Early Prediction of Major Adverse Cardiovascular Events Using Remote Monitoring

Principal Investigators

Brennan Spiegel, MD, MSHS
Director of Health Services Research, Cedars-Sinai Medical Center

C. Noel Bairey Merz, MD
Director of Barbara Streisand Women's Heart Center, Cedars-Sinai Medical Center

Jennifer Van Eyk, PhD
Director of Advanced Clinical Biosystems Institute, Cedars-Sinai Medical Center

Background

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 reasons that are within the realm of being prevented: they were undertreated, not taking their medicines, or not receiving the care they needed in the first place. Studies have shown that this occurs more often with 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 are solidly associated with ischemic heart disease (IHD), such as smoking, physical inactivity, poor nutrition, and obesity, interventions designed to induce positive behavior changes are often ineffective due to poor adherence.

Remote monitoring

Patient-reported informatics (PRI) is the umbrella term that includes step counts, active minutes, sleep parameters, heart rate, measures of physiologic stress, and other biometrics. Patient-reported outcome (PRO) data is generated from mobile health platforms and reflects self-reported levels of perceived stress, anxiety, depression, and health-related quality of life each week. With continuous insight of participants in real-time and real-world situations, clinicians could evaluate a patient and possibly intervene without needing to wait until the next in-office appointment.

Biomarkers that circulate in the blood also serve an important role in predicting risk of cardiovascular events and should be considered alongside remote monitoring of PROs and PRIs. FDA-approved micro-sampling devices are available and allow an individual to collect small volumes of blood remotely. When patients mail their samples to the hospital, researchers can measure over 500 blood proteins representing a broad systemic response, such as inflammation, vascular reactivity, organ function, and fat content.

Project Summary

To understand whether cardiovascular threats can be detected early enough for effective treatment or prevention, the research team pursued the question of whether physiological, biochemical, and psychosocial measurements could predict MACEs. They did this by recruiting 200 patients (aged 54-76 years) diagnosed with stable IHD and remotely monitoring them 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 could be covered by insurance companies and hospital payers.

Supplemental Project

The team is working to further the prediction capabilities for an impending heart attack or stroke. They will add 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 will explore in more detail why patient compliance with remote data collection has been so high, and they will test an alternative home blood collection device to determine if it improves sample quality and patient adherence.

Research Team and Collaborators

Cedars-Sinai Medical Center

  • 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

Agilent

Beckman Coulter

DocuSign

Fitabase

Fitbit

HealthLoop

Neoteryx

SCIEX

Tasso

Thermo Fisher Scientific

UC Los Angeles

Project team photos

L to R: Sandy Joung; Janet Wei, MD; Qin Fu, PhD; Kelly N. Mouapi, PhD; Jennifer Van Eyk, PhD; Brennan Spiegel, MD; Noel C. Bairey Merz, MD; Shivani Dhawan, MS; Irene van den Broek, PhD; Gilhad Khanian

Leverage of Funds

The research team was successful in establishing partnerships with industry, which supplemented state funds with in 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 their award of $1,423,261 to receive an additional $1,062,351 in materials and services and $446,000 of in-kind institutional support.