Pathophysiology of the transition from chronic compensated and acute decompensated heart failure: New insights from continuous monitoring devices

CIED-based remote monitoring in heart failure using the HeartLogic™ algorithm: Which patients benefit most?

BACKGROUND & AIMS

Early identification of worsening HF enables timely adjustments to prevent hospitalization. Recent studies show the HeartLogic™ algorithm detects congestion and reduces HF events. However, it is unclear which patients benefit most. Therefore, this study aims to identify and characterize HF patients who benefit most from CIED-based remote monitoring with HeartLogic™.

METHODS

In this multicenter retrospective study, patients with a CIED and HeartLogic™ algorithm under structured follow-up were included. Patients were classified as having "substantial benefit" or "no benefit" from monitoring.

RESULTS

In total, 242 patients were included (male n = 190, 79%, median age 61 years [IQR 61-77]). Median follow-up was 1.2 years [IQR 1.1-2.7]. Among 378 alerts, 266 were true positive (70%) and 112 false positive (30%). Of the 242 patients, 69 (29%) were classified as having "substantial benefit", while 173 (71%) had "no benefit" from HeartLogic™ monitoring. Univariate and multivariate analysis showed that patients with "substantial benefit" had higher NYHA functional class (OR 2.64, P = 0.004), higher NT-ProBNP (OR 1.02, P = 0.003), higher serum creatinine (OR 1.10, P < 0.001), lower LVEF (OR 1.19, P = 0.004), more severe mitral regurgitation (OR 2.16, P = 0.006), higher right ventricular end diastolic volume (OR 1.05, P = 0.040), higher pulmonary artery pressures (OR 1.19, P = 0.003), and were more likely to use loop diuretics (OR 2.79, P = 0.001). Among patients with "substantial benefit," the positive predictive value (PPV) of HeartLogic™ to detect congestion was 92%.

CONCLUSION

The utilization of CIED-based HeartLogic™ driven HF care demonstrated pronounced efficacy, predominantly in patients exhibiting characteristics of HF at a more advanced disease stage.

Benefits of remote hemodynamic monitoring in heart failure

Despite treatment advancements, HF mortality remains high, prompting interest in reducing HF-related hospitalizations through remote monitoring. These advances are necessary considering the rapidly rising prevalence and incidence of HF worldwide, presenting a burden on hospital resources. While traditional approaches have failed in predicting impending HF-related hospitalizations, remote hemodynamic monitoring can detect changes in intracardiac filling pressure weeks prior to HF-related hospitalizations which makes timely pharmacological interventions possible. To ensure successful implementation, structural integration, optimal patient selection, and efficient data management are essential. This review aims to provide an overview of the rationale, the available devices, current evidence, and the implementation of remote hemodynamic monitoring.

Current approaches to preventing heart failure readmissions and decompensated disease

Heart failure is a resource-intensive condition to manage and typically involves a multi-disciplinary and multi-modality approach leading to an expensive treatment paradigm. It is worth noting that hospital admissions constitute over 80% of heart failure management costs. In the past two decades, healthcare systems have developed new ways of following patients remotely to prevent them from being readmitted to the hospital. However, despite these efforts, hospital admissions have still increased. Many successful readmission reduction programs prioritize education and self-care to increase patients' awareness of their disease and promote lasting lifestyle changes. While socioeconomic factors impact success, interventions tend to be effective when medication adherence and guideline-directed medical therapy are emphasized. Monitoring intracardiac pressure can improve resource allocation efficiency and has demonstrated significant reductions in readmissions with improved quality of life in outpatient and remote settings. Data from several studies focused on remote monitoring devices strongly suggest that understanding congestion using physiological biomarkers is an effective management strategy. Since most cases of heart failure are first presented in acute hospitalization settings, immediate access to intracardiac pressure for treatment and decision-making purposes could result in substantial management improvements. However, a notable technology gap needs to be addressed to enable this at a low cost with less reliability on scarce specialist care resources. Contemporary evidence is conclusive that direct hemodynamic are the vital signs in heart failure with the highest clinical utility. Therefore, future ability to obtain these insights reliably using non-invasive methods will be a paradigm-changing technology.

An explainable model for predicting Worsening Heart Failure based on genetic programming

Heart Failure (HF) poses a challenge for our health systems, and early detection of Worsening HF (WHF), defined as a deterioration in symptoms and clinical and instrumental signs of HF, is vital to improving prognosis. Predicting WHF in a phase that is currently undiagnosable by physicians would enable prompt treatment of such events in patients at a higher risk of WHF. Although the role of Artificial Intelligence in cardiovascular diseases is becoming part of clinical practice, especially for diagnostic and prognostic purposes, its usage is often considered not completely reliable due to the incapacity of these models to provide a valid explanation about their output results. Physicians are often reluctant to make decisions based on unjustified results and see these models as black boxes. This study aims to develop a novel diagnostic model capable of predicting WHF while also providing an easy interpretation of the outcomes. We propose a threshold-based binary classifier built on a mathematical model derived from the Genetic Programming approach. This model clearly indicates that WHF is closely linked to creatinine, sPAP, and CAD, even though the relationship of these variables and WHF is almost complex. However, the proposed mathematical model allows for providing a 3D graphical representation, which medical staff can use to better understand the clinical situation of patients. Experiments conducted using retrospectively collected data from 519 patients treated at the HF Clinic of the University Hospital of Salerno have demonstrated the effectiveness of our model, surpassing the most commonly used machine learning algorithms. Indeed, the proposed GP-based classifier achieved a 96% average score for all considered evaluation metrics and fully supported the controls of medical staff. Our solution has the potential to impact clinical practice for HF by identifying patients at high risk of WHF and facilitating more rapid diagnosis, targeted treatment, and a reduction in hospitalizations.

