Combined heart failure device diagnostics identify patients at higher risk of subsequent heart failure hospitalizations: results from PARTNERS HF (Program to Access and Review Trending Information and Evaluate Correlation to Symptoms in Patients With Heart Failure) study

Heart Failure Management through Telehealth: Expanding Care and Connecting Hearts

Heart failure (HF) is a leading cause of morbidity worldwide, imposing a significant burden on deaths, hospitalizations, and health costs. Anticipating patients' deterioration is a cornerstone of HF treatment: preventing congestion and end organ damage while titrating HF therapies is the aim of the majority of clinical trials. Anyway, real-life medicine struggles with resource optimization, often reducing the chances of providing a patient-tailored follow-up. Telehealth holds the potential to drive substantial qualitative improvement in clinical practice through the development of patient-centered care, facilitating resource optimization, leading to decreased outpatient visits, hospitalizations, and lengths of hospital stays. Different technologies are rising to offer the best possible care to many subsets of patients, facing any stage of HF, and challenging extreme scenarios such as heart transplantation and ventricular assist devices. This article aims to thoroughly examine the potential advantages and obstacles presented by both existing and emerging telehealth technologies, including artificial intelligence.

An Era of Digital Healthcare-A Comprehensive Review of Sensor Technologies and Telehealth Advancements in Chronic Heart Failure Management

Heart failure (HF) is a multi-faceted, complex clinical syndrome characterized by significant morbidity, high mortality rate, reduced quality of life, and rapidly increasing healthcare costs. A larger proportion of these costs comprise both ambulatory and emergency department visits, as well as hospital admissions. Despite the methods used by telehealth (TH) to improve self-care and quality of life, patient outcomes remain poor. HF management is associated with numerous challenges, such as conflicting evidence from clinical trials, heterogeneity of TH devices, variability in patient inclusion and exclusion criteria, and discrepancies between healthcare systems. A growing body of evidence suggests there is an unmet need for increased individualization of in-hospital management, continuous remote monitoring of patients pre and post-hospital admission, and continuation of treatment post-discharge in order to reduce re-hospitalizations and improve long-term outcomes. This review summarizes the current state-of-the-art for HF and associated novel technologies and advancements in the most frequently used types of TH (implantable sensors), categorizing devices in their preclinical and clinical stage, bench-to-bedside implementation challenges, and future perspectives on remote HF management to improve long-term outcomes of HF patients. The Review also highlights recent advancements in non-invasive remote monitoring technologies demonstrated by a few pilot observational prospective cohort studies.

Ambulatory Risk Stratification for Worsening Heart Failure in Patients with Reduced and Preserved Ejection Fraction Using Diagnostic Parameters Available in Implantable Cardiac Monitors

BACKGROUND

Ambulatory risk stratification for worsening heart failure (HF) using diagnostics measured by insertable cardiac monitors (ICM) may depend on the left ventricular ejection fraction (LVEF). We evaluated risk stratification performance in patients with reduced versus preserved LVEF.

METHODS

ICM patients with a history of HF events (HFEs) were included from the Optum® de-identified Electronic Health Record dataset merged with ICM device-collected data during 2007-2021. ICM measures nighttime heart rate (NHR), heart rate variability (HRV), atrial fibrillation (AF) burden, rate during AF, and activity duration (ACT) daily. Each diagnostic was categorized into high, medium, or low risk using previously defined features. HFEs were HF-related inpatient, observation unit, or emergency department stays with IV diuresis administration. Patients were divided into two cohorts: LVEF ≤ 40% and LVEF > 40%. A marginal Cox proportional hazards model compared HFEs for different risk groups.

RESULTS

A total of 1020 ICM patients with 18,383 follow-up months and 301 months with HFEs (1.6%) were included. Monthly evaluations with a high risk were 2.3, 4.2, 5.0, and 4.5 times (p < 0.001 for all) more likely to have HFEs in the next 30 days compared to those with a low risk for AF, ACT, NHR, and HRV, respectively. HFE rates were higher for patients with LVEF > 40% compared to LVEF ≤ 40% (2.0% vs. 1.3%), and the relative risk between high-risk and low-risk for each diagnostic parameter was higher for patients with LVEF ≤ 40%.

CONCLUSIONS

Diagnostics measured by ICM identified patients at risk for impending HFEs. Patients with preserved LVEF showed a higher absolute risk, and the relative risk between risk groups was higher in patients with reduced LVEF.

A Novel Heart Failure Diagnostic Risk Score Using a Minimally Invasive Subcutaneous Insertable Cardiac Monitor

BACKGROUND

The authors tested the hypothesis that physiological information from sensors within a minimally invasive, subcutaneous, insertable cardiac monitor (ICM) could be used to develop an ambulatory heart failure risk score (HFRS) to accurately identify heart failure (HF) patients, across the ejection fraction spectrum, at high risk of an impending worsening heart failure event (HFE).

OBJECTIVES

The purpose of this study was to examine performance of ICM-based, multiparameter, dynamic HFRS to predict HFEs in patients with NYHA functional class II/III HF.

METHODS

In 2 observational cohorts, HF patients were implanted with an ICM; subcutaneous impedance, respiratory rate, heart rate and variability, atrial fibrillation burden, ventricular rate during atrial fibrillation, and activity duration were combined into an HFRS to identify the probability of HFE within 30 days. Patients and providers were blinded to the data. HFRS sensitivity and unexplained detection rate were defined in 2 independent patient population data sets. HFEs were defined as hospitalization, observation unit, or emergency department visit with a primary diagnosis of HF, and intravenous diuretic treatment.

RESULTS

First data set (development): 42 patients had 19 HFE; second data set (validation): 94 patients had 19 HFE (mean age 66 ± 11 years, 63% men, 50% with LVEF ≥40%, 80% NYHA functional class III). Using a high-risk threshold = 7.5%, development and validation data sets: sensitivity was 73.7% and 68.4%; unexplained detection rate of 1.4 and 1.5 per patient-year; median 47 and 64 days early warning before HFE.

CONCLUSIONS

ICM-HFRS provides a multiparameter, integrated diagnostic method with the ability to identify when HF patients are at increased risk of heart failure events. (Reveal LINQ Evaluation of Fluid [REEF]; NCT02275923, Reveal LINQ Heart Failure [LINQ HF]; NCT02758301, Algorithm Using LINQ Sensors for Evaluation and Treatment of Heart Failure [ALLEVIATE-HF]; NCT04452149).

New models for heart failure care delivery

Heart failure (HF) is a common disease with increasing prevalence around the world. There is high morbidity and mortality associated with poorly controlled HF along with increasing costs and strain on healthcare systems due to a high rate of rehospitalization and resource utilization. Despite the establishment of clear evidence-based guideline directed medical therapies (GDMT) proven to improve HF morbidity and mortality, there remains significant clinical inertia to optimizing HF patients on GDMT. Only a minority of HF patients are prescribed on all four classes of GDMT. To bridge the gap between the vulnerable population of HF patients and lifesaving GDMT, HF implementation is of increasing importance. HF implementation involves strategies and techniques to improve GDMT optimization along with other modalities to improve HF management. HF implementation meets patients where they are, including at the time of acute decompensation in the inpatient setting, at the vulnerable discharge stage, and at the chronic management stage in the outpatient setting. Inpatient HF implementation strategies include protocolized rapid titration of GDMT, site-level audit-and-feedback, virtual GDMT optimization teams, and electronic health record notifications and alerts. Discharge HF implementation strategies include education at patient and provider levels, discharge summaries, and HF transitional programs. Outpatient HF implementation strategies include digital innovations such as electronic health record utilization and mobile applications, population level strategies such as registries and clinical dashboards), changes in HF team structure and member roles, remote monitoring with implanted devices and telemonitoring, and hospital at home care model. With a growing population of HF patients, there is an increasing need for novel and creative HF implementation and monitoring methods.

