Cardiology Conference Featured Innovations from UCSF Health Experts

Cardiology experts from UCSF Health presented new research and clinical findings at the American College of Cardiology’s (ACC) 74th Annual Scientific Session and Expo in Chicago, March 29-31.

This year’s program featured presentations from UCSF Division of Cardiology investigators and clinicians on such topics as interventional cardiology, pulmonary vascular disease, congenital heart disease, critical care cardiology, electrophysiology and AI in cardiovascular imaging and diagnostics.

Featured Clinical Research

Sammy Elmariah, MD, an interventional cardiologist and chief of Interventional Cardiology at UCSF was senior author and presenter for “Electronic Provider Notification to Facilitate the Recognition and Management of Severe Aortic Stenosis: The DETECT AS Trial” during the Featured Clinical Research I session (#109). During the discussion following the presentation, Elmariah reported on the results of a randomized clinical trial with Massachusetts General Hospital, evaluating the impact of electronic provider notifications (EPN) on treatment of patients with severe aortic stenosis. In this first-of-its-kind study, EPN increased rates of aortic valve replacement (AVR) for severe aortic stenosis, lessened gender and age disparities in AVR utilization and improved survival time. The results showed EPN may provide a simple, scalable intervention to raise awareness of critical transthoracic echocardiogram findings and improve the quality of care for severe aortic stenosis.

Elmariah was also a panelist at the Primetime Event symposium (#4510), “Referral of Severe Aortic Stenosis: Are Patient Pathways Changing?” This symposium featured a roundtable discussion regarding the latest clinical data in the management of severe aortic stenosis. Expert clinicians discussed how these findings impact patients, including the benefits of prompt referral and early intervention to achieve optimal outcomes in this challenging patient population.

Carolyn Hendrickson, MD, MPH, a pulmonary and critical care medicine subspecialist and UCSF associate professor of Medicine, was first author and presenter of “The Equiox Study: Evaluating Pulse Oximeter Bias Across a Range of Skin Pigment in Critically Ill Adults” during the late-breaking clinical trials session (#106). A discussion followed the presentation of the study, which had the primary aim of measuring the bias in pulse oximeter blood oxygen measurements across a range of skin pigmentations among critically ill patients with hypoxia (low blood oxygen levels). The study found that the differences, or bias, between estimates of blood oxygen saturation levels as measured with pulse oximeters compared to the gold-standard method of measuring oxygen saturation in arterial blood varied significantly between patients with darkly pigmented skin compared to lighter skin pigment.

Samuel Brusca, MD, a cardiologist and UCSF critical care specialist, presented “POCUS (Cardiac)” and “POCUS (Pericardiocentesis)” during special topic session (#808), “Hands-on Learning: Critical Care Cardiology – Survival Skills in the CICU II.” The session was a simulation learning experience, with five hands-on simulation stations, including common procedures, therapies and diagnostic tests frequently seen in a contemporary cardiac intensive care unit. This included high fidelity simulation with key clinical scenarios in invasive hemodynamic monitoring, point-of-care lung ultrasound, focus cardiac ultrasound, mechanical circulatory support and pericardiocentesis.

Brusca also served as a panelist for special topic session (#5048), “Surviving in the CICU: Early Career Conundrums and Burnout in Critical Care Cardiology.”

Marc Simon, MD, MS, cardiologist and director of pulmonary vascular disease and the Pulmonary Hypertension Comprehensive Care Center at UCSF, was a panelist, first author and presenter for “Methamphetamine and PAH” during a scientific session on pulmonary vascular disease (#332), “High Stakes! Complex Clinical Cases in Pulmonary.” The session delved into methamphetamine-associated PAH (pulmonary arterial hypertension), connective tissue disease-related pulmonary hypertension and critical care challenges.

Simon also served as co-chair of pulmonary vascular disease session (#248), “Highlighted Original Research: Pulmonary Vascular Disease and the Year in Review.”

James Pirruccello, MD, a cardiologist and UCSF assistant professor of Cardiology, was the moderator for multimodal imaging session (#353), “Putting the IQ into Artificial Intelligence for Cardiac Imaging,” about how AI is transforming cardiovascular imaging. He also served as moderator for moderated poster session (#998), “CardioHacks: Innovative Solutions for Heart Health,” which focused on devices and tools that use AI to improve cardiovascular health.

Theodore Abraham, MD, FACC, FASE, a cardiologist and co-director of UCSF’s Hypertrophic Cardiomyopathy Center of Excellence, served as co-chair of multimodal imaging session (#354), “Multimodality Imaging Unlocks the Secrets of HCM: Joint Symposium of the American Society of Echocardiology and the American College of Cardiology.” The session focused on the importance of multimodality imaging for diagnosing and managing hypertrophic cardiomyopathy. Cased-based examples provided a practical approach to echocardiography, cardiac myocardial resonance imaging and cardiac-computed tomography.

Shabnam Peyvandi, MD, MAS, a pediatric cardiologist and director of UCSF’s pediatric cardiovascular research program, was a panelist, first author and presenter for “Telemedicine Approaches to Fetal Care” during congenital heart disease session (#388), “Access to Quality Life Long Congenital Heart Health: Myth or Reality?” The overarching aim of the study is to provide uninterrupted life-long care to patients with congenital heart disease while multidimensional factors pose barriers to this goal. Major life events, mental health, health care infrastructure, political policy shifts, geographical scarcity and the disparity in practicing subspecialty cardiologists threatens to undermine care delivery.

