Feature
Article
Author(s):
AI-enabled remote cardiac telemetry can help manage stress’s effects on high-risk populations.
Reports suggest that cardiac events see an uptick during election season. For example, in California, a Kaiser Permanente study revealed that stroke hospitalizations were reportedly 62% higher in the 2 days following the 2016 US election compared to prior weeks.1 Similarly, the same study notes that the days following the 2020 election saw a 42% increase in heart attacks and a 17% rise in overall cardiovascular events.2
A portable electrocardiogram monitor shows a digital display. Image Credit: © Andrew - stock.adobe.com
Stress of any kind has profound physiological impacts, especially on the cardiovascular system. While major stressors such as elections, holidays, and life changes affect many people, those with heart conditions are at even greater risk. Research and reports show that the risk of a heart attack increases greatly during seasonal periods of heightened stress for those with underlying heart conditions.3
As health care moves into an era of proactive interventions and increasingly sophisticated monitoring outside of the hospital, artificial intelligence (AI)-enabled remote cardiac monitoring is emerging as a powerful tool to help clinicians manage the effects of patients’ stress by detecting, predicting, and even potentially preventing stress-induced cardiac events among those most at risk.
This article explores the multifaceted impact of stress on cardiovascular health, unpacks the role of AI-enabled remote cardiac monitoring in managing its effects on high-risk populations, and provides actionable tips to control stress during the election season and beyond.
For individuals without known cardiac conditions, the physiological impacts of stress, such as elevated blood pressure and heart rate, often go unnoticed, as they don’t always produce clear symptoms. However, for the estimated 127.9 million US adults with some form of cardiovascular disease (tallied between 2017 and 2020) , these stress-induced responses can be more severe.4 Chronic stress can lead to higher risk of arrhythmias and may even be a precursor to serious events such as heart attacks, amplifying risks for individuals already dealing with conditions like coronary artery disease or heart failure.
Among traditionally low-risk populations, raising awareness of the connection between stress and cardiovascular health is foundational to recognizing symptoms early, when the opportunity for intervention is greatest. In higher-risk populations, advancements in AI and remote patient monitoring (RPM) go one step further, enabling patients and providers to manage the cardiac effects of stress proactively for the first time. These tools allow for continuous monitoring of stress-related changes in heart rate and rhythm, enabling timely interventions to mitigate the risk of serious events before they occur.
By shifting from reactive to proactive stress management, AI and RPM technologies are helping improve cardiovascular outcomes across diverse patient populations. Previously, cardiac patients relied on intermittent data collection for arrhythmia detection and condition monitoring. This approach left critical time periods in the fringes and crucial nonevent data under the radar. In reality, a continuous (as opposed to episodic) approach is required to proactively address the more than 700,000 potentially avoidable cardiac deaths each year.4 Through AI-powered detection, we can finally make continuous monitoring a standard of care for high-risk populations.
Modern virtual cardiac telemetry solutions collect and analyze large volumes of physiological data, such as heart rate, electrocardiogram results, and blood pressure. They do this continuously and in the natural context of a patient’s daily life. This allows AI to identify subtle variations in heart rhythms that may signal a developing issue well before a patient identifies symptoms, enabling earlier intervention. It also enables AI to discern more nuanced observations about patient health, including the relationship between stress levels and cardiac indicators.
One of the most powerful differentiators of AI is its superior predictive capability. By processing historical data alongside near real-time metrics, AI can recognize patterns that precede arrhythmias or cardiac events, particularly during periods of increased emotional or physical stress. Leading up to a political election, AI may be able to detect early warning signs in patients at risk—such as changes in heart rate variability—triggering an alert before a potential cardiac event occurs. This allows health care providers to take preventive action, like adjusting medications, recommending lifestyle changes, or offering stress-reduction techniques.
But cardiac care among those at high risk is not always about diagnosing a major condition or spotting a major event—it is often about disease management. AI’s strength also lies in its ability to personalize interventions and offer insight for more effective condition management. These algorithms can help clinicians create individualized risk profiles based on a patient’s medical history, lifestyle, and health data, then make recommendations that are tailored to their specific needs.
Whether it’s advising a temporary increase in beta blockers, scheduling a physician check-in, or suggesting immediate lifestyle adjustments, AI can assist clinicians in suggesting the most appropriate interventions for each patient and do so at scale. Over time, as AI systems learn from accumulating data, their predictive power only grows, enabling clinicians to better foresee and try therapies to potentially prevent arrhythmias and other cardiac events in the future.
AI-enabled virtual cardiac telemetry is a paradigm shift in the management of cardiac health among high-risk populations. But what about everyone else? While it is possible that these solutions may someday make their way into primary care paradigms, widespread awareness and active vigilance remain a patient’s best tools for combating stress-related cardiac effects.
Here are tailored recommendations based on risk levels, with ways to manage stress proactively and protect heart health during high-stress periods:
Low-Risk Individuals
For low-risk individuals, strategies should focus on mitigating stress levels on an ongoing basis before they produce significant symptoms. Techniques might include:
Moderate-Risk Individuals
For moderate-risk individuals, strategies should extend beyond mitigation to encompass monitoring and prevention. Some actions might include:
High-Risk Individuals
For high-risk individuals, strategies should be tightly integrated with the guidance of the patient’s clinician. Among other techniques, a clinician may recommend:
Stuart Long has been the CEO of InfoBionic.Ai since March 2017. He underscores the company’s commitment to widespread market adoption of its transformative wireless remote patient monitoring platform for chronic disease management. With more than 25 years of experience in the medical device market, Long brings expertise in achieving rapid commercial growth.
High-stress events like elections have a tangible impact on heart health, especially for those with existing conditions. Empowering patients through stress management strategies and recognizing early cardiac warning signs is essential in addressing this risk. By fostering cardiac vigilance and equipping high-risk individuals with powerful tools like AI-enabled remote cardiac monitoring, health care providers can make timely interventions in situations that might otherwise have tragic outcomes.
Reducing avoidable cardiac deaths on a larger scale relies on proactive, population-level strategies: Better patient education, accessible stress management resources, and continuous cardiac monitoring serve as crucial steps toward a healthier population. With these measures in place, we can improve clinical outcomes throughout the year, supporting patients in living healthier, more heart-conscious lives.