Telemedicine for the treatment of heart failure: new opportunities after COVID-19

ABSTRACT

During the Coronavirus Disease 2019 (COVID-19) pandemic, the epidemiology of heart failure significantly changed with reduced access to health system resources and a worsening of patients' outcome. Understanding the causes of these phenomena could be important to refine the management of heart failure during and after the pandemic. Telemedicine was associated with an improvement in heart failure outcomes in several studies; therefore, it may help in refining the out-of-hospital care of heart failure. In this review, the authors describe the changes in heart failure epidemiology during the COVID-19 pandemic; analyse available evidence on use and benefit of telemedicine during the pandemic and prepandemic periods; and discuss approaches to optimize the home-based or outpatient heart failure management in the future, beyond the pandemic.

Heart Failure Remote Monitoring: A Review and Implementation How-To

Heart failure (HF) is a significant clinical and financial burden worldwide. Remote monitoring (RM) devices capable of identifying early physiologic changes in decompensation have the potential to reduce the HF burden. However, few trials have discussed at length the practical aspects of implementing RM in real-world clinical practice. The present paper reviews current RM devices and clinical trials, focusing on patient populations, outcomes, data collection, storage, and management, and describes the implementation of an RM device in clinical practice, providing a pragmatic and adaptable framework.

Remote multiparametric monitoring and management of heart failure patients through cardiac implantable electronic devices

In this review we focus on heart failure (HF) which, as known, is associated with a substantial risk of hospitalizations and adverse cardiovascular outcomes, including death. In recent years, systems to monitor cardiac function and patient parameters have been developed with the aim to detect subclinical pathophysiological changes that precede worsening HF. Several patient-specific parameters can be remotely monitored through cardiac implantable electronic devices (CIED) and can be combined in multiparametric scores predicting patients' risk of worsening HF with good sensitivity and moderate specificity. Early patient management at the time of pre-clinical alerts remotely transmitted by CIEDs to physicians might prevent hospitalizations. However, it is not clear yet which is the best diagnostic pathway for HF patients after a CIED alert, which kind of medications should be changed or escalated, and in which case in-hospital visits or in-hospital admissions are required. Finally, the specific role of healthcare professionals involved in HF patient management under remote monitoring is still matter of definition. We analyzed recent data on multiparametric monitoring of patients with HF through CIEDs. We provided practical insights on how to timely manage CIED alarms with the aim to prevent worsening HF. We also discussed the role of biomarkers and thoracic echo in this context, and potential organizational models including multidisciplinary teams for remote care of HF patients with CIEDs.

Integration of a Smartphone HF-Dedicated App in the Remote Monitoring of Heart Failure Patients with Cardiac Implantable Electronic Devices: Patient Access, Acceptance, and Adherence to Use

(200 w) Introduction. Remote monitoring (RM) of cardiac implantable electronic device (CIED) diagnostics helps to identify patients potentially at risk of worsening heart failure (HF). Additionally, knowledge of patient HF-related symptoms is crucial for decision making. Patient smartphone applications may represent an ideal option to remotely collect this information.

PURPOSE

To assess real-world HF patient access, acceptance, and adherence to use of an HF-dedicated smartphone application (HF app).

METHODS

In this study, 10 Italian hospitals administered a survey on smartphone/app use to HF patients with CIED. The subgroup who accepted it downloaded the HF app. Mean 1-year adherence of the HF app use was evaluated.

RESULTS

A total of 495 patients (67 ± 13 years, 79% males, 26% NYHA III-IV) completed the survey, of which 84% had access to smartphones and 85% were willing to use the HF app. In total, 311/495 (63%) downloaded the HF app. Patients who downloaded the HF app were younger and had higher school qualification. Patients who were ≥60 years old had higher mean 1-year adherence (54.1%) than their younger counterparts (42.7%; p < 0.001). Hospitals with RM-dedicated staff had higher mean 1-year patient adherence (64.0% vs. 33.5%; p < 0.001). Adherence to HF app decreased from 63.3% (weeks_1-13) to 42.2% (weeks_40-52, p < 0.001).

CONCLUSIONS

High access and acceptance of smartphones/apps by HF patients with CIED allow HF app use for RM of patient signs/symptoms. Younger patients with higher school qualifications are more likely to accept HF app; however, older patients have higher long-term adherence.

Telemedicine in Heart Failure in the COVID-19 and Post-Pandemic Era: What Have We Learned?

Numerous studies showed that patients with heart failure (HF) and COVID-19 are at high risk of in-hospital complications and long-term mortality. Changes in the organisation of the medical system during the pandemic also worsened access to standard procedures, increasing the general mortality in HF and forcing the systems to be reorganised with the implementation and development of telemedical technologies. The main challenges for HF patients during the pandemic could be solved with new technologies aimed to limit the risk of SARS-CoV-2 transmission, optimise and titrate the therapy, prevent the progression and worsening of HF, and monitor patients with acute HF events in the course of and after COVID-19. Dedicated platforms, phone calls or video conferencing and consultation, and remote non-invasive and invasive cardiac monitoring became potential tools used to meet the aforementioned challenges. These solutions showed to be effective in the model of care for patients with HF and undoubtedly will be developed after the experience of the pandemic. However, the multitude of possibilities requires central coordination and collaboration between institutes with data protection and cost reimbursement to create effective mechanisms in HF management. It is crucial that lessons be learned from the pandemic experience to improve the quality of care for HF patients.

Telemedicine in Adult Congenital Heart Disease: Usefulness of Digital Health Technology in the Assistance of Critical Patients

The number of adults with congenital heart disease (ACHD) has progressively increased in recent years to surpass that of children. This population growth has produced a new demand for health care. Moreover, the 2019 coronavirus pandemic has caused significant changes and has underlined the need for an overhaul of healthcare delivery. As a result, telemedicine has emerged as a new strategy to support a patient-based model of specialist care. In this review, we would like to highlight the background knowledge and offer an integrated care strategy for the longitudinal assistance of ACHD patients. In particular, the emphasis is on recognizing these patients as a special population with special requirements in order to deliver effective digital healthcare.

Heart failure and telemedicine: where are we and where are we going? Opportunities and critical issues

Heart failure (HF) is one of the main causes of morbidity in the world and is responsible for an enormous amount of health costs, mostly due to hospitalizations. The remote control techniques of vital signs and health status have the potential to help prevent factors leading to HF instability by stimulating early therapeutic interventions. The goal of telemedicine is to change the intervention strategy from a 'reactive' type, in which therapy is optimized in response to the worsening of symptoms, to a 'pro-active' type, in which therapeutic changes are undertaken based on changes in the monitored parameters during the sub-clinical phase. This article is aimed at exploring the major results obtained by telemedicine application in HF patients with and without cardiac electronic devices or in those with haemodynamic sensors and to analyse the critical issues and the opportunities of its use.