Wearable Devices Based on Bioimpedance Test in Heart Failure: Clinical Relevance: Systematic Review

Background

Heart failure (HF) represents a frequent cause of hospital admission, with fluid overload directly contributing to decompensations. Bioimpedance (BI), a physical parameter linked to tissue hydration status, holds promise in monitoring congestion and improving prognosis. This systematic review aimed to assess the clinical relevance of BI-based wearable devices for HF fluid monitoring.

Methods

A systematic review of the published literature was conducted in five medical databases (PubMed, Scopus, Cochrane, Web of Science, and Embase) for studies assessing wearable BI-measuring devices on HF patients following PRISMA recommendations on February 4th, 2024. The risk of bias was evaluated using the ROBINS tool.

Results

The review included 10 articles with 535 participants (mean age 66.7 ± 8.9 years, males 70.4%). Three articles identified significant BI value differences between HF patients and controls or congestive vs non-congestive HF patients. Four articles focused on the devices' ability to predict HF worsening-related events, revealing an overall sensitivity of 70.0 (95% CI 68.8-71.1) and specificity of 89.1 (95% CI 88.3-89.9). One article assessed prognosis, showing that R80kHz decrease was related to all-cause-mortality with a hazard ratio (HR) of 5.51 (95% CI 1.55-23.32; p = 0.02) and the composite all-cause-mortality and HF admission with a HR of 4.96 (95% CI 1.82-14.37; p = 0.01).

Conclusions

BI-measuring wearable devices exhibit efficacy in detecting fluid overload and hold promise for HF monitoring. However, further studies and technological improvements are required to optimize their impact on prognosis compared to standard care before they can be routinely implemented in clinical practice.

PROSPERO Registration

The search protocol was registered at PROSPERO (CRD42024509914).

Non-invasive heart failure monitoring: leveraging smart scales and digital biomarkers to improve heart failure outcomes

Heart failure (HF) is a significant global concern, impacting patient morbidity, mortality, and healthcare costs. Guideline-directed medical therapy and various preventive measures have proven effective in improving clinical outcomes and reducing HF hospitalizations. Recent data indicates that remote HF monitoring facilitates early detection of HF decompensation by observing upstream events and parameters before clinical signs and symptoms manifest. Moreover, these innovative devices have been shown to decrease unnecessary HF hospitalizations and, in some cases, provide predictive insights before an actual HF incident. In this review, we aim to explore the data regarding smart scales and digital biomarkers and summarize both FDA-approved devices and emerging technologies by assessing their clinical utility, mechanism of HF decompensation detection, and ongoing trials. Furthermore, we also discuss the future trend of integrating these devices into routine clinical practice to improve patient clinical outcomes.

Seated Pulmonary Artery Pressure Monitoring in Patients With Heart Failure: Results of the PROACTIVE-HF Trial

BACKGROUND

Monitoring supine pulmonary artery pressures to guide heart failure (HF) management has reduced HF hospitalizations in select patients.

OBJECTIVES

The purpose of this study was to evaluate the effect of managing seated mean pulmonary artery pressure (mPAP) with the Cordella Pulmonary Artery sensor on outcomes in patients with HF.

METHODS

Following GUIDE-HF (Hemodynamic-GUIDEd Management of Heart Failure Trial), with U.S. Food and Drug Administration input, PROACTIVE-HF (A Prospective, Multi-Center, Open Label, Single Arm Clinical Trial Evaluating the Safety and Efficacy of the Cordella Pulmonary Artery Sensor System in NYHA Class III Heart Failure Patients trial) was changed from a randomized to a single-arm, open label trial, conducted at 75 centers in the USA and Europe. Eligible patients had chronic HF with NYHA functional class III symptoms, irrespective of the ejection fraction, and recent HF hospitalization and/or elevated natriuretic peptides. The primary effectiveness endpoint at 6 months required the HF hospitalization or all-cause mortality rate to be lower than a performance goal of 0.43 events/patient, established from previous hemodynamic monitoring trials. Primary safety endpoints at 6 months were freedom from device- or system-related complications or pressure sensor failure.

RESULTS

Between February 7, 2020, and March 31, 2023, 456 patients were successfully implanted in modified intent-to-treat cohort. The 6-month event rate was 0.15 (95% CI: 0.12-0.20) which was significantly lower than performance goal (0.15 vs 0.43; P < 0.0001). Freedom from device- or system-related complications was 99.2% and freedom from sensor failure was 99.8% through 6 months.

