Detecting early physiologic changes through cardiac implantable electronic device data among patients with COVID-19.
Academic Article
Overview
abstract
Background: Cardiac implantable electronic devices (CIEDs) may enable early identification of COVID-19 to facilitate timelier intervention. Objective: To characterize early physiologic changes associated with the onset of acute COVID-19 infection, as well as during and post-acute infection, among patients with CIEDs. Methods: CIED sensor data from March 2020 - February 2021 from 286 patients with a CIED were linked to clinical data from electronic health records. Three cohorts were created: known COVID-positive (n=20), known COVID-negative (n=166), and a COVID-untested control group (n=100) included to account for testing bias. Associations between changes in CIED sensors from baseline (including HeartLogic Index, a composite index predicting worsening heart failure) and COVID-19 status were evaluated using logistic regression models, Wilcoxon signed-rank tests, and Mann-Whitney U tests. Results: Significant differences existed between the cohorts by race, ethnicity, CIED device type, and medical admissions. Several sensors changed earlier for COVID-positive vs. COVID-negative patients: HeartLogic Index (mean 16.4 vs. 9.2 days [p=0.08]), respiratory rate (mean 8.5 vs. 3.9 days [p=0.01], and activity (mean 8.2 vs. 3.5 days [p=0.008]). Respiratory rate during the seven days before testing significantly predicted a positive versus negative COVID-19 test, adjusting for age, gender, race, and device type (OR 2.31 [95% CI 1.33-5.13]). Conclusions: Physiologic data from CIEDs could signal early signs of infection that precede clinical symptoms, which may be used to support early detection of infection to prevent decompensation in this at-risk population.