Implantable Cardiovascular Devices: Current and Emerging Technologies for Remote Heart Failure Monitoring

Heart failure remains a substantial socioeconomic burden to our health care system. With the aging of the population, the incidence is expected to rise in the ensuing years. Standard heart failure management strategies have failed to reduce hospitalizations and mortality. In patients with heart failure, remote hemodynamic monitoring with implantable devices provides essential data, which can be used in unison with standard patient management to reduce heart failure hospitalizations. This review will chronicle the important clinical trials of various implantable devices and describe the emerging technologies in remote heart failure management. Cardiovascular implantable electronic devices, namely implanted cardioverter-defibrillator and cardiac resynchronization therapy devices with defibrillator, have evolved beyond sole resynchronization and currently can deliver real-time cardiac hemodynamics. Clinical data regarding hemodynamic monitoring with implanted cardioverter-defibrillator and cardiac resynchronization therapy devices with defibrillator have not consistently demonstrated a reduction in heart failure or mortality benefit. However, there is promise in the future with the application of multiparameter diagnostic algorithms with these devices. The most efficacious implantable device has been the pulmonary artery pressure sensor, CardioMEMS. This device has been proven to be safe and shown to reduce heart failure hospitalizations. Moreover, multiple newly developed devices are currently under investigation after successful first-in-man studies.

HeartLogic™: real-world data-efficiency, resource consumption, and workflow optimization

Heart failure (HF) is a major and still growing medical problem and is characterized by episodes of acute decompensation that are associated with a negative prognosis and a significant burden on the patients, doctors, and healthcare resources. Early detection of incipient HF may allow outpatient treatment before patients severely decompensate, thus reducing HF hospitalizations and related costs. The HeartLogic™ algorithm is an automatic, remotely managed system combining data directly related to HF pathophysiology into a single score, the HeartLogic™ index. This index proved to be effective in predicting the risk of incipient HF decompensation, allowing to redistribute resources from low-risk to high-risk patients in a timely and cost-saving manner. The alert-based remote management system seems more efficient than the one based on scheduled remote transmission in terms of caregivers' workload and alert detection timing. The widespread application of the HeartLogic™ algorithm requires the resolution of logistical and financial issues and the adoption of a pre-defined, functional workflow. In this paper, we reviewed general aspects of remote monitoring in HF patients, the functioning and pathophysiological basis of the HeartLogic index, its efficiency in the management of HF patients, and the economic effects and the organizational revolution associated with its use.

Clinical Pathways Guided by Remotely Monitoring Cardiac Device Data: The Future of Device Heart Failure Management?

Research examining the utility of cardiac device data to manage patients with heart failure (HF) is rapidly evolving. COVID-19 has reignited interest in remote monitoring, with manufacturers each developing and testing new ways to detect acute HF episodes, risk stratify patients and support self-care. As standalone diagnostic tools, individual physiological metrics and algorithm-based systems have demonstrated utility in predicting future events, but the integration of remote monitoring data with existing clinical care pathways for device HF patients is not well described. This narrative review provides an overview of device-based HF diagnostics available to care providers in the UK, and describes the current state of play with regard to how these systems fit in with current HF management.

Cardiovascular Implantable Electronic Devices Enabled Remote Heart Failure Monitoring; What We Have Learned and Where to Go Next

Despite recent developments, heart failure (HF) remains to be a great burden to the individual patient, entailing major morbidity and mortality. Moreover, HF is a great burden to overall healthcare, mainly because of frequent hospitalizations. Timely diagnosis of HF deterioration and implementation of appropriate therapy may prevent hospitalization and eventually improve a patient’s prognosis; however, depending on the patient’s presentation, the signs and symptoms of HF often offer too little therapeutic window to prevent hospitalizations. Cardiovascular implantable electronic devices (CIEDs) can provide real-time physiologic parameters and remote monitoring of these parameters can potentially help to identify patients at high risk. However, routine implementation of remote monitoring of CIEDs has still not been widely used in daily patient care. This review gives a detailed description of available metrics for remote HF monitoring, the studies that provide evidence of their efficacy, ways to implement them in clinical HF practice, as well as lessons learned on where to go on from where we currently are.

Predicting all-cause mortality by means of a multisensor implantable defibrillator algorithm for heart failure monitoring

BACKGROUND

The HeartLogic algorithm (Boston Scientific) has proved to be a sensitive and timely predictor of impending heart failure (HF) decompensation.

OBJECTIVE

The purpose of this study was to determine whether remotely monitored data from this algorithm could be used to identify patients at high risk for mortality.

METHODS

The algorithm combines implantable cardioverter-defibrillator (ICD)-measured accelerometer-based heart sounds, intrathoracic impedance, respiration rate, ratio of respiration rate to tidal volume, night heart rate, and patient activity into a single index. An alert is issued when the index crosses a programmable threshold. The feature was activated in 568 ICD patients from 26 centers.

RESULTS

During median follow-up of 26 months [25th-75th percentile 16-37], 1200 alerts were recorded in 370 patients (65%). Overall, the time IN-alert state was 13% of the total observation period (151/1159 years) and 20% of the follow-up period of the 370 patients with alerts. During follow-up, 55 patients died (46 in the group with alerts). The rate of death was 0.25 per patient-year (95% confidence interval [CI] 0.17-0.34) IN-alert state and 0.02 per patient-year (95% CI 0.01-0.03) OUT of the alert state, with an incidence rate ratio of 13.72 (95% CI 7.62-25.60; P <.001). After multivariate correction for baseline confounders (age, ischemic cardiomyopathy, kidney disease, atrial fibrillation), the IN-alert state remained significantly associated with the occurrence of death (hazard ratio 9.18; 95% CI 5.27-15.99; P <.001).

CONCLUSION

The HeartLogic algorithm provides an index that can be used to identify patients at higher risk for all-cause mortality. The index state identifies periods of significantly increased risk of death.

Digital Health Technologies for Post-Discharge Care after Heart Failure Hospitalisation to Relieve Symptoms and Improve Clinical Outcomes

The prevention of recurrent heart failure (HF) hospitalisations is of particular importance, as each such successive event may increase the risk of death. Effective care planning during the vulnerable phase after discharge is crucial for symptom control and improving patient prognosis. Many clinical trials have focused on telemedicine interventions in HF, with varying effects on the primary endpoints. However, the evidence of the effectiveness of telemedicine solutions in cardiology is growing. The scope of this review is to present complementary telemedicine modalities that can support outpatient care of patients recently hospitalised due to worsening HF. Remote disease management models, such as video (tele) consultations, structured telephone support, and remote monitoring of vital signs, were presented as core components of telecare. Invasive and non-invasive monitoring of volume status was described as an important step forward to prevent congestion-the main cause of clinical decompensation. The idea of virtual wards, combining these facilities with in-person visits, strengthens the opportunity for education and enhancement to promote more intensive self-care. Electronic platforms provide coordination of tasks within multidisciplinary teams and structured data that can be effectively used to develop predictive algorithms based on advanced digital science, such as artificial intelligence. The rapid progress in informatics, telematics, and device technologies provides a wide range of possibilities for further development in this area. However, there are still existing gaps regarding the use of telemedicine solutions in HF patients, and future randomised telemedicine trials and real-life registries are still definitely needed.

