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Integration of Brain Tissue Saturation Monitoring in Cardiopulmonary Exercise Testing in Patients with Heart Failure
Published on: October 1, 2019
A protocol integrating remote patient monitoring patient reported outcomes and cardiovascular biomarkers
Chrisandra Shufelt1, Eldin Dzubur2, Sandy Joung1
11Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA.
Insights
The PRE-MACE study uses remote monitoring with biosensors and biomarkers to predict major adverse cardiac events (MACE) in stable ischemic heart disease patients. This approach aims to improve outcomes and reduce healthcare costs by identifying MACE precursors early.
Area of Science:
- Cardiology
- Digital Health
- Biomarker Research
Background:
- Major adverse cardiac events (MACE) remain a concern in stable ischemic heart disease despite current treatments.
- Early identification of MACE precursors is crucial for timely intervention and improved patient outcomes.
- Current monitoring methods may not capture subtle physiological changes preceding MACE.
Purpose of the Study:
- To evaluate the PRE-MACE study's protocol for remote patient monitoring in cardiology.
- To assess the ability of remote monitoring (biosensors, biomarkers, patient-reported outcomes) to predict MACE and MACE biomarkers in stable ischemic heart disease.
- To determine the adherence and cost-effectiveness of this remote monitoring approach.
Main Methods:
- Utilizing continuous remote monitoring via wearable biosensors.
- Measuring biomarkers through plasma and at-home micro-sampling blood collection.
- Collecting patient-reported outcomes on stress, anxiety, depression, and quality of life.
Main Results:
- The study aims to establish cross-sectional correlations between remote monitoring data and MACE.
- It will assess the predictive capability of remote monitoring for MACE biomarkers and incident MACE.
- Adherence and cost-effectiveness of remote monitoring and blood sampling will be evaluated.
Conclusions:
- Remote monitoring using biosensors, biomarkers, and patient-reported outcomes can identify MACE precursors in stable ischemic heart disease.
- This intervention holds potential for improving patient outcomes by predicting MACE between clinical visits.
- Successful implementation could reduce the financial burden associated with MACE.
Abstract:
We describe the protocol, design, and methodology of the Prediction, Risk, and Evaluation of Major Adverse Cardiac Events (PRE-MACE) study as a multicomponent remote patient monitoring in cardiology. Using biosensor, biomarkers, and patient-reported outcomes in participants with stable ischemic heart disease, the PRE-MACE study is designed to measure cross-sectional correlations and establish the ability of remote monitoring to predict major adverse cardiovascular event (MACE) biomarkers and incident MACE at baseline and 12-month follow-up. It will further assess the adherence and cost-effectiveness of remote monitoring and blood sampling over the initial months. Despite medication and lifestyle changes, patients with cardiovascular disease can experience MACE due to undertreatment, poor adherence, or failure to recognize clinical or biochemical changes that presage MACE. Identifying patients using remote monitoring to detect MACE forerunners has potential to improve outcomes, avoid MACE, and reduce resource utilization. Data collection will include: (1) continuous remote monitoring using wearable biosensors; (2) biomarker measurements using plasma and at-home micro-sampling blood collection; and (3) patient-reported outcomes to monitor perceived stress, anxiety, depression, and health-related quality of life. Two hundred participants will be followed for 90 days with a subset (n = 80) monitored for 180 days. All participants will be followed up for MACE at 12 months.The PRE-MACE study will utilize remote monitoring with biosensors, biomarkers, and patient-reported outcomes to identify intermediate biomarkers of MACE in patients with stable ischemic heart disease. If shown to be effective, this intervention can be utilized between health visits to predict MACE and reduce financial impact of MACE.
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