Abstract:The severe acute respiratory syndrome novel coronavirus-2 pandemic has established a new set of challenges to health care delivery. Remotely monitored physiologic sensors on implantable cardiac devices can provide insight into the differential diagnosis of dyspnea in the heart failure population. We report on a unique pattern of sensor deviations that seem to occur specifically with severe acute respiratory syndrome novel coronavirus-2 infection.
“… 18 Numerous individual case studies with HeartLogic capable devices and SARS‐CoV‐2 infections have also suggested that individual sensors may help identify patients who are COVID‐19 positive, even before patients themselves report symptoms. 19 , 20 , 21 , 22 The sensor changes reported in these individual cases are consistent with the quantitative trends that we report here, including increasing respiratory rate and impedance.…”
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 (S
1
and S
3
) 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.
“… 18 Numerous individual case studies with HeartLogic capable devices and SARS‐CoV‐2 infections have also suggested that individual sensors may help identify patients who are COVID‐19 positive, even before patients themselves report symptoms. 19 , 20 , 21 , 22 The sensor changes reported in these individual cases are consistent with the quantitative trends that we report here, including increasing respiratory rate and impedance.…”
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 (S
1
and S
3
) 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.
“…118 However, the utility of this technology in differentiating HF from COVID-19related lung injury yielded mixed results. 119,120 The post-pandemic world of remote monitoring and telemedicine for patients with HF is likely to include all forms of care including virtual, in-person, and remote assessments. Wearables will may see accelerated adoption, 121 as smartwatch heart rate and rhythm monitoring may effectively trigger the need to seek medical attention.…”
Section: Challenges and Innovations In Hf Care Delivery During The Pandemicmentioning
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
“…The use of remote monitoring and telemedicine was forever changed by the COVID‐19 pandemic and are now more firmly entrenched in healthcare delivery than ever before. Multiple publications have also shown how the HeartLogic sensors are directly impacted in patients that contracted COVID‐19 39–44 . As of 6 October 2020, six subjects from PREEMPT were reported to have presented to the hospital with COVID‐19 and were included in an analysis comparing sensor changes with COVID‐19 to those presenting with decompensated HF or pneumonia 45 .…”
Section: Discussionmentioning
confidence: 99%
“…Multiple publications have also shown how the HeartLogic sensors are directly impacted in patients that contracted COVID‐19. 39 , 40 , 41 , 42 , 43 , 44 As of 6 October 2020, six subjects from PREEMPT were reported to have presented to the hospital with COVID‐19 and were included in an analysis comparing sensor changes with COVID‐19 to those presenting with decompensated HF or pneumonia. 45 COVID‐19 was distinguishable from worsening HF by an extreme and fast rise in respiratory rate and no changes in S3.…”
AimsThe 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 resultsThe 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%).ConclusionsThe 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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.