JACC advances最新文献

{"title":"Cardio-Oncological Sequelae of Autologous Stem Cell Transplantation","authors":"Zsófia Sándor MD,&nbsp;Zoltán V. Varga MD, PhD,&nbsp;Tamás G. Gergely MD, PhD,&nbsp;Laura Horváth MD, PhD,&nbsp;Tamás Masszi MD, PhD,&nbsp;Zsófia D. Drobni MD, PhD,&nbsp;José J. Fuster MD, PhD,&nbsp;Zoltán Pozsonyi MD, PhD","doi":"10.1016/j.jacadv.2026.103279","DOIUrl":"10.1016/j.jacadv.2026.103279","url":null,"abstract":"<div><div>Autologous hematopoietic stem cell transplantation is a major milestone in modern oncohematological therapies; however, both in the peritransplant and post-transplant phase, the incidence of cardiovascular (CV) events is markedly higher than in the general population. The pathomechanism of CV complications is multifactorial, determined by complex interactions between patient-specific, transplant-related, and oncological risk factors. In recent years, clonal hematopoiesis has emerged as a clinically relevant determinant of adverse CV outcomes. Patients undergoing autologous hematopoietic stem cell transplantation represent a high-risk CV population due to cumulative cytotoxic exposure, treatment-driven clonal selection, and increasing long-term survival. These factors highlight the need for future development of clonal hematopoiesis–based risk stratification models that combine gene-specific alterations, clonal expansion magnitude, and mutational burden with conventional CV risk factors. Novel risk stratification approaches may enable tailored patient follow-up, individualized preventive interventions, and the early detection and prevention of CV complications in this sensitive patient population.</div></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"5 10","pages":"Article 103279"},"PeriodicalIF":5.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149076988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Enabled Electrocardiogram for Rule-Out of NSTEMI Across Clinically Challenging Presentations","authors":"Hak Seung Lee MD,&nbsp;Kyuseok Kim MD, PhD,&nbsp;Min Sung Lee MD","doi":"10.1016/j.jacadv.2026.103275","DOIUrl":"10.1016/j.jacadv.2026.103275","url":null,"abstract":"<div><span><figure><span><img><ol><li><span><span>Download: <span>Download high-res image (144KB)</span></span></span></li><li><span><span>Download: <span>Download full-size image</span></span></span></li></ol></span></figure></span></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"5 10","pages":"Article 103275"},"PeriodicalIF":5.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"U.S. Trends in 10-Year Cardiovascular Risk Scores Over 2 Decades.","authors":"Yelena Drexler, Ofek Goldwasser, Connor McCarley, Danielle Land, Christopher Naranjo, Vinodh Mechery, Shathiyah Kulandavelu, Tatjana Rundek, Eugene Yang, Tali Elfassy","doi":"10.1016/j.jacadv.2026.103307","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103307","url":null,"abstract":"<p><strong>Background: </strong>The PREVENT (Predicting Risk of Cardiovascular Disease Events) equations estimate 10-year risk of total cardiovascular disease (CVD), atherosclerotic CVD (ASCVD), coronary heart disease (CHD), stroke, and heart failure (HF).</p><p><strong>Objectives: </strong>The objective of the study was to describe the trends in PREVENT-based 10-year CVD risk among U.S. adults.</p><p><strong>Methods: </strong>We used data from the National Health and Nutrition Examination Survey (1999-2023) to estimate 10-year risk of total CVD, ASCVD, CHD, stroke, and HF among adults aged 30 to 79 years. Crude and age-standardized risk scores were calculated for each survey cycle, and orthogonal polynomial coefficients were used to test for trends across 10 continuous 2-year cycles (1999-2018) overall and according to sociodemographic characteristics.</p><p><strong>Results: </strong>Among 26,980 adults, 10-year CVD risk increased 24.4%, from 4.9% in 1999 to 2000 to 6.1% in 2017 to 2018 (P < 0.01). After age standardization, 10-year CVD risk remained stable at 5.4% in both periods. Age-standardized ASCVD risk declined from 3.5% to 3.3% (P = 0.04), driven by a 10% decline in CHD risk from 2.0% to 1.8% (P = 0.01), whereas stroke risk remained stable at 1.7%, and HF risk increased 7.1%, from 2.8% to 3.0% (P = 0.01). Reductions in CHD risk were more pronounced and increases in HF risk more modest among non-Hispanic White adults, those with higher educational attainment, and those with a higher income-to-poverty ratio.</p><p><strong>Conclusions: </strong>Among U.S. adults, 10-year total CVD risk increased over time due to population aging. Age-adjusted total CVD risk remained stable, with declining ASCVD risk driven by reductions in CHD risk offset by rising HF risk. Socioeconomic disparities in both CHD and HF risk widened overtime.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103307"},"PeriodicalIF":5.5,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139728","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}

