Highlights of Cardiovascular Disease Prevention Studies Presented at the 2023 American Heart Association Scientific Sessions.

PURPOSE OF REVIEW: Focused review highlighting ten select studies presented at the 2023 American Heart Association (AHA) Scientific Sessions. RECENT FINDINGS: Included studies assessed semaglutide and cardiovascular outcomes in overweight or obese patients without diabetes (SELECT); dapagliflozin in patients with acute myocardial infarction without diabetes (DAPA-MI); effects of dietary sodium on systolic blood pressure in middle-aged individuals (CARDIA-SSBP); long-term blood pressure control after hypertensive pregnancy with physician guided self-management (POP-HT); effect and safety of zilebesiran, an RNA interference therapy, for sustained blood pressure reduction (KARDIA-1); recaticimab add-on therapy in patients with non-familial hypercholesterolemia and mixed hyperlipidemia (REMAIN-2); efficacy and safety of lepodisiran an extended duration short-interfering RNA targeting lipoprotein(a); safety and pharmacodynamic effects of an investigational DNA base editing medicine that inactivates the PCSK9 gene and lowers LDL cholesterol (VERVE-101); automated referral to centralized pharmacy services for evidence-based statin initiation in high-risk patients; and effects of intensive blood pressure lowering in reducing risk of cardiovascular events (ESPRIT). Research presented at the 2023 AHA Scientific Sessions emphasized innovative strategies in cardiovascular disease prevention and management.

In-ear infrasonic hemodynography with a digital health device for cardiovascular monitoring using the human audiome.

Human bodily mechanisms and functions produce low-frequency vibrations. Our ability to perceive these vibrations is limited by our range of hearing. However, in-ear infrasonic hemodynography (IH) can measure low-frequency vibrations (<20 Hz) created by vital organs as an acoustic waveform. This is captured using a technology that can be embedded into wearable devices such as in-ear headphones. IH can acquire sound signals that travel within arteries, fluids, bones, and muscles in proximity to the ear canal, allowing for measurements of an individual's unique audiome. We describe the heart rate and heart rhythm results obtained in time-series analysis of the in-ear IH data taken simultaneously with ECG recordings in two dedicated clinical studies. We demonstrate a high correlation (r = 0.99) between IH and ECG acquired interbeat interval and heart rate measurements and show that IH can continuously monitor physiological changes in heart rate induced by various breathing exercises. We also show that IH can differentiate between atrial fibrillation and sinus rhythm with performance similar to ECG. The results represent a demonstration of IH capabilities to deliver accurate heart rate and heart rhythm measurements comparable to ECG, in a wearable form factor. The development of IH shows promise for monitoring acoustic imprints of the human body that will enable new real-time applications in cardiovascular health that are continuous and noninvasive.

COVID-19 telehealth preparedness: a cross-sectional assessment of cardiology practices in the USA.

Aim: The COVID-19 pandemic forced medical practices to augment healthcare delivery to remote and virtual services. We describe the results of a nationwide survey of cardiovascular professionals regarding telehealth perspectives. Materials & methods: A 31-question survey was sent early in the pandemic to assess the impact of COVID-19 on telehealth adoption & reimbursement. Results: A total of 342 clinicians across 42 states participated. 77% were using telehealth, with the majority initiating usage 2 months after the COVID-19 shutdown. A variety of video-based systems were used. Telehealth integration requirements differed, with electronic medical record integration being mandated in more urban than rural practices (70 vs 59%; p < 0.005). Many implementation barriers surfaced, with over 75% of respondents emphasizing reimbursement uncertainty and concerns for telehealth generalizability given the complexity of cardiovascular diseases. Conclusion: Substantial variation exists in telehealth practices. Further studies and legislation are needed to improve access, reimbursement and the quality of telehealth-based cardiovascular care.

As the COVID-19 pandemic was just beginning, the American College of Cardiology administered a survey to cardiology professionals across the USA regarding their preparedness for telehealth and video-visits. The results demonstrated rapid adoption of video based telehealth services, however revealed uncertainty for how to best use these services in different practice settings. Many providers expressed concerns about how these visits will be compensated, but fortunately federal agencies have dramatically changed the way telehealth is reimbursed as the pandemic has progressed. Further studies are needed to explore the impact of telehealth on healthcare inequality, however we hope that rather it serves to increase healthcare access to all.

Artificial intelligence in healthcare: a primer for medical education in radiomics.

The application of artificial intelligence (AI) to healthcare has garnered significant enthusiasm in recent years. Despite the adoption of new analytic approaches, medical education on AI is lacking. We aim to create a usable AI primer for medical education. We discuss how to generate a clinical question involving AI, what data are suitable for AI research, how to prepare a dataset for training and how to determine if the output has clinical utility. To illustrate this process, we focused on an example of how medical imaging is employed in designing a machine learning model. Our proposed medical education curriculum addresses AI's potential and limitations for enhancing clinicians' skills in research, applied statistics and care delivery.

The application of artificial intelligence (AI) to healthcare has generated increasing interest in recent years; however, medical education on AI is lacking. With this primer, we provide an overview on how to understand AI, gain exposure to machine learning (ML) and how to develop research questions utilizing ML. Using an example of a ML application in imaging, we provide a practical approach to understanding and executing a ML analysis. Our proposed medical education curriculum provides a framework for healthcare education which we hope will propel healthcare institutions to implement ML laboratories and training environments and improve access to this transformative paradigm.