AI is rapidly transforming the medical industry, as many in healthcare may find themselves challenged to deliver effective, high-quality care and transform care at scale while simultaneously combating shortages in the workforce. AI algorithms are being developed specifically for the healthcare workforce. These innovative systems are helping medical professionals improve their work through diagnoses and treatment, developing personalized treatment plans, predicting operation success, and surveilling and forecasting disease outbreaks.
“As AI develops, it becomes increasingly important for the interventional cardiovascular field to utilize these technologies to improve patient care in areas where it may currently need support,” said SCAI President James B. Hermiller, MD, MSCAI. “We hope such technologies can help ease the burden on healthcare workers by enhancing the detection and treatment of common cardiovascular conditions with the goal of improving patient care and outcomes.”
Wearables, When Paired with AI, Detect a Cardiovascular Event an Hour Before it Occurs, Similar to Hospital-Grade Monitors
Traditional hospital-based tracking systems that use GPS, Wi-Fi, or Bluetooth face recurrent issues such as late detection of heart issues, lack of accessibility to patients, and inadequate heart monitoring. However, cardiovascular care is improving with the introduction of noninvasive digital health technologies (DHTs) powered by AI, like wearable biosensors, electrocardiograms (ECG), and remote patient monitoring (RPM). This study shows how DHTs enable constant tracking, further enhancing early cardiovascular diagnosis, risk assessment, and improved patient outcomes.
Researchers analyzed late-breaking clinical trials from 2023-2024 where noninvasive heart monitoring devices were updated with AI. The study aimed to evaluate the accuracy of AI digital health diagnoses, their effectiveness in clinical settings, and their impact on healthcare delivery.
Findings demonstrate that DHTs can detect a cardiovascular event up to an hour before it occurs, which suggests such devices may produce diagnoses in line with ECGs performed in hospitals. Smartwatches and portable ECGs with sensitivity levels over 90% were able to detect AFib before occurring. In the CardioMEMSTM Heart Sensor Monitor Pressure to HaveImprove Outcomes in Heart Failure Patients NYHA Class III (CHAMPION) trial, remote tracking showed that hospitals using AI and wearable technology saw a 33.1% decrease in heart failure patients and a 20-30% increase in medication adherence.
“Hospitals need to start using new noninvasive digital health tools if they want to better monitor their patients and detect cardiovascular events before they occur,” said Nishat Tamanna, MD, MBBS, and lead author of the study. “AI and RPM systems can help detect heart problems early, monitor patient health continuously, and improve treatment plans to make heart care more efficient and accessible for both patients and hospital staff.”
Triage Algorithm Improved Management of Cardiac Arrest Survivors Leading to 30% Reduction in Unnecessary Testing and Improvement of Care Decisions
Out-of-hospital cardiac arrest (OHCA) remains a leading cause of global deaths, while survivors are burdened with long-term neurological and cardiovascular complications. Coronary angiographies (CAGs), a heart-imaging procedure to visualize an artery blockage, are often completed in patients with OHCA to determine if a heart attack was the cause, which can support treatment decisions. However, it can be difficult for staff to decide if a CAG is needed after a patient is revived due to the potential delay in intensive care management and treatment. The Detroit Medical Center Heart Hospital determined conflicting practices between emergency and cardiology teams, leading to unnecessary recurrent use of the catheterization laboratory and equipment for CAGs. To address this discrepancy, researchers developed a triage algorithm to determine the order of treatment priority based on previous guidelines and recent OHCA trials.
The algorithm was set to analyze retrospective data across two data sets: data from the year prior to and nine months following its adoption. The analysis aimed to enhance hospital staff decision-making, reduce additional interventions, and prioritize patient neuroprotection.
The retrospective analysis comparing both data sets found a 30% reduction in unnecessary OHCA catheterization lab use and a 40% decrease in unwarranted heart attack alerts after the triage algorithm was implemented. Additional findings demonstrated improved team decisions, cutting costs, and streamlined workflow. Key findings enabled more accurate decisions for physicians to prescribe a CAG which would be inappropriately overutilized in such instances. Keeping up with the guidelines and data from the most recent trials.
“Our team was pleasantly surprised to see improvements in OCHA management, which allowed physicians to provide more timely care and alternative diagnoses when needed. By implementing a tailored algorithm that determines treatment priorities, we were able to reduce unnecessary cath lab visits and the risks and costs associated with those visits, as well as help our emergency department colleagues navigate these very critical patients in a more streamlined way, keeping up with the most recent data,” said Abdalaziz Awadelkarim, MD, Wayne State University in Detroit, Mich., and lead author of the study.”
Further research is warranted to refine the algorithm and explore advanced interventions like extracorporeal life support for certain patients.
This abstract is published in the SCAI Abstract Supplement, which appears in SCAI’s official journal, JSCAI. You can access it here: https://doi.org/10.1016/j.jscai.2025.102670.
Session Details:
“Noninvasive Digital Health Technology: Revolutionizing Cardiovascular Care Through AI and Wearable Devices – A Systematic Review of Late-Breaking Clinical Trials (2023–2024)”
Saturday, May 3, 2025;10:25-11:45 AM ET
Walter E. Washington Convention Center, SCAI Central, Hall D
“The Detroit Medical Center OHCA Algorithm: A Data-Driven Approach to Optimize Out-of-Hospital Cardiac Arrest Management by Reducing Unnecessary Cath Lab Activations and Enhancing Neuroprotection”
Friday, May 2, 2025;1:31-1:39 PM ET
Walter E. Washington Convention Center, Hall D, Theater 1
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About Society for Cardiovascular Angiography & Interventions (SCAI)
The Society for Cardiovascular Angiography & Interventions, established in 1978, stands as the primary nonprofit medical society dedicated to representing invasive and interventional cardiology. SCAI's mission is to guide the global interventional cardiovascular community by fostering education, advocacy, research, and upholding standards for quality patient care. For more than 40 years, SCAI has exemplified professional excellence and innovation worldwide, cultivating a reputable community of over 5,000 members committed to advancing medical science and providing life-saving care for individuals, both adults and children, affected by cardiovascular disease. For more information, visit https://scai.org/.
For more information about the SCAI 2025 Scientific Sessions, visit https://scai.org/scai-2025-scientific-sessions. Follow @SCAI on X for the latest heart health news and use #SCAI2025 to follow the latest discussions.
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