Remote Patient Monitoring for Patients with Heart Failure: Sex- and Race-based Disparities and Opportunities

Remote patient monitoring (RPM), within the larger context of telehealth expansion, has been established as an effective and safe means of care for patients with heart failure (HF) during the recent pandemic. Of the demographic groups, female patients and black patients are underenrolled relative to disease distribution in clinical trials and are under-referred for RPM, including remote haemodynamic monitoring, cardiac implantable electronic devices (CIEDs), wearables and telehealth interventions. The sex- and race-based disparities are multifactorial: stringent clinical trial inclusion criteria, distrust of the medical establishment, poor access to healthcare, socioeconomic inequities, and lack of diversity in clinical trial leadership. Notwithstanding addressing the above factors, RPM has the unique potential to reduce disparities through a combination of implicit bias mitigation and earlier detection and intervention for HF disease progression in disadvantaged groups. This review describes the uptake of remote haemodynamic monitoring, CIEDs and telehealth in female patients and black patients with HF, and discusses aetiologies that may contribute to inequities and strategies to promote health equity.

Temporal Characteristics of Device-Based Individual and Integrated Risk Metrics in Patients With Chronic Heart Failure

BACKGROUND

Temporal characteristics of a multimetric risk score and its individual parameters before, during, and after a heart failure (HF) event have not been defined.

OBJECTIVES

A large real-world patient cohort with implantable cardioverter-defibrillators and cardiac resynchronization therapy (CRT) defibrillators was used to define these temporal characteristics.

METHODS

Deidentified health records were linked to manufacturer's device database in 17,886 patients. Multimetric risk score combined daily measures of impedance, heart rate, activity, heart rate variability, and atrial fibrillation (AF) burden, AF ventricular rate, CRT pacing, and ventricular tachycardia episodes and shocks. HF event was defined as an inpatient, emergency department, or observation unit stay with primary diagnosis of HF and intravenous diuretic agents administration. Changes in risk parameters during 60 days before, during, and after an HF event were compared in patients with no HF readmissions vs patients with HF readmission.

RESULTS

A total of 1,174 patients had HF events with no HF readmission, and 282 patients had HF events with HF readmission. Diagnostic risk score was higher on all 60 days before and after a HF event in patients with HF readmission compared with patients with no readmission (P < 0.001). Change in risk score from admission to discharge was similar in patients with and without HF readmission, but the risk score fell more significantly 7 after discharge and 30 days after admission in patients without HF readmission (P < 0.001).

CONCLUSIONS

Temporal characteristics of risk metrics were significantly different in patients with no HF readmissions vs patients with HF readmission; patients without HF recurrence had larger recovery of risk metrics values toward normal.

'Acute Heart Failure': Should We Abandon the Term Altogether?

PURPOSE OF REVIEW

The distinction between 'acute' and 'chronic' heart failure persists. Our review aims to explore whether reclassifying heart failure decompensation more accurately as an event within the natural history of chronic heart failure has the potential to improve outcomes.

RECENT FINDINGS

Although hospitalisation for worsening heart failure confers a poor prognosis, much of this reflects chronic disease severity. Most patients survive hospitalisation with most deaths occurring in the post-discharge 'vulnerable phase'. Current evidence supports four classes of medications proven to reduce cardiovascular mortality for those who have heart failure with a reduced ejection fraction, with recent trials suggesting worsening heart failure events are opportunities to optimise these therapies. Abandoning the term 'acute heart failure' has the potential to give greater priority to initiating proven pharmacological and device therapies during decompensation episodes, in order to improve outcomes for those who are at the greatest risk.

Multidisciplinary heart failure care program: an experience from Colombia

The prevalence of Heart Failure is growing alarmingly; its treatment consumes health resources and affects the quality of life of patients.

OBJECTIVE

to describe the changes in NYHA functional Class, ejection fraction, hospitalizations and mortality after 8 years of follow up in a multidisciplinary heart failure program in Colombia as a model for lower and middle income countries.

METHODS

An observational study was performed with the retrospective analysis of the information RESULTS: 1757 patients were included, The NYHA functional class at the beginning of the program was: NYHA I 23.5%, NYHA II 50.3%, NYHA class Improvement was observed at the end of the follow-up with an increase in the percentage of patients in Functional Class NYHA I and II. The reduction in hospitalizations were 35% less (mean: 0.68 ± 0.95, p < 0.0001), a reduction in the length of stay in the hospital was 13.2% (before: 4.46 ± 7.16, after 3.87 ± 8.1 days, p < 0.001). The total mortality after eight years of follow-up was 6.6 % (n = 116).

CONCLUSION

Multidisciplinary follow-up in HF programs improves Functional Class and EF, decreases hospital admissions as well as hospitalization and the length of stay. This is a very simple and successful model of care for this disease that can be implemented for countries of lower- and middle-income countries.

Impact of remote monitoring in heart failure patients with cardiac implantable electronic devices during COVID-19 pandemic: a single center experience

Background

Coronavirus disease 2019 (COVID-19) had spread into a pandemic affecting healthcare providers worldwide. Heart failure patients with implanted cardiac devices require close follow-up in-spite of pandemic related healthcare restrictions.

Methods

Patients were retrospectively registered and clinical outcomes were compared of 61 remote monitored (RMG) versus 71 conventionally (in-office only) followed (CFG) cardiac device implanted, heart failure patients. Follow-up length was 12 months, during the COVID-19 pandemic related intermittent insitutional restrictions. We used a specified heart failure detection algorithm in RMG. This investigation compared worsening heart failure-, arrhythmia- and device related adverse events as primary outcome and heart failure hospitalization rates as secondary outcome in the two patient groups.

Results

No significant difference was observed in the primary composite end-point during the first 12 months of COVID-19 pandemic (p = 0.672).

In RMG, patients who had worsening heart failure event had relative modest deterioration in heart failure functional class (p = 0.026), relative lower elevation of N terminal-pro BNP levels (p < 0.01) at in-office evaluation and were less hospitalized for worsening heart failure in the first 6 months of pandemic (p = 0.012) compared to CFG patients.

Conclusions

Specified remote monitoring alert-based detection algorithm and workflow in device implanted heart failure patients may potentially indicate early worsening in heart failure status. Preemptive adequate intervention may prevent further progression of deteriorating heart failure and thus prevent heart failure hospitalizations.

Treatment of cardiac resynchronization therapy non-responders: current approaches and new frontiers

INTRODUCTION

Cardiac resynchronization therapy (CRT) has developed into a very effective technology for patients with decreased systolic function and has substantially improved patients' clinical course. However, non-responsiveness to CRT, described as lack of reverse cardiac chamber remodeling, leading to lack to improve symptoms, heart failure hospitalizations or mortality, is common, rather unpredictable, and not fully understood.

