Background

Cardiovascular Disease

Cardiovascular disease is the leading cause of death for both men and women in California. Major Adverse Cardiac Events (MACEs), like heart attack, stroke, and heart failure, result from complex biological and physiological factors as well as demographic and social determinants.

Many people experience a heart attack, stroke, or other complication of cardiovascular disease for preventable reasons, such as undertreatment, failure to take medicines, or lack of access to care.

Studies show that potentially preventable MACEs occur more often in younger women and racial/ethnic minorities. According to the researchers, "One reason for this is that early signs of disease can be easily missed, and also because people spend most of their life far away from a doctor or hospital where it is challenging to monitor disease progression."

While several lifestyle risk factors like smoking, physical inactivity, poor nutrition, and obesity are solidly associated with ischemic heart disease (IHD), patients often don't or won't adopt or maintain interventions to encourage positive behavior changes.

Remote Monitoring

Insight into a patient's condition in real-time and real-world situations allows clinicians to evaluate and possibly intervene in a potential medical emergency without needing to wait until the next in-office appointment.

Mobile health platforms can track patient-reported informatics (PRI), such as step counts, active minutes, sleep, heart rate, physical measures of stress, and other biometrics along with patient-reported outcome (PRO) data, such as levels of perceived stress, anxiety, depression, and health-related quality of life each week.

Considered alongside PRIs and PROs, biomarkers that circulate in the blood serve an important role in predicting risk of cardiovascular events. FDA-approved micro-sampling devices allow an individual to collect small volumes of blood remotely and send the samples to a hospital, where researchers can assess that patient's risk for MACEs by measure over 500 blood proteins representing a broad systemic response, such as inflammation, vascular reactivity, organ function, and fat content.

Project

To understand the potential to detect cardiovascular threats early enough for effective treatment or prevention, the research team pursued the question of whether physiological, biochemical, and psychosocial measurements could predict MACEs. They recruited 200 patients (aged 54-76 years) diagnosed with stable IHD and monitored them remotely with wearable biosensors for 12 months. Patients wore a specialized watch that measured activity, sleep, heart rate, and stress levels.

Additionally, patients reported their levels of anxiety, depression, and quality of life using a smartphone or computer. To supplement the passive monitoring, patients periodically sent a small finger prick blood sample by mail, allowing doctors to measure over 500 different blood chemicals. By combining these different types of data, the researchers sought out a "signal in the noise" to better predict who may be about to have a heart attack or stroke. The team also measured how this approach might be covered by insurance companies and hospital payers.

Supplemental Project

The team worked to enhance the prediction capabilities for an impending heart attack or stroke. They added several analyses and measurements, including an assessment for genomic risk for heart disease, AI-based modelling of electrical activity of the patient's heart, and the use of more frequently updated prediction scores. Additionally, the team explored in more detail why patient compliance with remote data collection is high, and they tested an alternative home blood collection device to determine if it improved sample quality and patient compliance.

Leverage of Funds

The research team established partnerships with industry, which supplemented state funds with materials, technical support, and other services. In addition, the host institution, Cedars-Sinai, contributed funds and waived indirect costs. In total, the research team leveraged its award of $1,423,261 to receive an additional $1,062,351 in materials and services and $446,000 of in-kind institutional support.

Research Team and Collaborators

Research Team

  • Cedars-Sinai Medical Center
    • Brennan Spiegel, MD, MSHS
    • C. Noel Bairey Merz, MD
    • Jennifer Van Eyk, PhD
    • Chrisandra Shufelt, MD
    • Janet Wei, MD
    • Margo Minissian, PhD, ACNP
  • University of California, Los Angeles
    • Peipei Ping, PhD
    • Corey Arnold, PhD

Collaborators

  • Agilent
  • Beckman Coulter
  • DocuSign
  • Fitabase
  • Fitbit
  • HealthLoop
  • Neoteryx
  • SCIEX
  • Tasso
  • Thermo Fisher Scientific