CONCLUSIONS

Remote management of seated mPAP is safe and results in a low rate of HF hospitalizations and mortality. These results support the use of seated mPAP monitoring and extend the growing body of evidence that pulmonary artery pressure-guided management improves outcomes in heart failure. (Multi-Center, Open Label, Single Arm Clinical Trial Evaluating the Safety and Efficacy of the Cordella Pulmonary Artery Sensor System in NYHA Class III Heart Failure Patients trial [PROACTIVE-HF]; NCT04089059).

Efficacy of the Cardiac Implantable Electronic Device Multisensory Triage-HF Algorithm in Heart Failure Care: A Real-World Clinical Experience

Heart failure (HF) admissions are burdensome, and the mainstay of prevention is the timely detection of impending fluid retention, creating a window for medical treatment intensification. This study evaluated the accuracy and performance of a Triage-HF-guided carepath in real-world ambulatory HF patients in daily clinical practice. In this prospective, observational study, 92 adult HF patients (71 males (78%), with a median age of 69 [IQR 59-75] years) with the Triage-HF algorithm activated in their cardiac implantable electronic devices (CIEDs), were monitored. Following high-risk alerts, an HF nurse contacted patients to identify signs and symptoms of fluid retention. The sensitivity and specificity were 83% and 97%, respectively. The positive predictive value was 89%, and negative predictive value was 94%. The unexplained alert rate was 0.05 alerts/patient year, and the false negative rate was 0.11 alerts/patient year. Ambulatory diuretics were initiated or escalated in 77% of high-risk alert episodes. In 23% (n = 6), admission was ultimately required. The median alert handling time was 2 days. Fifty-eight percent (n = 18) of high-risk alerts were classified as true positives in the first week, followed by 29% in the second-third weeks (n = 9), and 13% (n = 4) in the fourth-sixth weeks. Common sensory triggers included an elevated night ventricular rate (84%), OptiVol (71%), and reduced patient activity (71%). The CIED-based Triage-HF algorithm-driven carepath enables the timely detection of impending fluid retention in a contemporary ambulatory setting, providing an opportunity for clinical action.

Impact of a pharmacist-managed remote heart failure program in patients with a multisensor-capable implanted device

PURPOSE

Added layers of remote management in heart failure (HF) have become available for patients with an implantable cardioverter defibrillator (ICD). The aim of this study was to investigate the impact of pharmacist-managed HF monitoring in patients with a multisensor-capable ICD.

METHODS

This was a retrospective, data-only, single-arm study that compared primary outcome events individually in the preactivation and postactivation periods at a single center. The primary outcomes were the total number of all-cause and HF-related hospitalizations and all-cause emergency department (ED) visits and the median length of stay for all-cause and HF-related hospitalizations. The secondary outcome quantified medication utilization.

RESULTS

In total, 132 patients completed the 1-year follow-up period. Overall, there was a 49% reduction in the number of patients with an all-cause hospitalization, a 77% reduction in the number of patients with an HF-related hospitalization, and a 36% reduction in the number of patients with an ED visit. More patients were hospitalized, visited the ED (P < 0.005), and had a longer median length of stay for all-cause hospitalizations in the preactivation period (P < 0.05). Overall medication utilization increased in the postactivation period.

CONCLUSION

A pharmacist-led remote monitoring program, utilizing a multisensor diagnostic, was effective at significantly reducing hospitalizations, ED visits, and length of stay.

Role of splanchnic circulation in the pathogenesis of heart failure: State-of-the-art review

A hallmark of heart failure (HF), whether it presents itself during rest or periods of physical exertion, is the excessive elevation of intracardiac filling pressures at rest or with exercise. Many mechanisms contribute to the elevated intracardiac filling pressures, and notably, the concept of volume redistribution has gained attention as a cause of the elevated intracardiac filling pressures in patients with HF, particularly HF with preserved ejection fraction, who often present without symptoms at rest, with shortness of breath and fatigue appearing only during exertion. This phenomenon suggests cardiopulmonary system non-compliance and inappropriate volume distribution between the stressed and unstressed blood volume components. A substantial proportion of the intravascular blood volume is in the splanchnic vascular compartment in the abdomen. Preclinical and clinical investigations support the critical role of the sympathetic nervous system in modulating the capacitance and compliance of the splanchnic vascular bed via modulation of the greater splanchnic nerve (GSN). The GSN activation by stressors such as exercise causes excessive splanchnic vasoconstriction, which may contribute to the decompensation of chronic HF via volume redistribution from the splanchnic vascular bed to the central compartment. Accordingly, for example, GSN ablation for volume management has been proposed as a potential therapeutic intervention to increase unstressed blood volume. Here we provide a comprehensive review of the role of splanchnic circulation in the pathogenesis of HF and potential novel treatment options for redistributing blood volume to improve symptoms and prognosis in patients with HF.

