Biometric and Psychometric Remote Monitoring and Cardiovascular Risk Biomarkers in Ischemic Heart Disease
Open Access
- 15 September 2020
- journal article
- research article
- Published by Ovid Technologies (Wolters Kluwer Health) in Journal of the American Heart Association
- Vol. 9 (18)
- https://doi.org/10.1161/jaha.120.016023
Abstract
Background Patients with stable ischemic heart disease represent a heterogeneous population at variable risk for major adverse cardiac events (MACE). Because MACE typically occurs outside the hospital, we studied whether biometric and psychometric remote patient monitoring are associated with MACE risk biomarkers. Methods and Results In 198 patients with stable ischemic heart disease (mean age 65±11 years, 60% women), we evaluated baseline measures, including biometric (FitBit 2) and psychometric (acquired via smartphone‐administered patient‐reported outcomes) remote monitoring, in the PRE‐MACE (Prediction, Risk, and Evaluation of Major Adverse Cardiac Events) study. In multivariable adjusted regression analyses, we examined the association of these measures with biomarkers of MACE risk, including NT‐proBNP (N‐terminal pro‐b‐type natriuretic peptide), u‐hs‐cTnI (ultra‐high sensitivity cardiac‐specific troponin I), and hs‐CRP (high‐sensitivity C‐reactive) protein. Both biometric and psychometric measures were associated with NT‐proBNP. Specifically, step count, heart rate, physical activity, global health score, and physical function score were all inversely related, whereas physical limitation score was directly related (P≤0.05 for all). However, only biometric measures (step count and heart rate) were associated with u‐hs‐cTnI (inversely related, PP≤0.05). Conclusions In stable ischemic heart disease patients, remotely monitored measures were associated with MACE risk biomarkers. Both biometric and psychometric measures were related to NT‐proBNP. In contrast, biometric measures were uniquely related to u‐hs‐cTnI, while psychometric indices were uniquely related to hs‐CRP. Further investigation could assess the predictive value of these metrics for MACE in ischemic heart disease.Keywords
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