AREAS COVERED

This article aims to discuss key factors that are impacting CRT response; from patient selection to LV lead position, to structured follow-up in CRT clinics. Secondly, common causes and interventions for CRT non-responsiveness are discussed. Next, insight is given into technologies representing new and feasible interventions as well as pacing strategies in this group of patients that remain challenging to treat. Finally, an outlook is given into future scientific development.

EXPERT OPINION

Despite the progress that has been made, CRT non-response remains a significant and complex problem. Patient management in interdisciplinary teams including heart failure, imaging, and cardiac arrhythmia experts appears critical as complexity is increasing and CRT non-response often is a multifactorial problem. This will allow optimization of medical therapy, the use of new integrated sensor technologies and telemedicine to ultimately optimize outcomes for all patients in need of CRT.

Remotely Monitored Cardiac Implantable Electronic Device Data Predict All-Cause and Cardiovascular Unplanned Hospitalization

Background Unplanned hospitalizations are common in patients with cardiovascular disease. The "Triage Heart Failure Risk Status" (Triage-HFRS) algorithm in patients with cardiac implantable electronic devices uses data from up to 9 device-derived physiological parameters to stratify patients as low/medium/high risk of 30-day heart failure (HF) hospitalization, but its use to predict all-cause hospitalization has not been explored. We examined the association between Triage-HFRS and risk of all-cause, cardiovascular, or HF hospitalization. Methods and Results A prospective observational study of 435 adults (including patients with and without HF) with a Medtronic Triage-HFRS-enabled cardiac implantable electronic device (cardiac resynchronization therapy device, implantable cardioverter-defibrillator, or pacemaker). Cox proportional hazards models explored association between Triage-HFRS and time to hospitalization; a frailty term at the patient level accounted for repeated measures. A total of 274 of 435 patients (63.0%) transmitted ≥1 high HFRS transmission before or during the study period. The remaining 161 patients never transmitted a high HFRS. A total of 153 (32.9%) patients had ≥1 unplanned hospitalization during the study period, totaling 356 nonelective hospitalizations. A high HFRS conferred a 37.3% sensitivity and an 86.2% specificity for 30-day all-cause hospitalization; and for HF hospitalizations, these numbers were 62.5% and 85.6%, respectively. Compared with a low Triage-HFRS, a high HFRS conferred a 4.2 relative risk of 30-day all-cause hospitalization (8.5% versus 2.0%), a 5.0 relative risk of 30-day cardiovascular hospitalization (3.6% versus 0.7%), and a 7.7 relative risk of 30-day HF hospitalization (2.0% versus 0.3%). Conclusions In patients with cardiac implantable electronic devices, remotely monitored Triage-HFRS data discriminated between patients at high and low risk of all-cause hospitalization (cardiovascular or noncardiovascular) in real time.

Physical Activity in Cardiac Implantable Electronic Device Recipients During the COVID-19 Pandemic

OBJECTIVE

To characterize the physical activity (PA) level in patients with a cardiac implantable electronic device (CIED) during the coronavirus disease 2019 (COVID-19) pandemic and compare PA level during the pandemic in 2020 with the year 2019.

METHODS

We performed a retrospective analysis of PA activity in individuals implanted with a CIED enrolled in the BIOTRONIK CERTITUDE Registry. Mean daily and weekly PA from January to August 2020 was compared with 2019.

RESULTS

A total of 21,660 individuals met eligibility criteria, with mean age of 72.6±11.6 years, and 12,411 (57.3)% were males. A significant decline in daily PA was noted following the pandemic declaration in 2020, with a maximum mean reduction of -24.5±36.3 minutes (P<.0001) observed in April 2020 compared with 2019. PA in 2020 increased from April to May (120.6±67.4 to 129.2±70.9 min/d). PA was lower for all months in 2020 compared with 2019. The decrease in PA was observed in all prespecified groups based on age, sex, type of device, and region of the country.

CONCLUSION

After the declaration of the coronavirus disease 2019 pandemic, a significant decline in daily PA was observed in individuals with a CIED. Future investigation to establish the impact of this reduction on short and long-term cardiovascular outcomes is required.

Comparative Analysis of Physical Activity Detected via an External Accelerometer and Cardiac Implantable Electronic Devices

Background

Physical activity (PA) has become an important health issue for decades. Cardiovascular implantable electronic devices (CIEDs) have built-in PA-recording functions. We aimed to compare PA measurements using an external accelerometer (ActiGraph GT3X+) and internal accelerometers (Abbott, Biotronik, and Medtronic CIEDs).

Methods

This was a prospective, single-center observational study. The device-measured 7-day average PA was collected, and GT3X+ -measured 7-day average PA was used as the gold-standard, including all daily observations of activity. Pearson’s correlation coefficients were used to compare the correlations between GT3X+ -measured and CIED-measured PA. Bland-Altman plots were used to analyze measurement agreement, and intraclass correlation coefficients were used to analyze reliability.

Results

In total, 720 patients treated with CIEDs were surveyed between November 2020 and April 2021, 60 of them were analyzed after patient screening by our protocol. Each manufacturer included 20 patients for the final analysis. The CIED-measured PAs of Abbott, Biotronik, and Medtronic were 3.0 ± 1.5, 2.6 ± 1.8, and 3.8 ± 2.5 h per day, respectively; the GT3X+ -measured PAs were 6.9 ± 2.8, 6.0 ± 2.4, and 6.4 ± 2.5 h per day, respectively. Moderate and significant correlations were found in patients using Abbott, Biotronik, and Medtronic CIEDs (r = 0.534, p = 0.015; r = 0.465, p = 0.039; r = 0.677, p = 0.001, respectively). Bland-Altman plots and intraclass correlation coefficients both showed a significant correlation and reliability between the average PA measured by GT3X+ and CIEDs (hours per day).

Conclusion

Although the PA recording function of CIEDs includes a single-axis accelerometer, it has a moderate correlation compared with the triaxial accelerometer of the GT3X+. However, CIEDs seem to underestimate PA for 3–4 h compared to the GT3X+.

Decongestive treatment adjustments in heart failure patients remotely monitored with a multiparametric implantable defibrillators algorithm

AIMS

HeartLogic algorithm combines data from multiple implantable defibrillators (ICD)-based sensors to predict impending heart failure (HF) decompensation. A treatment protocol to manage algorithm alerts is not yet known, although decongestive treatment adjustments are the most frequent alert-triggered actions reported in clinical practice. We describe the implementation of HeartLogic for remote monitoring of HF patients, and we evaluate the approach to diuretic dosing and timing of the intervention in patients with device alerts.

METHODS

The algorithm was activated in 229 ICD patients at eight centers. The median follow-up was 17 months (25th-75th percentile: 11-24). Remote data reviews and patient phone contacts were undertaken at the time of HeartLogic alerts, to assess the patient's status and to prevent HF worsening. We analyzed alert-triggered augmented HF treatments, consisting of isolated increases in diuretics dosage.

RESULTS

We reported 242 alerts (0.8 alerts/patient-year) in 123 patients, 137 (56%) alerts triggered clinical actions to treat HF. The HeartLogic index decreased after the 56 actions consisting of diuretics increase. Specifically, alerts resolved more quickly when the increases in dosing of diuretics were early rather than late: 28 days versus 62 days, p < .001. The need of hospitalization for further treatments to resolve the alert condition was associated with higher HeartLogic index values on the day of the diuretics increase (odds ratio: 1.11, 95% CI: 1.02-1.20, p = .013) and with late interventions (odds ratio: 5.11, 95% CI: 1.09-24.48, p = .041). No complications were reported after drug adjustments.