Implementation of remote monitoring strategies to improve chronic heart failure management

PURPOSE OF REVIEW

The goal of this review is to describe the current evidence available for remote monitoring devices available for patients with chronic heart failure, and also detail practical clinical recommendations for implementing these tools in daily clinical practice.

RECENT FINDINGS

Several devices ranging from sophisticated multiparametric algorithms in defibrillators, implantable pulmonary artery pressure sensors, and wearable devices to measure thoracic impedance can be utilized as important adjunctive tools to reduce the risk of heart failure hospitalization in patients with chronic heart failure. Pulmonary artery pressure sensors provide the most granular data regarding hemodynamic status, while alerts from wearable devices for thoracic impedance and defibrillator-based algorithms increase the likelihood of worsening clinical status while also having high negative predictive value when values are within normal range.

SUMMARY

Multiple device-based monitoring strategies are available to reduce longitudinal risk in patients with chronic heart failure. Further studies are needed to best understand a practical pathway to integrate multiple signals of data for early clinical decompensation risk predictionVideo abstract: http://links.lww.com/HCO/A95.

A Novel Subcutaneous Furosemide Formulation for Outpatient Management of Heart Failure

In patients with fluid overload and congestion, parenteral diuretic therapy is frequently utilized. However, administration of parenteral diuretic therapy commonly requires hospital admission or outpatient clinic visits. Furoscix (scPharmaceuticals, Burlington, MA), a subcutaneous formulation of furosemide designed for home use, offers new treatment possibilities with the potential for profound cost savings for patients and health systems. Currently, subcutaneous furosemide formulations have been studied in palliative care populations and outpatient clinics, however, new literature has evaluated utility in prescribing on discharge from the emergency department. This review aims to describe the pharmacokinetic profile and utilization of subcutaneous furosemide for treatment of congestion in patients with heart failure.

A comprehensive review on efficient artificial intelligence models for classification of abnormal cardiac rhythms using electrocardiograms

Deep learning has made many advances in data classification using electrocardiogram (ECG) waveforms. Over the past decade, data science research has focused on developing artificial intelligence (AI) based models that can analyze ECG waveforms to identify and classify abnormal cardiac rhythms accurately. However, the primary drawback of the current AI models is that most of these models are heavy, computationally intensive, and inefficient in terms of cost for real-time implementation. In this review, we first discuss the current state-of-the-art AI models utilized for ECG-based cardiac rhythm classification. Next, we present some of the upcoming modeling methodologies which have the potential to perform real-time implementation of AI-based heart rhythm diagnosis. These models hold significant promise in being lightweight and computationally efficient without compromising the accuracy. Contemporary models predominantly utilize 12-lead ECG for cardiac rhythm classification and cardiovascular status prediction, increasing the computational burden and making real-time implementation challenging. We also summarize research studies evaluating the potential of efficient data setups to reduce the number of ECG leads without affecting classification accuracy. Lastly, we present future perspectives on AI's utility in precision medicine by providing opportunities for accurate prediction and diagnostics of cardiovascular status in patients.

Clinical Predictive Modeling of Heart Failure: Domain Description, Models' Characteristics and Literature Review

This study attempts to identify and briefly describe the current directions in applied and theoretical clinical prediction research. Context-rich chronic heart failure syndrome (CHFS) telemedicine provides the medical foundation for this effort. In the chronic stage of heart failure, there are sudden exacerbations of syndromes with subsequent hospitalizations, which are called acute decompensation of heart failure (ADHF). These decompensations are the subject of diagnostic and prognostic predictions. The primary purpose of ADHF predictions is to clarify the current and future health status of patients and subsequently optimize therapeutic responses. We proposed a simplified discrete-state disease model as an attempt at a typical summarization of a medical subject before starting predictive modeling. The study tries also to structure the essential common characteristics of quantitative models in order to understand the issue in an application context. The last part provides an overview of prediction works in the field of CHFS. These three parts provide the reader with a comprehensive view of quantitative clinical predictive modeling in heart failure telemedicine with an emphasis on several key general aspects. The target community is medical researchers seeking to align their clinical studies with prognostic or diagnostic predictive modeling, as well as other predictive researchers. The study was written by a non-medical expert.

Implementation of evidence-based heart failure management: Regional variations between Japan and the USA

The implementation of optimal medical therapy is a crucial step in the management of heart failure with reduced ejection fraction (HFrEF). Over the prior three decades, there have been substantial advancements in this field. Early and accurate detection and diagnosis of the disease allow for the appropriate initiation of optimal therapies. The initiation and uptitration of optimal medical therapy including renin-angiotensin system inhibitor, beta-blocker, mineralocorticoid receptor antagonist, and sodium-glucose cotransporter 2 inhibitor in the early stage would prevent the progression and morbidity of HF. Concurrently, individualized surveillance to recognize and treat signs of disease progression is critical given the progressive nature of HF, even among stable patients on optimal therapy. However, there remains a wide variation in regional practice regarding the initiation, titration, and long-term monitoring of this therapy. To cover the differences in approaches toward HFrEF management and the implementation of guideline-based medical therapy, we discuss the current evidence in this arena, differences in present guideline recommendations, and compare practice patterns in Japan and the USA using a case of new-onset HF as an example. We will discuss pros and cons of the way HF is managed in each region, and highlight potential areas for improvement in care.

