Welcome to the New Mexico Chapter of the American College of Cardiology
ACC Live Courses For a listing of all ACC Live Courses please visit: https://www.acc.org/education-and-meetings/meetings |
Please join your cardiology colleagues at the ACC Rockies Chapter Meeting in Park City, Utah for updates on ACC affairs, the potential new CV Board, and clinical topics such as Genetic and Sports EP, plus a discussion on the growing role of obesity medications in heart failure, and the first-ever Cardiology State-of-the-State report. There will be many opportunities for networking, as well!.
For more information and to register, please visit: 
Latest in Cardiology from ACC.org
- Hyperlipidemia Before Pregnancy Associated With Higher Obstetric and CV RiskPreexisting hyperlipidemia in pregnancy is associated with heightened risk of obstetric complications and early cardiovascular events within five years postpartum, according to research presented at ACC's Cardio-Obstetric Essentials conference.
- ACC CardiaCast: Frontline PE Therapies: Insights from ACC’s Interventional and Vascular SectionsIn this episode, host Dr. Saraschandra Vallabhajosyula is joined by colleagues Drs. Uzoma Ibebuogu, Michael Young, and Dean Boudoulas for a dynamic discussion on the frontline management of pulmonary embolism (PE).
- ACC CardiaCast: 2023 ACC Expert Consensus Decision Pathway on Management of Patients with HFpEFIn this episode, Clyde W. Yancy, MD, MSc, MACC, and Leslie L. Davis, NP, PhD, FACC, discuss the 2023 ACC Expert Consensus Decision Pathway on Management of Patients with HFpEF, and where to consider newer treatments with guideline-directed medical therapy.
- ACC Quality Summit Award Winners Address Post-PCI Prediction Models, Enhanced Transitional Care, CathPCI For OPPEAs ACC Quality Summit 2025 convened in Denver, CO, this week, the top three poster winners presented research on the use of the Distressed Communities Index (DCI) to predict post-PCI in-hospital mortality; enhanced transitional care reducing readmissions after TAVR; and use of CathPCI metrics in the ongoing professional practice evaluation process (OPPE).
- Deep Learning Model Accurately Identifies MV Prolapse From TTEsA deep learning model accurately identified mitral valve prolapse (MVP) from transthoracic echocardiograms (TTE), and its predictions were associated with clinical endpoints such as mitral regurgitation (MR) and future mitral valve repair or replacement (MVR), thus it could automate the diagnosis of MVP...