CONCLUSIONS

Decongestive treatment adjustments triggered by alerts seem safe and effective. The early use of decongestive treatment and the use of high doses of diuretics seem to be associated with more favorable outcomes.

Electronic Health Records and Heart Failure

Increasing the global adoption of electronic health records (EHRs) is transforming the delivery of clinical care. EHRs offer tools that are useful in the care of heart failure ranging from individualized risk stratification and decision support to population management. EHR tools can be combined to target specific areas of need such as the standardization of care, improved quality of care, and resource management. Leveraging EHR functionality has been shown to improve select outcomes including guideline-based therapies, reduction in adverse clinical outcomes, and improved cost-efficiency. Central to success is participation by clinicians and patients in the design and feedback of EHR tools.

Association of time-varying changes in physical activity with cardiac death and all-cause mortality after ICD or CRT-D implantation

OBJECTIVE

To evaluate the association of longitudinal changes in physical activity (PA) with long-term outcomes after implantable cardioverter-defibrillator (ICD) or cardiac resynchronization therapy defibrillator (CRT-D) implantation.

METHODS

Patients with ICD/CRT-D implantation from SUMMIT registry were retrospectively analyzed. Accelerometer-derived PA changes over 12 months post implantation were obtained from the archived home monitoring data. The primary endpoints were cardiac death and all-cause mortality. The secondary endpoints were the first ventricular arrthymia (VA) and first appropriate ICD shock.

RESULTS

In 705 patients, 446 (63.3%) patients showed improved PA over 12 months after implantation. During a mean 61.5-month follow-up duration, 99 cardiac deaths (14.0%) and 153 all-cause deaths (21.7%) occurred. Compared to reduced/unchanged PA, improved PA over 12 months could result in significantly reduced risks of cardiac death (improved PA ≤ 30 min: hazard ratio (HR) = 0.494, 95% CI: 0.288-0.848; > 30 min: HR = 0.390, 95% CI: 0.235-0.648) and all-cause mortality (improved PA ≤ 30 min: HR = 0.467, 95%CI: 0.299-0.728; > 30 min: HR = 0.451, 95% CI: 0.304-0.669). No differences in the VAs or ICD shocks were observed across different groups of PA changes. PA changes can predict the risks of cardiac death only in the low baseline PA group, but improved PA was associated with 56.7%, 57.4%, and 62.3% reduced risks of all-cause mortality in the low, moderate, and high baseline PA groups, respectively, than reduced/unchanged PA.

CONCLUSIONS

Improved PA could protect aganist cardiac death and all-cause mortality, probably reflecting better clinical efficacy after ICD/CRT-D implantation. Low-intensity exercise training might be encouraged among patients with different baseline PA levels.

Rationale and design of the SafeHeart study: Development and testing of a mHealth tool for the prediction of arrhythmic events and implantable cardioverter-defibrillator therapy

Background

Patients with an implantable cardioverter-defibrillator (ICD) are at a high risk of malignant ventricular arrhythmias. The use of remote ICD monitoring, wearable devices, and patient-reported outcomes generate large volumes of potential valuable data. Artificial intelligence–based methods can be used to develop personalized prediction models and improve early-warning systems.

Objective

The purpose of this study was to develop an integrated web-based personalized prediction engine for ICD therapy.

Methods

This international, multicenter, prospective, observational study consists of 2 phases: (1) a development study and (2) a feasibility study. We plan to enroll 400 participants with an ICD (with or without cardiac resynchronization therapy) on remote monitoring: 300 participants in the development study and 100 in the feasibility study. During 12-month follow-up, electronic health record data, remote monitoring data, accelerometry-assessed physical behavior data, and patient-reported data are collected. By using machine- and deep-learning approaches, a prediction engine is developed to assess the risk probability of ICD therapy (shock and antitachycardia pacing). The feasibility of the prediction engine as a clinical tool, the SafeHeart Platform, is assessed during the feasibility study.

Results

Development study recruitment commenced in 2021. The feasibility study starts in 2022.

Conclusion

SafeHeart is the first study to prospectively collect a multimodal data set to construct a personalized prediction engine for ICD therapy. Moreover, SafeHeart explores the integration and added value of detailed objective accelerometer data in the prediction of clinical events. The translation of the SafeHeart Platform to clinical practice is examined during the feasibility study.

Use of CIED Generated Heart Failure Risk Score (HFRS) Alerts in an Integrated, Multi-Disciplinary Approach to HF Management-A Prospective Cohort Study

Aim: To evaluate use of CIED-generated Heart Failure Risk Score (HFRS) alerts in an integrated, multi-disciplinary approach to HF management. Methods: We undertook a prospective, single centre outcome study of patients implanted with an HFRS-enabled Medtronic CIED, generating a “high risk” alert between November 2018 and November 2020. All patients generating a “high risk” HFRS alert were managed within an integrated HF pathway. Alerts were shared with local HF teams, prompting patient contact and appropriate intervention. Outcome data on health care utilisation (HCU) and mortality were collected. A validated questionnaire was completed by the HF teams to obtain feedback. Results: 367 “High risk” alerts were noted in 188 patients. The mean patient age was 70 and 49% had a Charlson Comorbidity Score of >6. Mean number of alerts per patients was 1.95 and 44 (23%) of patients had >3 “high risk” alerts in the follow up period. Overall, 75 (39%) patients were hospitalised in the 4−6-week period of the alert; 53 (28%) were unplanned of which 24 (13%) were for decompensated HF. A total of 33 (18%) patients died in the study period. Having three or more alerts significantly increased the risk of hospitalisation for heart failure (HR 2.5, CI 1.1−5.6 p = 0.03). The feedback on the pathway was positive. Conclusions: Patients with “high risk” alerts are co-morbid and have significant HCU. An integrated approach can facilitate timely risk stratification and intervention. Intervention in these patients is not limited to HF alone and provides the opportunity for holistic management of this complex cohort.

Implantable cardioverter defibrillators and devices for cardiac resynchronization therapy: what perspective for patients' apps combined with remote monitoring?

INTRODUCTION

Remote monitoring (RM) of cardiac implantable electronic devices (CIED) allows rapid detection of clinical and electrical events. Recently, several smartphone applications have been developed with the aim of improving patient compliance and better interpreting and integrating data deriving from remote control for the management of heart failure (HF).

AREAS COVERED

Studies investigating the role of CIEDs' RM in HF patients to predict and early treat acute decompensation. The importance of new technologies and applications developed to provide crucial information to clinicians, to better manage HF patients.

EXPERT OPINION

New medical technologies and smartphone applications for CIEDs' RM were developed to help clinicians in the management of CIED carriers. Indeed, the accessibility of technological devices (e.g. smartphones) and the improvements in medical technology provide the opportunity to optimize HF patients' monitoring by the transmission of device-related data, and with direct involvement of patients themselves. Thanks to these advancements, physicians have the possibility to recognize worsening signs of HF and promptly optimize treatments to potentially avoid hospitalization. The great value of this approach is its potential of reducing scheduled in-office visits or unnecessary medical contacts and optimizing healthcare resources management.