Home Bioelectrical Impedance Analysis Management System in Patients With Heart Failure: Rationale and Study Design

Body fluid monitoring and management are essential to control dyspnea and prevent re-hospitalization in patients with chronic heart failure (HF). There are several methods to estimate and monitor patient's volume status, such as symptoms, signs, body weight, and implantable devices. However, these methods might be difficult to use for reasons that are slow to reflect body water change, inaccurate in specific patients' condition, or invasive. Bioelectrical impedance analysis (BIA) is a novel method for body water monitoring in patients with HF, and the value in prognosis has been proven in previous studies. We aim to determine the efficacy and safety of home BIA body water monitoring-guided HF treatment in patients with chronic HF. This multi-center, open-label, randomized control trial will enroll patients with HF who are taking loop diuretics. The home BIA group patients will be monitored for body water using a home BIA device and receive messages regarding their edema status and direction of additional diuretics usage or behavioral changes through the linked application system once weekly. The control group patients will receive the usual HF management. The primary endpoint is the change in N-terminal prohormone of brain natriuretic peptide levels from baseline after 12 weeks. This trial will provide crucial evidence for patient management with a novel home BIA body water monitoring system in patients with HF.

Fewer Worsening Heart Failure Events With HeartLogic on top of Standard Care: a Propensity-Matched Cohort Analysis

BACKGROUND

The implantable cardiac defibrillator-based HeartLogic algorithm aims to detect impending fluid retention in patients with heart failure (HF). Studies show that HeartLogic is safe to integrate into clinical practice. The current study investigates whether HeartLogic provides clinical benefit on top of standard care and device telemonitoring in patients with HF.

METHODS

A multicenter, retrospective, propensity-matched cohort analysis was performed in patients with HF and implantable cardiac defibrillators, and it compared HeartLogic to conventional telemonitoring. The primary endpoint was the number of worsening HF events. Hospitalizations and ambulatory visits due to HF were also evaluated.

RESULTS

Propensity score matching yielded 127 pairs (median age 68 years, 80% male). Worsening HF events occurred more frequently in the control group (2; IQR 0-4) compared to the HeartLogic group (1; IQR 0-3; P = 0.004). The number of HF hospitalization days was higher in controls than in the HeartLogic group (8; IQR 5-12 vs 5; IQR 2-7; P = 0.023), and ambulatory visits for diuretic escalation were more frequent in the control group than in the HeartLogic group (2; IQR 0-3 vs 1; IQR 0-2; P = 0.0001).

CONCLUSION

Integrating the HeartLogic algorithm in a well-equipped HF care path on top of standard care is associated with fewer worsening HF events and shorter duration of fluid retention-related hospitalizations.

Telemetric long-term assessment of autonomic function in experimental heart failure

Despite medical advances in the treatment of heart failure (HF), mortality remains high. It has been shown that alterations of the autonomic-nervous-system (ANS) are associated with HF progression and increased mortality. Preclinical models are required to evaluate the effectiveness of novel treatments modulating the autonomic imbalance. However, there are neither standard models nor diagnostic methods established to measure sympathetic and parasympathetic outflow continuously. Digital technologies might be a reliable tool for continuous assessment of autonomic function within experimental HF models. Telemetry devices and pacemakers were implanted in beagle dogs (n = 6). HF was induced by ventricular pacing. Cardiac hemodynamics, plasma catecholamines and parameter describing the ANS ((heart rate variability (HRV), deceleration capacity (DC), and baroreflex sensitivity (BRS)) were continuously measured at baseline, during HF conditions and during recovery phase. The pacing regime led to the expected depression in cardiac hemodynamics. Telemetric assessment of the ANS function showed a significant decrease in Total power, DC, and Heart rate recovery, whereas BRS was not significantly affected. In contrast, plasma catecholamines, revealing sympathetic activity, showed only a significant increase in the recovery phase. A precise diagnostic of the ANS in the context of HF is becoming increasingly important in experimental models. Up to now, these models have shown many limitations. Here we present the continuous assessment of the autonomic function in the progression of HF. We could demonstrate the advantage of highly resolved ANS measurement by HR and BP derived parameters due to early detection of an autonomic imbalance in the progression of HF.

A novel opportunity to improve heart failure care: focusing on subcutaneous furosemide

The prevalence of heart failure (HF) continues to rise in developed nations. Symptomatic congestion is the most common reason for patients to seek medical attention, and management often requires intravenous (IV) diuretic administration in the hospital setting. Typically, the number of admissions increases as the disease progresses, not only impacting patient survival and quality of life but also driving up healthcare expenditures. pH-neutral furosemide delivered subcutaneously using a proprietary, single-use infusor system (Furoscix) has a tremendous potential to transition in-hospital decongestive therapy to the outpatient setting or to the patient's home. This review is aimed at providing an overview of the pharmacodynamic and pharmacokinetic profile of the novel pH-neutral furosemide in addition to the most recent clinical trials demonstrating its benefit when used in the home setting. Given the newest data and approval by the Food and Drug Administration in the US, it has the potential to revolutionize the care of patients with decompensated HF. Undoubtedly, it will lead to improved quality of life as well as significantly reduced healthcare costs related to hospital admissions.

