery.</div></div><div><h3>Methods</h3><div>We retrospectively studied 284 patients (median age 61 years, 24% women) with chronic significant primary MR, who underwent CMR and echocardiography (echo) prior to mitral valve repair surgery. The endpoint was a composite of all-cause mortality, hospitalization for heart failure, stroke, or life-threatening ventricular arrhythmia.</div></div><div><h3>Results</h3><div>Over a median follow-up of 7.3 years (Q1-Q3: 3.4-10.5), adverse events occurred in 36 (13%) patients. CMR-left atrial emptying fraction (LAEF) (HR: 1.84 [95% CI: 1.32-2.56]; <em>P</em> < 0.001), CMR-right ventricular ejection fraction (HR: 1.36 [95% CI: 1.00-1.84]; <em>P</em> = 0.047), and CMR-indexed aortic forward stroke volume (HR: 1.40 [95% CI: 0.99-2]; <em>P</em> = 0.059) were each associated with a higher risk of adverse outcomes (HR for decrease in 1 SD). After adjusting for clinical and imaging risk factors, reduced CMR-LAEF remained independently associated with adverse prognosis (adjusted HR: 1.78 [95% CI: 1.27-2.48]; <em>P</em> < 0.001). Patients with CMR-LAEF <30% had higher 5-year event rates (28% vs 4%; <em>P</em> < 0.001) and were at a substantially higher risk of adverse outcomes (adjusted HR: 3.78 [95% CI: 1.83-7.80]; <em>P</em> < 0.001), with added prognostic value confirmed by multiple performance model metrics.</div></div><div><h3>Conclusions</h3><div>In patients with primary MR, among CMR and echo preoperative characteristics, reduced CMR-LAEF, with a threshold value of 30%, is markedly associated with an increased risk of postoperative adverse outcomes.</div></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 6","pages":"Article 101838"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JACC advancesPub Date : 2025-06-01DOI: 10.1016/j.jacadv.2025.101791
Lily N. Dastmalchi DO, MA , Martha Gulati MD, MS , Rebecca C. Thurston PhD , Emily Lau MD, MPH , Amy Sarma MD , Cherie Q. Marfori MD , Allison E. Gaffey PhD , Stephanie Faubion MD, MBA , Deepika Laddu PhD , Chrisandra L. Shufelt MD, MS , Garima Sharma MD
{"title":"Improving Cardiovascular Clinical Competencies for the Menopausal Transition","authors":"Lily N. Dastmalchi DO, MA , Martha Gulati MD, MS , Rebecca C. Thurston PhD , Emily Lau MD, MPH , Amy Sarma MD , Cherie Q. Marfori MD , Allison E. Gaffey PhD , Stephanie Faubion MD, MBA , Deepika Laddu PhD , Chrisandra L. Shufelt MD, MS , Garima Sharma MD","doi":"10.1016/j.jacadv.2025.101791","DOIUrl":"10.1016/j.jacadv.2025.101791","url":null,"abstract":"<div><div>Cardiovascular disease (CVD) is the leading cause of death in women with an increase in risk after menopause. Over the past 20 years, longitudinal studies have helped differentiate the influence of chronological aging from ovarian aging on cardiovascular health. In addition to the pronounced sex hormone changes of the menopause transition (MT), the MT is also often accompanied by vasomotor symptoms, sleep problems, and mental health changes that impact women's cardiovascular health. The purpose of this invited review is to highlight the key changes that can alter CVD risk. Given the gaps in medical training, we also describe the need for specialized postgraduate curriculum in managing the MT with an aim to improve MT screening and management of CVD during this universal life stage. Finally, we propose a multidisciplinary approach led by experts in women's cardiovascular health and present an approach utilizing validated screening tools and CVD risk scores to discuss the candidacy of systemic menopause hormone therapy.</div></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 6","pages":"Article 101791"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
JACC advancesPub Date : 2025-06-01DOI: 10.1016/j.jacadv.2025.101803
Kaveh Hosseini MD, MPH , Nazanin Anaraki MD, MPH , Parham Dastjerdi MD , Sina Kazemian MD , Mandana Hasanzad PhD , Mohamad Alkhouli MD, MBA , Mahboob Alam MD , Khurram Nasir MD, MPH , Jamal S. Rana MD, PhD , Ami B. Bhatt MD
{"title":"Bridging Genomics to Cardiology Clinical Practice","authors":"Kaveh Hosseini MD, MPH , Nazanin Anaraki MD, MPH , Parham Dastjerdi MD , Sina Kazemian MD , Mandana Hasanzad PhD , Mohamad Alkhouli MD, MBA , Mahboob Alam MD , Khurram Nasir MD, MPH , Jamal S. Rana MD, PhD , Ami B. Bhatt MD","doi":"10.1016/j.jacadv.2025.101803","DOIUrl":"10.1016/j.jacadv.2025.101803","url":null,"abstract":"<div><div>Despite advances in cardiovascular disease risk stratification, traditional risk prediction models often fail to identify high-risk individuals before adverse events occur, underscoring the need for more precise tools. Polygenic risk scores (PRS) quantify genetic susceptibility by aggregating genetic variants but face challenges in practice. This systematic review investigates how artificial intelligence (AI) and machine learning algorithms can optimize PRS (AI-optimized PRS) to improve cardiovascular disease prediction. Analyzing 13 studies, we found that AI-optimized PRS models enhance predictive accuracy by improving feature selection, handling high-dimensional data, and integrating diverse variables—including clinical risk factors, biomarkers, imaging, and combining multiple PRS. These models outperform nonoptimized PRS models, providing a more comprehensive understanding of individual risk profiles. Evidence suggests that AI-optimized PRS can better stratify patients and guide personalized prevention strategies. Future research is needed to explore sex differences, include diverse populations, integrate AI-optimized PRS into electronic health records, and assess cost-effectiveness.</div></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 6","pages":"Article 101803"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}