JMIR Cardio

Introducing telemedicine in outpatient treatment may improve patient satisfaction and convenience. However, the optimal in-person visit interval for video-based telemedicine among patients with hypertension remains unreported in Japan.

Critical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention.

Cardiac rehabilitation (CR) is underused in the United States and globally, with participation disparities across gender, socioeconomic status, race, and ethnicities. The pandemic led to greater adoption of telehealth CR and mobile app use.

Limited data accuracy is often cited as a reason for caution in the integration of physiological data obtained from consumer-oriented wearable devices in care management pathways. The effect of decreasing accuracy on predictive models generated from these data has not been previously investigated.

Despite accumulating research on artificial intelligence–based electrocardiography (ECG) algorithms for predicting acute coronary syndrome (ACS), their application in stable angina is not well evaluated.

An accurate quantitative analysis of coronary artery stenotic lesions is essential to make optimal clinical decisions. Recent advances in computer vision and machine learning technology have enabled the automated analysis of coronary angiography.

Center-based cardiac rehabilitation programs (CRPs) reduce morbidity and mortality after an ischemic cardiac event; however, they are widely underused. Home-based CRP has emerged as an alternative to improve patient adherence; however, its safety and efficacy remain unclear, especially for older patients and female patients.

Mobile health (mHealth) interventions serve as a scalable opportunity to engage people with hypertension in self-measured blood pressure (SMBP) monitoring, an evidence-based approach to lowering blood pressure (BP) and improving BP control. Reach Out is an SMS text messaging–based SMBP mHealth trial that aims to reduce BP among hypertensive patients recruited from the emergency department of a safety net hospital in a low-income, predominately Black city.

eHealth technology can help patients with cardiovascular disease adopt and maintain a healthy lifestyle by supporting self-management and offering guidance, coaching, and tailored information. However, to support patients over time, eHealth needs to blend in with their needs, treatment, and daily lives. Just as needs can differ between patients, needs can change within patients over time. To better adapt technology features to patients’ needs, it is necessary to account for these changes in needs and contexts of use.

The prevalence of atrial fibrillation (AF) increases with age and can lead to stroke. Therefore, older adults may benefit the most from AF screening. However, older adult populations tend to lag more than younger groups in the adoption of, and comfort with, the use of mobile health (mHealth) apps. Furthermore, although mobile apps that can detect AF are available to the public, most are designed for intermittent AF detection and for younger users. No app designed for long-term AF monitoring has released detailed system design specifications that can handle large data collections, especially in this age group.

Exercise-based cardiac rehabilitation (CR) is recommended for coronary heart disease (CHD). However, poor uptake of and poor adherence to CR exercise programs have been reported globally. Delivering CR exercise classes remotely may remove some of the barriers associated with traditional hospital- or center-based CR.

It is well documented that individuals struggle to understand cardiovascular disease (CVD) percentage risk scores, which led to the development of heart age as a means of communicating risk. Developed for clinical use, its application in raising public awareness of heart health as part of a self-directed digital test has not been considered previously.