{"title":"Automated Aortic Valve Calcification Scoring: Multicenter External Validation of a Deep Learning Algorithm.","authors":"Jimmy Zheng, Eren Alkan, Aniruddha Deshpande, Jo Ann Efobi, William F Fearon, Paul A Heidenreich, Nishith Khandwala, David J Maron, Felipe Morais, Fatima Rodriguez, David Eng, Alexander T Sandhu","doi":"10.1016/j.jacadv.2026.103277","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103277","url":null,"abstract":"<p><strong>Background: </strong>Aortic valve calcification (AVC) quantification is a guideline-recommended imaging biomarker for aortic stenosis (AS) severity and progression yet remains underreported on routine chest computed tomography (CT). With nearly 20 million nongated chest CTs performed annually in the United States, automated AVC detection offers potential for opportunistic AS screening without added radiation or cost.</p><p><strong>Objectives: </strong>This study evaluated whether deep learning can accurately quantify AVC from nongated, noncontrast chest CT, with performance comparable to expert assessment.</p><p><strong>Methods: </strong>We evaluated a convolutional neural network across a multicenter consortium of 33 sites spanning 8 health systems in the United States and Brazil. The algorithm was developed using training (n = 1,446) and validation (n = 361) sets and evaluated on a separate holdout test set (n = 239) acquired from 2021 to 2024. Reference standards were manual segmentations independently verified by at least 2 board-certified radiologists. Primary outcomes were Pearson correlation and Bland-Altman analysis of algorithm-estimated vs manual Agatston scores. Secondary outcomes were sensitivity and specificity for a high calcium burden associated with moderate-to-severe AS using validated sex-specific thresholds.</p><p><strong>Results: </strong>The algorithm showed high correlation with expert reference standards (r = 0.99; 95% CI: 0.98-0.99; P < 0.001). Bland-Altman analysis showed minimal bias (mean difference: 5.2 AU; 95% CI: -7.6 to 17.9). For moderate-to-severe AS, sensitivity was 0.92 (95% CI: 0.80-0.97) and specificity 0.98 (95% CI: 0.95-0.99). Performance remained consistent across demographic subgroups and CT technical parameters.</p><p><strong>Conclusions: </strong>This automated deep learning algorithm quantifies AVC from routine chest CT with expert-comparable performance, potentially enabling opportunistic AS screening. Prospective studies are needed to determine whether it improves clinical outcomes.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103277"},"PeriodicalIF":5.5,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119587","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}

{"title":"A Hemodynamic Echocardiographic Approach to Disease Severity and Prognosis in Transthyretin Amyloid Cardiomyopathy.","authors":"Matteo Serenelli, Anna Cantone, Aldostefano Porcari, Marco Pozzan, Marco Merlo, Gianfranco Sinagra, Gabriele Guidi Colombi, Beatrice Dal Passo, Federico Sanguettoli, Matteo Arzenton, Daniele Maio, Martina Vitali, Giulia Casolari, Jacopo Bonini, Alberto Cipriani, Laura De Michieli, Donato Mele, Giulio Sinigiani, Daniela Tomasoni, Marco Metra, Rita Pavasini, Simone Biscaglia, Gianluca Campo","doi":"10.1016/j.jacadv.2026.103244","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103244","url":null,"abstract":"<p><strong>Background: </strong>Transthyretin amyloid cardiomyopathy (ATTR-CM) causes heart failure and poor outcomes. Prognostic stratification is fundamental, yet validated staging systems rely exclusively on biomarkers, neglecting structural and functional cardiac parameters.</p><p><strong>Objectives: </strong>This study evaluates a noninvasive hemodynamic echocardiographic approach to stratify patients with ATTR-CM.</p><p><strong>Methods: </strong>Patients were categorized into 3 groups based on stroke volume index (SVi) and systolic pulmonary artery pressure (sPAP), markers of forward flow and elevated filling pressures. We compared receiver operating characteristic curves for various potentially predictive hemodynamic parameters to identify these as the most robust candidates for risk stratification. Optimal cutoffs (30 mL/m² for SVi and 40 mm Hg for sPAP) were determined using the Liu index, supported by both univariable and multivariable survival analyses. The primary endpoint was the composite of all-cause mortality and heart failure hospitalization. Prognostic utility was evaluated using multivariable Cox regression, adjusted for age, sex, and disease-modifying therapy.</p><p><strong>Results: </strong>The cohort included 293 patients with ATTR-CM: group 1 (normal SVi/sPAP, n = 115 [39%]), group 2 (low SVi or high sPAP, n = 129), and group 3 (low SVi/high sPAP, n = 49). The primary outcome occurred in 108 (37%) patients. The multivariable analysis confirmed the staging system as an independent predictor of the composite outcome (group 2 HR: 1.70, 95% CI: 1.05-2.71; group 3 HR: 2.50, 95% CI: 1.44-4.30; P < 0.001).</p><p><strong>Conclusions: </strong>The noninvasive hemodynamic approach provides an alternative and promising method to stratify the risk of clinical outcome in patients with ATTR-CM, potentially improving management strategies.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103244"},"PeriodicalIF":5.5,"publicationDate":"2026-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119505","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}