Heart failure management guided by remote multiparameter monitoring: A meta-analysis

BACKGROUND

Several implant-based remote monitoring strategies are currently tested to optimize heart failure (HF) management by anticipating clinical decompensation and preventing hospitalization. Among these solutions, the modern implantable cardioverter-defibrillator and cardiac resynchronization therapy devices have been equipped with sensors allowing continuous monitoring of multiple preclinical markers of worsening HF, including factors of autonomic adaptation, patient activity, and intrathoracic impedance.

OBJECTIVES

We aimed to assess whether implant-based multiparameter remote monitoring strategy for guided HF management improves clinical outcomes when compared to standard clinical care.

METHODS

A systematic literature research for randomized controlled trials (RCTs) comparing multiparameter-guided HF management versus standard of care was performed on PubMed, Embase, and CENTRAL databases. Incidence rate ratios (IRRs) and associated 95% confidence intervals (CIs) were calculated using the Poisson regression model with random study effects. The primary outcome was a composite of all-cause death and HF hospitalization events, whereas secondary endpoints included the individual components of the primary outcome.

RESULTS

Our meta-analysis included 6 RCTs, amounting to a total of 4869 patients with an average follow-up time of 18 months. Compared with standard clinical management, the multiparameter-guided strategy reduced the risk of the primary composite outcome (IRR 0.83, 95%CI 0.71-0.99), driven by statistically significant effect on both HF hospitalization events (IRR 0.75, 95%CI 0.61-0.93) and all-cause death (IRR 0.80, 95%CI 0.66-0.96).

CONCLUSION

Implant-based multiparameter remote monitoring strategy for guided HF management is associated with significant benefit on clinical outcomes compared to standard clinical care, providing a benefit on both hospitalization events and all-cause death.

Efficacy of pulmonary artery pressure monitoring in patients with chronic heart failure: a meta-analysis of three randomized controlled trials

AIMS

Adjustment of treatment based on remote monitoring of pulmonary artery (PA) pressure may reduce the risk of hospital admission for heart failure (HF). We have conducted a meta-analysis of large randomized trials investigating this question.

METHODS AND RESULTS

A systematic literature search was performed for randomized clinical trials with PA pressure monitoring devices in patients with HF. The primary outcome of interest was the total number of HF hospitalizations. Other outcomes assessed were urgent visits leading to treatment with intravenous diuretics, all-cause mortality, and composites. Treatment effects are expressed as hazard ratios, and pooled effect estimates were obtained applying random effects meta-analyses. Three eligible randomized clinical trials were identified that included 1898 outpatients in New York Heart Association functional classes II-IV, either hospitalized for HF in the prior 12 months or with elevated plasma NT-proBNP concentrations. The mean follow-up was 14.7 months, 67.8% of the patients were men, and 65.8% had an ejection fraction ≤40%. Compared to patients in the control group, the hazard ratio (95% confidence interval) for total HF hospitalizations in those randomized to PA pressure monitoring was 0.70 (0.58-0.86) (P = .0005). The corresponding hazard ratio for the composite of total HF hospitalizations, urgent visits and all-cause mortality was 0.75 (0.61-0.91; P = .0037) and for all-cause mortality 0.92 (0.73-1.16). Subgroup analyses, including ejection fraction phenotype, revealed no evidence of heterogeneity in the treatment effect.

CONCLUSION

The use of remote PA pressure monitoring to guide treatment of patients with HF reduces episodes of worsening HF and subsequent hospitalizations.

Recent successes in heart failure treatment

Remarkable recent advances have revolutionized the field of heart failure. Survival has improved among individuals with heart failure and a reduced ejection fraction and for the first time, new therapies have been shown to improve outcomes across the entire ejection fraction spectrum of heart failure. Great strides have been taken in the treatment of specific cardiomyopathies such as cardiac amyloidosis and hypertrophic cardiomyopathy, whereby conditions once considered incurable can now be effectively managed with novel genetic and molecular approaches. Yet there remain substantial residual unmet needs in heart failure. The translation of successful clinical trials to improved patient outcomes is limited by large gaps in implementation of care, widespread lack of disease awareness and poor understanding of the socioeconomic determinants of outcomes and how to address disparities. Ongoing clinical trials, advances in phenotype segmentation for precision medicine and the rise in technology solutions all offer hope for the future.

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.

Telemonitoring for heart failure: a meta-analysis

AIMS

Telemonitoring modalities in heart failure (HF) have been proposed as being essential for future organization and transition of HF care, however, efficacy has not been proven. A comprehensive meta-analysis of studies on home telemonitoring systems (hTMS) in HF and the effect on clinical outcomes are provided.