Clinical Utility of HeartLogic, a Multiparametric Telemonitoring System, in Heart Failure

Telemonitoring through multiple variables measured on cardiac devices has the potential to improve the follow-up of patients with heart failure. The HeartLogic algorithm (Boston Scientific), implemented in some implantable cardiac defibrillators and cardiac resynchronisation therapy, allows monitoring of the nocturnal heart rate, respiratory movements, thoracic impedance, physical activity and the intensity of heart tones, with the aim of predicting major clinical events. Although HeartLogic has demonstrated high sensitivity for the detection of heart failure decompensations, its effects on hospitalisation and mortality in randomised clinical trials has not yet been corroborated. This review details how the HeartLogic algorithm works, compiles available evidence from clinical studies, and discusses its application in daily clinical practice.

Remote Cardiac Monitoring in Patients With Heart Failure: A Review

Importance

Heart failure (HF) is often characterized by an insidious disease course leading to frequent rehospitalizations and a high use of ambulatory care. Remote cardiac monitoring is a promising approach to detect worsening HF early and intervene prior to an overt decompensation.

Observations

Recently, a multitude of novel technologies for remote cardiac monitoring (RCM) in patients with HF have been developed and are undergoing clinical trials. This development has been accelerated by the COVID-19 pandemic.

Conclusions and Relevance

This review summarizes the major clinical trials on RCM in patients with HF and present the most recent developments in noninvasive and invasive RCM technologies.

Evaluation of Medicare Claims for the Development of Heart Failure Diagnostics

BACKGROUND

Although claims data provide a large and efficient source of clinical events, validation is needed prior to use in heart failure (HF) diagnostic development.

METHODS AND RESULTS

Data from the Multisensor Chronic Evaluations in Ambulatory Heart Failure Patients (MultiSENSE) study, used to create the HeartLogic HF diagnostic, were linked with fee-for-service (FFS) Medicare claims. Events were matched by patient ID and date, and agreement was calculated between claims primary HF diagnosis codes and study event adjudication. HF events (HFEs) were defined as inpatient visits, or outpatient visits with intravenous decongestive therapy. Diagnostic performance was measured as HFE-detection sensitivity and false-positive rate (FPR). Linkage of 791 MultiSENSE subjects returned 320 FFS patients with an average follow-up duration of 0.94 years. Although study and claims deaths matched exactly (n = 14), matching was imperfect between study hospitalizations and acute inpatient claims events. Of 239 total events, 165 study hospitalizations (69%) matched inpatient claims events, 28 hospitalizations matched outpatient claims events (12%), 14 hospitalizations were study-unique (6%), and 32 inpatient events were claims-unique (13%). Inpatient HF classification had substantial agreement with study adjudication (κ = 0.823). Diagnostic performance was not different between claims and study events (sensitivity = 75.6% vs 77.6% and FPR = 1.539 vs 1.528 alerts/patient-year). HeartLogic-detected events contributed to > 90% of the HFE costs used for evaluation.

CONCLUSIONS

Acceptable event matching, good agreement of claims diagnostic codes with adjudication, and equivalent diagnostic performance support the validity of using claims for HF diagnostic development.

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.

Biomarkers in the management of acute heart failure: state of the art and role in COVID-19 era

Acute heart failure (AHF) affects millions of people worldwide, and it is a potentially life‐threatening condition for which the cardiologist is more often brought into play. It is crucial to rapidly identify, among patients presenting with dyspnoea, those with AHF and to accurately stratify their risk, in order to define the appropriate setting of care, especially nowadays due to the coronavirus disease 2019 (COVID‐19) outbreak. Furthermore, with physical examination being limited by personal protective equipment, the use of new alternative diagnostic and prognostic tools could be of extreme importance. In this regard, usage of biomarkers, especially when combined (a multimarker approach) is beneficial for establishment of an accurate diagnosis, risk stratification and post‐discharge monitoring. This review highlights the use of both traditional biomarkers such as natriuretic peptides (NP) and troponin, and emerging biomarkers such as soluble suppression of tumourigenicity (sST2) and galectin‐3 (Gal‐3), from patients' emergency admission to discharge and follow‐up, to improve risk stratification and outcomes in terms of mortality and rehospitalization.

Remote monitoring for heart failure using implantable devices: a systematic review, meta-analysis, and meta-regression of randomized controlled trials

In heart failure (HF) patients, remote monitoring using implantable devices may be used to predict and reduce HF exacerbations and mortality. Data from randomized controlled trials (RCTs) was assessed to determine the effectiveness of implantable remote monitoring on the improvement of outcomes in HF patients. A systematic review and meta-analysis of RCTs testing remote monitoring versus standard of care for management of HF patients was performed. Primary endpoints were all-cause mortality and a composite of cardiovascular (CV) and HF hospitalizations. Rate ratios (RRs) and 95% confidence intervals (CI) were calculated. A secondary analysis tested for heterogeneity of treatment effect (HTE) comparing right ventricular/pulmonary pressure monitoring versus impedance-based monitoring on hospitalization. A regression analysis was performed using the mean follow-up time as the moderator on each primary endpoint. Eleven RCTs (n = 6196) were identified with a mean follow-up of 21.9 months. The mean age and reported ejection fraction were 64.1 years and 27.7%, respectively. Remote monitoring did not reduce mortality (RR 0.89 [95% CI 0.77, 1.03]) or the composite of CV and HF hospitalizations (RR 0.98 [0.81, 1.19]). Subgroup analysis found significant HTE for hospitalizations between those studies that used right ventricular/pulmonary pressure monitoring versus impedance-based monitoring (I² = 87.1%, chi² = 7.75, p = 0.005). Regression analysis found no relationship between the log rate ratio of remote monitoring’s effect on mortality, CV hospitalization or HF hospitalization, and mean follow-up time. Compared to standard of care, remote monitoring using implantable devices did not reduce mortality, CV, or HF hospitalizations. However, right ventricular/pulmonary pressure monitoring may reduce HF hospitalizations, which will need to be explored in future studies.

Impact of COVID-19 Pandemic on Remote Monitoring of Cardiac Implantable Electronic Devices in Italy: Results of a Survey Promoted by AIAC (Italian Association of Arrhythmology and Cardiac Pacing)

The COVID-19 pandemic has had a profound impact on the organisation of health care in Italy, with an acceleration in the development of telemedicine. To assess the impact of the COVID-19 pandemic on the spread of remote monitoring (RM) of cardiac implantable electronic devices (CIEDs) in Italy, a survey addressed to cardiologists operating in all Italian CIED-implanting centres was launched. A total of 127 cardiologists from 116 Italian arrhythmia centres took part in the survey, 41.0% of all 283 CIED-implanting centres operating in Italy in 2019. All participating centres declared to use RM of CIEDs. COVID-19 pandemic resulted in an increase in the use of RM in 83 (71.6%) participating centres. In a temporal perspective, an increase in the median number of patients per centre followed up by RM was found from 2012 to 2017, followed by an exponential increase from 2017 to 2020. In 36 participating centres (31.0%) a telehealth visits service was activated as a replacement for in-person outpatient visits (in patients with or without CIED) during the COVID-19 pandemic. COVID-19 pandemic has caused an acceleration in the use of RM of CIEDs and in the use of telemedicine in the clinical practice of cardiology.