{"title":"Prognostic Impact of CCTA According to Standard Cardiovascular Modifiable Risk Factors.","authors":"Alaaeddine El Ghazawi, Maria Alwan, Ahmad El Yaman, Mahmoud Al Rifai, Mouaz H Al-Mallah","doi":"10.1016/j.jacadv.2026.103239","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103239","url":null,"abstract":"<p><strong>Background: </strong>The prognostic value of coronary computed tomographic angiography (CCTA) findings across standard modifiable risk factor (SMuRF) categories has not been explored.</p><p><strong>Objectives: </strong>We evaluated whether SMuRF burden modifies the prognostic value of the different coronary artery disease (CAD) categories on CCTA.</p><p><strong>Methods: </strong>Patients without prior CAD who underwent clinically indicated CCTA were included. CCTA findings were categorized as absent CAD (0% stenosis), nonobstructive CAD (1% to 49%), or obstructive CAD (≥50%). SMuRF burden was defined by hypertension, dyslipidemia, diabetes, and smoking, and classified from 0 to 4. The primary endpoint was all-cause mortality or myocardial infarction (MI).</p><p><strong>Results: </strong>Among 29,840 patients (mean age 64 ± 14 years, 53% men), 33% had absent CAD, 43% nonobstructive CAD, and 23% obstructive CAD. Over a median follow-up of 2 years, 2,030 patients (7%) experienced death or MI. Across all CAD categories, higher SMuRF burden was associated with higher cumulative incidence of death or MI rates and higher incidence rates (P < 0.001). Incidence rates per 1,000 person-years across SMuRF categories 0 to 4 increased from 10 to 74 in absent CAD, and 35 to 75 in obstructive CAD (P < 0.001). In adjusted models, each 1-SMuRF increase was associated with a higher risk across all CAD groups (HR: 1.41; 95% CI: 1.27-1.56 for absent CAD; HR: 1.26; 95% CI: 1.17-1.35 for nonobstructive CAD; HR: 1.29; 95% CI: 1.19-1.40 for obstructive CAD). Adding SMuRF burden to age, sex, body mass index, and CAD severity significantly improved prognostic discrimination (C-index 0.653-0.673; P < 0.001).</p><p><strong>Conclusions: </strong>Across CCTA-defined stenosis categories, SMuRF burden provides incremental prognostic information beyond anatomic disease severity, supporting its integration into CCTA-based risk stratification and personalized preventive management.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103239"},"PeriodicalIF":5.5,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018952","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}