METHODS AND RESULTS

A systematic literature search was performed in four bibliographic databases, including randomized trials and observational studies that were published during January 1996-July 2022. A random-effects meta-analysis was carried out comparing hTMS with standard of care. All-cause mortality, first HF hospitalization, and total HF hospitalizations were evaluated as study endpoints. Sixty-five non-invasive hTMS studies and 27 invasive hTMS studies enrolled 36 549 HF patients, with a mean follow-up of 11.5 months. In patients using hTMS compared with standard of care, a significant 16% reduction in all-cause mortality was observed [pooled odds ratio (OR): 0.84, 95% confidence interval (CI): 0.77-0.93, I2: 24%], as well as a significant 19% reduction in first HF hospitalization (OR: 0.81, 95% CI 0.74-0.88, I2: 22%) and a 15% reduction in total HF hospitalizations (pooled incidence rate ratio: 0.85, 95% CI 0.76-0.96, I2: 70%).

CONCLUSION

These results are an advocacy for the use of hTMS in HF patients to reduce all-cause mortality and HF-related hospitalizations. Still, the methods of hTMS remain diverse, so future research should strive to standardize modes of effective hTMS.

Heart Failure with Reduced Ejection Fraction: The Role of Cardiovascular and Lung Ultrasound beyond Ejection Fraction

Heart failure with reduced ejection fraction (HFrEF) is considered a major health care problem with frequent decompensations, high hospitalization and mortality rates. In severe heart failure (HF), the symptoms are refractory to medical treatment and require advanced therapeutic strategies. Early recognition of HF sub- and decompensation is the cornerstone of the timely treatment intensification and, therefore, improvement in the prognosis. Echocardiography is the gold standard for the assessment of systolic and diastolic functions. It allows one to obtain accurate and non-invasive measurements of the ventricular function in HF. In severely compromised HF patients, advanced cardiovascular ultrasound modalities may provide a better assessment of intracardiac hemodynamic changes and subclinical congestion. Particularly, cardiovascular and lung ultrasound allow us to make a more accurate diagnosis of subclinical congestion in HFrEF. The aim of this review was to summarize the advantages and limitations of the currently available ultrasound modalities in the ambulatory monitoring of patients with HFrEF.

A Wearable Multi-Sensor Array Enables the Recording of Heart Sounds in Homecare

The home monitoring of patients affected by chronic heart failure (CHF) is of key importance in preventing acute episodes. Nevertheless, no wearable technological solution exists to date. A possibility could be offered by Cardiac Time Intervals extracted from simultaneous recordings of electrocardiographic (ECG) and phonocardiographic (PCG) signals. Nevertheless, the recording of a good-quality PCG signal requires accurate positioning of the stethoscope over the chest, which is unfeasible for a naïve user as the patient. In this work, we propose a solution based on multi-source PCG. We designed a flexible multi-sensor array to enable the recording of heart sounds by inexperienced users. The multi-sensor array is based on a flexible Printed Circuit Board mounting 48 microphones with a high spatial resolution, three electrodes to record an ECG and a Magneto-Inertial Measurement Unit. We validated the usability over a sample population of 42 inexperienced volunteers and found that all subjects could record signals of good to excellent quality. Moreover, we found that the multi-sensor array is suitable for use on a wide population of at-risk patients regardless of their body characteristics. Based on the promising findings of this study, we believe that the described device could enable the home monitoring of CHF patients soon.

Noninvasive assessment of pulmonary congestion in heart failure: Need of the hour

Early pulmonary congestion detection and surveillance in acute heart failure patients can prevent decompensation, minimize hospitalizations, and improve prognosis. In India, the warm and wet types of HF are still the most common types and residual congestion at discharge is still a significant concern. Thus, there is an urgent need for a reliable and sensitive means of identifying residual and subclinical congestion. Two such monitoring systems are available and approved by US FDA. These include CardioMEMS HF System (Abbott, Sylmar, California) and ReDS System (Sensible Medical Innovations, Ltd., Nanya, Israel). CardioMEMS is a wireless pressure-sensitive implantable device, while ReDS is a wearable noninvasive device for measurement of the lung fluid and hence direct detection of PC. This review discusses the role of noninvasive assessment in PC monitoring in patients with heart failure and its implications from an Indian perspective.

Remote haemodynamic monitoring of pulmonary artery pressures in patients with chronic heart failure (MONITOR-HF): a randomised clinical trial

BACKGROUND

The effect of haemodynamic monitoring of pulmonary artery pressure has predominantly been studied in the USA. There is a clear need for randomised trial data from patients treated with contemporary guideline-directed-medical-therapy with long-term follow-up in a different health-care system.

METHODS

MONITOR-HF was an open-label, randomised trial, done in 25 centres in the Netherlands. Eligible patients had chronic heart failure of New York Heart Association class III and a previous heart failure hospitalisation, irrespective of ejection fraction. Patients were randomly assigned (1:1) to haemodynamic monitoring (CardioMEMS-HF system, Abbott Laboratories, Abbott Park, IL, USA) or standard care. All patients were scheduled to be seen by their clinician at 3 months and 6 months, and every 6 months thereafter, up to 48 months. The primary endpoint was the mean difference in the Kansas City Cardiomyopathy Questionnaire (KCCQ) overall summary score at 12 months. All analyses were by intention-to-treat. This trial was prospectively registered under the clinical trial registration number NTR7673 (NL7430) on the International Clinical Trials Registry Platform.