She was also co-chair of congenital heart disease session (#424), “Neurodevelopment in Congenital Heart Disease: Across the Lifespan.”

Christopher Barnett, MD, MPH, a cardiologist, critical care specialist and CICU director at UCSF, presented “POCUS (Lung)” during special topic session (#826), “Hands-on Learning: Critical Care Cardiology – Survival Skills in the CICU V.” The session was a simulation learning experience, with five hands-on simulation stations, including common procedures, therapies and diagnostic tests frequently seen in a contemporary cardiac intensive care unit. This included high fidelity simulation with key clinical scenarios in invasive hemodynamic monitoring, point-of-care lung ultrasound, focused cardiac ultrasound, mechanical circulatory support and pericardiocentesis.

Barnett also served as a panelist for the special topic session (#5048), “Surviving in the CICU: Early Career Conundrums and Burnout in Critical Care Cardiology.”

Yousif Ahmad, MBBS, PhD, was a panelist for scientific session (#410), “Trials and Tribulations: Top Interventional Trials of 2024.” The session reviewed the top four interventional cardiology trials of 2024, which were pitted against each other in a March Madness-style bracket with one trial being crowned the winner by the audience after a lively series of debates. Ahmad reviewed the TRISCEND II Trial.

Poster Presentations:

Cell-Free DNA Predicts Cardiogenic Shock Severity and Outcomes (Moderated Poster Session #938)

Samuel Brusca, MD, presented “Cell-Free DNA Predicts Cardiogenic Shock Severity and Outcomes” during the moderated poster session “Critical Care Cardiology Perspectives: Shocking Headlines in Cardiogenic Shock,” and participated in a question and answer session following the presentation. Because management of cardiogenic shock (CS) remains challenging with limited biomarkers available to assess disease severity, cell-free DNA (cfDNA) has emerged as a tool to noninvasively quantitate tissue injury. This pilot study examined the utility of cfDNA to assess CS severity and in-hospital mortality. Brusca reported on whether cfDNA levels at CICU admission can predict CS severity and risk of in-hospital death.

Clinical Performance of Novel Machine-Learning-Based Antiarrhythmic Dosing Software: A Prospective Study (#1082-14)

Atrial fibrillation affects 38 million individuals worldwide and is responsible for $26 billion in healthcare costs in the U.S., with 75% of costs attributed to hospitalizations. Early rhythm control improves cardiovascular outcomes, although Class III antiarrhythmic drugs (AADs) require inpatient initiation due to the risk of QT prolongation. This limits access and increases healthcare costs, which disproportionately affects minority and underserved populations. First author Rachita Navara, MD, a cardiologist and UCSF research associate, and senior author Edward Gerstenfeld, MD, FACC, the Melvin Scheinman Endowed Professor of Medicine and chief of Cardiac Electrophysiology and Arrhythmia at UCSF, developed a novel machine learning algorithm and paired it with SafeBeat Rx technology to determine if the combination would enable safe outpatient AAD initiation and potentially improve access to care and reducing costs. They reported on the software platform’s potential to match clinician AAD dosing decisions.

Mavacamten Reduces Echo-Doppler Derived Pulmonary Artery Systolic Pressure in Obstructive Hypertrophic Cardiomyopathy Patients with Elevated Pulmonary Artery Systolic Pressure at Baseline (#1132-185)

Mavacamten (Mava) is an FDA-approved first-in-class cardiac myosin inhibitor that improves symptoms and reduces left ventricular outflow gradients (LVOTg) in symptomatic obstructive hypertrophic cardiomyopathy, but it has been unclear if Mava improves pulmonary pressures. First author Maka Gegenava, a UCSF research associate, and senior author Theodore Abraham, MD, FACC, FASE, examined Mava effects on echo-Doppler derived pulmonary artery systolic pressure in obstructive hypertrophic cardiomyopathy by reviewing clinical features and echo-Doppler findings and reported on these results.

Automated Detection of Rheumatic Mitral Valve Disease From 12-Lead ECG Using Deep Learning (#1166-50)

First author Stephanie Hu, UCSF medical student, and senior author Geoffrey Tison, MD, MPH, a cardiologist and co-director of the UCSF Center for Biosignal Research, conducted a study of rheumatic mitral valve disease (RMV), a significant global health concern in resource-limited settings. Because echocardiography is the standard diagnostic tool but requires specialized expertise and hardware, the investigators aimed to determine if a deep neural network (DNN) could detect RMV from electrocardiograms, a widely accessible diagnostic tool. They report that RMV can be detected from electrocardiogram waveforms alone using a DNN.

Comprehensive Automated ECG Analysis: Simultaneous Prediction of 68 Diagnostic Labels Using Deep Learning (#1166-52)

First author Stephanie Hu and senior author Geoffrey Tison, MD, presented a study about using deep learning models to expand diagnoses with automated electrocardiograms (ECG). While automated ECG interpretation has the potential to improve physician sensitivity and reduce inter-observer variability in clinical practice, training deep learning ECG models for less common conditions has been limited by the small number of diagnostic labels in available datasets. The researchers aimed to address this challenge by developing a deep neural network model trained on a large, well-labeled dataset with 68 cardiologist-reviewed diagnoses, significantly expanding the scope of automated ECG interpretation.

Please visit ACC25 for complete meeting abstract and session information.

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