{"title":"Central Adiposity and Inflammation Mediate the Association Between Ultraprocessed Food Intake and Cardiovascular Disease Risk.","authors":"Amier Haidar, Spencer Flynn, Rishi Rikhi, Karol E Watson, Alexis C Wood, Michael D Shapiro","doi":"10.1016/j.jacadv.2026.103247","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103247","url":null,"abstract":"<p><strong>Background: </strong>Higher consumption of ultraprocessed foods (UPFs) has been consistently associated with increased cardiovascular disease (CVD) risk, but the biological pathways underlying this relationship remain incompletely understood.</p><p><strong>Objectives: </strong>The study aims to examine whether body composition, systemic inflammation, and metabolic biomarkers mediate the association between UPF consumption and incident CVD.</p><p><strong>Methods: </strong>MESA (Multi-Ethnic Study of Atherosclerosis) is a population-based, prospective cohort study of men and women aged 45 to 84 years who were free of clinically apparent CVD at baseline. UPFs were classified according to the Nova classification system. To evaluate potential pathways linking UPF intake with incident CVD, mediation analyses were conducted using generalized structural equation modeling and counterfactual-based causal mediation analysis.</p><p><strong>Results: </strong>Among 6,531 participants, higher UPF intake was associated with adverse cardiometabolic profiles. In single-mediator generalized structural equation models, both waist-to-height ratio (β: 0.012; CI: 0.007-0.017) and interleukin (IL)-6 (β: 0.003; CI: 0.001-0.006) significantly mediated the association between UPF intake and incident CVD, with waist-to-height ratio mediating 44% and IL-6 mediating 13% of the total association. In parallel mediation models including waist-to-height ratio and IL-6 simultaneously, both mediators retained independent indirect effects, with adiposity contributing 38% and IL-6 contributing 9% of the proportion mediated. Results were consistent in magnitude and direction across counterfactual mediation analyses.</p><p><strong>Conclusions: </strong>The association between UPF consumption and CVD risk appears to be partially mediated through central adiposity and systemic inflammation. These findings provide mechanistic insight into how UPFs may contribute to CVD risk and support dietary strategies that limit UPFs to reduce cardiometabolic risk.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103247"},"PeriodicalIF":5.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119548","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}

{"title":"Redefining First Medical Contact in Acute Coronary Syndromes: Implications for the National Cardiovascular Data Registry.","authors":"Nathaniel R Smilowitz, Michael R Gunderson, Cameron Buck, R Harper Stone, Julie Mobayed, Joaquin E Cigarroa, Leslie L Davis","doi":"10.1016/j.jacadv.2026.103241","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103241","url":null,"abstract":"","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103241"},"PeriodicalIF":5.5,"publicationDate":"2026-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148972388","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}

{"title":"Prioritizing Selective Use of Apolipoprotein-B Testing in the Era of Modern LDL-Cholesterol Calculation.","authors":"Alexander C Razavi, Michael D Shapiro, Pradeep Natarajan, Eugenia Gianos, Seth S Martin, Roger S Blumenthal","doi":"10.1016/j.jacadv.2026.103220","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103220","url":null,"abstract":"","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103220"},"PeriodicalIF":5.5,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119525","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}

{"title":"Preoperative Angiographic Washout and Coronary Artery Bypass Graft Patency.","authors":"Luciano J Delbono, Haizhou Yang, Domingo Uceda, Brennan Callow, Nathaniel Ayoub, Himanshu J Patel, C Alberto Figueroa","doi":"10.1016/j.jacadv.2026.103204","DOIUrl":"https://doi.org/10.1016/j.jacadv.2026.103204","url":null,"abstract":"<p><strong>Background: </strong>Coronary artery bypass graft (CABG) failure occurs in 3% to 30% of grafts by 1 year. Because graft flow depends on distal outflow, elevated microvascular resistance may predispose target vessels to graft failure.</p><p><strong>Objectives: </strong>The objective of the study was to determine whether quantitative target-vessel contrast washout from standard preoperative coronary angiography is associated with subsequent CABG patency.</p><p><strong>Methods: </strong>This single-center retrospective study included 107 patients undergoing CABG from 2021 to 2024 with preoperative coronary angiography and postoperative graft imaging by invasive angiography or computed tomography angiography. A total of 201 bypassed target vessels were analyzed. Preoperative angiograms were segmented using a validated neural network, and contrast intensity profiles (CIPs) were generated after isolating each target-vessel runoff territory. CIP downslope was the primary washout variable. The primary outcome was graft failure, defined as graft occlusion or stenosis.</p><p><strong>Results: </strong>Among 201 bypassed target vessels, 152 remained patent and 49 met the criteria for graft failure. Each 1-SD shift toward a shallower CIP downslope was associated with higher odds of graft failure on univariable generalized estimating equations analysis (OR: 1.71; 95% CI: 1.19-2.47; P = 0.004) and after adjustment for age, sex, diabetes mellitus, and current smoking (OR: 1.77; 95% CI: 1.22-2.57; P = 0.003). Model discrimination was modest (area under the curve: 0.67; 95% CI: 0.62-0.78). A downslope threshold of -3,158 stratified graft patency, with faster washout associated with lower failure hazard (HR: 0.51; 95% CI: 0.28-0.90; log-rank P = 0.0193).</p><p><strong>Conclusions: </strong>Automated quantification of preoperative angiographic contrast washout is feasible and associated with CABG patency, supporting CIP downslope as a potential angiography-derived marker of target-vessel outflow.</p>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":" ","pages":"103204"},"PeriodicalIF":5.5,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139708","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}