Impact of Remote Monitoring on Hospitalizations for Heart Failure: A Five-year Single-center Experience

The impact of a provider-driven assessment and treatment algorithm based on remote OptiVol (Medtronic, Minneapolis, MN, USA) fluid index levels on hospitalizations for congestive heart failure (CHF) remains unknown. We implemented a physician-guided screening and educational strategy for elevated OptiVol fluid index levels measured on remote implantable cardioverter-defibrillator (ICD) monitoring and assessed clinical outcomes over a five-year period. Patients with CHF and a left ventricular ejection fraction (LVEF) of 40% or less with a previously implanted ICD underwent monthly remote monitoring from January 2015 to November 2019. An OptiVol fluid index of 60 Ω-days or more triggered a protocol-based CHF screening and therapy adjustment according to clinical presentation. Among 279 patients included in the study, 228 (81%) were male and 205 (73%) had ischemic cardiomyopathy. The average LVEF was 29% (± 7.3%). A total of 6,616 monthly transmissions were reviewed over five years; of those, 575 (8.7%) were associated with elevated OptiVol fluid index levels in 178 (64%) patients, and clinical follow-up data were available in 459 of 575 (80%) cases. Following abnormal OptiVol fluid levels on remote monitoring, CHF hospitalization occurred in 10 of 459 (2.2%) patient cases. In conclusion, monthly remote monitoring of OptiVol fluid index levels with a health care provider–guided CHF screening and an educational approach to abnormal OptiVol fluid index levels were associated with a low CHF hospitalization rate. This compared favorably to prior similar studies, and randomized controlled prospective studies evaluating similar algorithms are warranted.

Combining Home Monitoring temporal trends from implanted defibrillators and baseline patient risk profile to predict heart failure hospitalizations: results from the SELENE HF study

AIMS

We developed and validated an algorithm for prediction of heart failure (HF) hospitalizations using remote monitoring (RM) data transmitted by implanted defibrillators.

METHODS AND RESULTS

The SELENE HF study enrolled 918 patients (median age 69 years, 81% men, median ejection fraction 30%) with cardiac resynchronization therapy (44%), dual-chamber (38%), or single-chamber defibrillators with atrial diagnostics (18%). To develop a predictive algorithm, temporal trends of diurnal and nocturnal heart rates, ventricular extrasystoles, atrial tachyarrhythmia burden, heart rate variability, physical activity, and thoracic impedance obtained by daily automatic RM were combined with a baseline risk-stratifier (Seattle HF Model) into one index. The primary endpoint was the first post-implant adjudicated HF hospitalization. After a median follow-up of 22.5 months since enrolment, patients were randomly allocated to the algorithm derivation group (n = 457; 31 endpoints) or algorithm validation group (n = 461; 29 endpoints). In the derivation group, the index showed a C-statistics of 0.89 [95% confidence interval (CI): 0.83-0.95] with 2.73 odds ratio (CI 1.98-3.78) for first HF hospitalization per unitary increase of index value (P < 0.001). In the validation group, sensitivity of predicting primary endpoint was 65.5% (CI 45.7-82.1%), median alerting time 42 days (interquartile range 21-89), and false (or unexplained) alert rate 0.69 (CI 0.64-0.74) [or 0.63 (CI 0.58-0.68)] per patient-year. Without the baseline risk-stratifier, the sensitivity remained 65.5% and the false/unexplained alert rates increased by ≈10% to 0.76/0.71 per patient-year.

CONCLUSION

With the developed algorithm, two-thirds of first post-implant HF hospitalizations could be predicted timely with only 0.7 false alerts per patient-year.

Optimized implementation of cardiac resynchronization therapy: a call for action for referral and optimization of care

Cardiac resynchronization therapy (CRT) is one of the most effective therapies for heart failure with reduced ejection fraction and leads to improved quality of life, reductions in heart failure hospitalization rates and all-cause mortality. Nevertheless, up to two-thirds of eligible patients are not referred for CRT. Furthermore, post-implantation follow-up is often fragmented and suboptimal, hampering the potential maximal treatment effect. This joint position statement from three European Society of Cardiology Associations, Heart Failure Association (HFA), European Heart Rhythm Association (EHRA) and European Association of Cardiovascular Imaging (EACVI), focuses on optimized implementation of CRT. We offer theoretical and practical strategies to achieve more comprehensive CRT referral and post-procedural care by focusing on four actionable domains: (i) overcoming CRT under-utilization, (ii) better understanding of pre-implant characteristics, (iii) abandoning the term 'non-response' and replacing this by the concept of disease modification, and (iv) implementing a dedicated post-implant CRT care pathway.

Remote Monitoring of Permanent Pacemakers and Implantable Cardioverter Defibrillators

Remote monitoring of permanent pacemakers and implantable cardiac defibrillators has undergone considerable advances over the past several decades. Advancement of technology has created the ability for remote monitoring of implantable cardiac devices; a device can monitor its own function, record arrhythmias, and transmit data to health care providers without frequent in-office checks, shown to be as safe as in-office interrogation. Remote monitoring allows earlier detection of clinically actionable events, reduces incidence of inappropriate shocks, and allows earlier detection of atrial fibrillation. App-based remote monitoring provides patients with rapid access to their cardiac data, which may improve compliance with remote monitoring.

Multiparametric Implantable Cardioverter-Defibrillator Algorithm for Heart Failure Risk Stratification and Management: An Analysis in Clinical Practice

BACKGROUND

The HeartLogic algorithm combines multiple implantable cardioverter-defibrillator sensors to identify patients at risk of heart failure (HF) events. We sought to evaluate the risk stratification ability of this algorithm in clinical practice. We also analyzed the alert management strategies adopted in the study group and their association with the occurrence of HF events.

METHODS

The HeartLogic feature was activated in 366 implantable cardioverter-defibrillator and cardiac resynchronization therapy implantable cardioverter-defibrillator patients at 22 centers. The median follow-up was 11 months [25th-75th percentile: 6-16]. The HeartLogic algorithm calculates a daily HF index and identifies periods IN alert state on the basis of a configurable threshold.

RESULTS

The HeartLogic index crossed the threshold value 273 times (0.76 alerts/patient-year) in 150 patients. The time IN alert state was 11% of the total observation period. Patients experienced 36 HF hospitalizations, and 8 patients died of HF during the observation period. Thirty-five events were associated with the IN alert state (0.92 events/patient-year versus 0.03 events/patient-year in the OUT of alert state). The hazard ratio in the IN/OUT of alert state comparison was (hazard ratio, 24.53 [95% CI, 8.55-70.38], P<0.001), after adjustment for baseline clinical confounders. Alerts followed by clinical actions were associated with less HF events (hazard ratio, 0.37 [95% CI, 0.14-0.99], P=0.047). No differences in event rates were observed between in-office and remote alert management.

CONCLUSIONS

This multiparametric algorithm identifies patients during periods of significantly increased risk of HF events. The rate of HF events seemed lower when clinical actions were undertaken in response to alerts. Extra in-office visits did not seem to be required to effectively manage HeartLogic alerts.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02275637.