Novel findings of respiratory rate increases using the multisensor HeartLogic heart failure monitoring algorithm in COVID-19-positive patients: a case series

PRecision Event Monitoring for PatienTs with Heart Failure using HeartLogic (PREEMPT-HF) study design and enrolment

AIMS

The HeartLogic multisensor index has been found to be a sensitive predictor of worsening heart failure (HF). However, there is limited data on this index's association and its constituent sensors with HF readmissions.

METHODS AND RESULTS

The PREEMPT-HF study is a global, multicentre, prospective, observational, single-arm, post-market study. HF patients with an implantable defibrillator device or cardiac resynchronization therapy with defibrillator with HeartLogic capabilities were eligible if sensor data collection was turned on and the HeartLogic feature was not enabled. Thus, the HeartLogic Index/alert and heart sounds sensor trends were unavailable via the LATITUDE remote monitoring system to clinicians (blinded). Evaluation of subject medical records at 6 months and a final in-clinic visit at 12 months was required for collection of all-cause hospitalizations and HF outpatient visits. The purpose of this study is exploratory, no formal hypothesis tests are planned, and no adjustment for multiple testing will be performed. A total of 2183 patients were enrolled at 103 sites between June 2018 and June 2020. A significant proportion of the patients were implanted with implantable defibrillator devices (39%) versus cardiac resynchronization therapy with defibrillator (61%); were female (27%); over 65 (61%); New York Heart Association class I (13%), II (53%), and III (33%); ejection fraction < 25% (21%); ischaemic (50%); and with a history of renal dysfunction (23%).

CONCLUSIONS

The PREEMPT study will provide clinical data and blinded sensor trends for the characterization of sensor changes with HF readmission, tachyarrhythmias, and event subgroups. These data may help to refine the clinical use of HeartLogic and to improve patient outcomes.

Detecting early physiologic changes through cardiac implantable electronic device data among patients with COVID-19

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 after acute infection, among patients with CIEDs.

Methods

CIED sensor data from March 2020 to 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 = .08]), respiratory rate (mean 8.5 vs 3.9 days [P = .01], and activity (mean 8.2 vs 3.5 days [P = .008]). Respiratory rate during the 7 days before testing significantly predicted a positive vs negative COVID-19 test, adjusting for age, sex, race, and device type (odds ratio 2.31 [95% confidence interval 1.33-5.13]).

Conclusion

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.

A reproducible sensor pattern to suspect COVID19 pulmonary infection with LATITUDETM . Case report and literature review

A 78 year‐old patient with postischaemic dilated cardiomyopathy and severely reduced ejection fraction was implanted with a Boston Scientific RESONATE X4 CRT‐D and followed by LATITUDE remote monitoring platform. From the end of January to the end of March 2021 he was hospitalized for COVID19 pneumonia followed by two episodes of acute heart decompensation with bilateral pleural effusion. We remotely followed the patient and identified a typical Heart Logic sensor pattern linked to the COVID19 pneumonia, different from the one linked to the heart failure (HF). We eventually made a literature review on the topic.

Emerging Implantable Device Technology for Patients at the Intersection of Electrophysiology and Heart Failure Interdisciplinary Care

Cardiac implantable electronic devices (CIEDs), including implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT), are part of guideline- indicated treatment for a subset of patients with heart failure with reduced ejection fraction (HFrEF). Current technological advancements in CIEDs have allowed the detection of specific patient physiologic parameters used for forecasting clinical decompensation through algorithmic, multiparameter remote monitoring. Other recent emerging technologies, including cardiac contractility modulation (CCM) and baroreflex activation therapy (BAT), may provide symptomatic or physiologic benefit in patients without an indication for CRT. Our goal in this state-of-the-art review is to describe the commercially available new technologies, purported mechanisms of action, evidence surrounding their clinical role, limitations, and future directions. Finally, we underline the need for standardized workflow and close interdisciplinary management of this population to ensure the delivery of high-quality care.

Multiparameter diagnostic sensor measurements in heart failure patients presenting with SARS-CoV-2 infection

Aims

Implantable device‐based sensor measurements including heart sounds, markers of ventilation, and thoracic impedance have been shown to predict heart failure (HF) hospitalizations. We sought to assess how these parameters changed prior to COVID‐19 (Cov‐19) and how these compared with those presenting with decompensated HF or pneumonia.

Methods and results

This retrospective analysis explores patterns of changes in daily measurements by implantable sensors in 10 patients with Cov‐19 and compares these findings with those observed prior to HF (n = 88) and pneumonia (n = 12) hospitalizations from the MultiSENSE, PREEMPT‐HF, and MANAGE‐HF trials. The earliest sensor changes prior to Cov‐19 were observed in respiratory rate (6 days) and temperature (5 days). There was a three‐fold to four‐fold greater increase in respiratory rate, rapid shallow breathing index, and night heart rate compared with those presenting with HF or pneumonia. Furthermore, activity levels fell more in those presenting with Cov‐19, a change that was often sustained for some time. In contrast, there were no significant changes in 1st or 3rd heart sound (S₁ and S₃) amplitude in those presenting with Cov‐19 or pneumonia compared with the known changes that occur in HF decompensation.

Conclusions

Multi‐sensor device diagnostics may provide early detection of Cov‐19, distinguishable from worsening HF by an extreme and fast rise in respiratory rate along with no changes in S3.