FINDINGS

Between April 1, 2019, and Jan 14, 2022, we randomly assigned 348 patients to either the CardioMEMS-HF group (n=176 [51%]) or the control group (n=172 [49%]). The median age was 69 years (IQR 61-75) and median ejection fraction was 30% (23-40). The difference in mean change in KCCQ overall summary score at 12 months was 7·13 (95% CI 1·51-12·75; p=0·013) between groups (+7·05 in the CardioMEMS group, p=0·0014, and -0·08 in the standard care group, p=0·97). In the responder analysis, the odds ratio (OR) of an improvement of at least 5 points in KCCQ overall summary score was OR 1·69 (95% CI 1·01-2·83; p=0·046) and the OR of a deterioration of at least 5 points was 0·45 (0·26-0·77; p=0·0035) in the CardioMEMS-HF group compared with in the standard care group. The freedom of device-related or system-related complications and sensor failure were 97·7% and 98·8%, respectively.

INTERPRETATION

Haemodynamic monitoring substantially improved quality of life and reduced heart failure hospitalisations in patients with moderate-to-severe heart failure treated according to contemporary guidelines. These findings contribute to the aggregate evidence for this technology and might have implications for guideline recommendations and implementation of remote pulmonary artery pressure monitoring.

FUNDING

The Dutch Ministry of Health, Health Care Institute (Zorginstituut), and Abbott Laboratories.

Remote Monitoring for Heart Failure Management at Home

Early telemonitoring of weights and symptoms did not decrease heart failure hospitalizations but helped identify steps toward effective monitoring programs. A signal that is accurate and actionable with response kinetics for early re-assessment is required for the treatment of patients at high risk, while signal specifications differ for surveillance of low-risk patients. Tracking of congestion with cardiac filling pressures or lung water content has shown most impact to decrease hospitalizations, while multiparameter scores from implanted rhythm devices have identified patients at increased risk. Algorithms require better personalization of signal thresholds and interventions. The COVID-19 epidemic accelerated transition to remote care away from clinics, preparing for new digital health care platforms to accommodate multiple technologies and empower patients. Addressing inequities will require bridging the digital divide and the deep gap in access to HF care teams, who will not be replaced by technology but by care teams who can embrace it.

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.

Use of a Cardiac Scale to Predict Heart Failure Events: Design of SCALE-HF 1

BACKGROUND

There is a need for simple, noninvasive solutions to remotely monitor and predict worsening heart failure (HF) events. SCALE-HF 1 (Surveillance and Alert-Based Multiparameter Monitoring to Reduce Worsening Heart Failure Events) is a prospective, multicenter study that will develop and assess the accuracy of the heart function index-a composite algorithm of noninvasive hemodynamic biomarkers from a cardiac scale-in predicting worsening HF events.

METHODS

Approximately 300 patients with chronic HF and recent decompensation will be enrolled in this observational study for model development. Patients will be encouraged to take daily cardiac scale measurements.

RESULTS

Approximately 50 HF events, defined as an urgent, unscheduled clinic, emergency department, or hospitalization for worsening HF will be used for model development. The composite index will be developed from hemodynamic biomarkers derived from ECG, ballistocardiogram, and impedance plethysmogram signals measured from the cardiac scale. Biomarkers of interest include weight, peripheral impedance, pulse rate and variability, and estimates of stroke volume, cardiac output, and blood pressure captured through the cardiac scale. The sensitivity, unexplained alert rate, and alerting time of the index in predicting worsening HF events will be evaluated and compared with the performance of simple weight-based rule-of-thumb algorithms (eg, weight increase of 3 lbs in 1 day or 5 lbs in 7 days) that are often used in practice.

CONCLUSIONS

SCALE-HF 1 is the first study to develop and evaluate the performance of a composite index derived from noninvasive hemodynamic biomarkers measured from a cardiac scale in predicting worsening HF events. Subsequent studies will validate the heart function index and assess its ability to improve patient outcomes.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT04882449.

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.

Changes in cardiac acoustic biomarkers before and after cardiac events in a patient with right-sided heart failure due to cor pulmonale

Chronic heart failure (HF) has various phenotypes. It is accompanied by repeated hospitalizations over a long period. Therefore, accumulating long-term observational data of patients with various backgrounds is important to establish a prediction technology for the exacerbation of HF. In a patient with chronic right-sided HF caused by cor pulmonale, heart sounds and electrocardiograms were recorded at home or our hospital twice a week for 7 months including the stable (31 days), pre-exacerbation (2 weeks just before the onset of exacerbation), and hospitalization periods and quantified as cardiac acoustic biomarkers (CABs) using AUDICOR technology (Inovise Medical, Inc., Portland, OR, USA). The relationship between the change in CABs and hospitalization events due to HF were investigated. During the pre-exacerbation period just before the onset of exacerbation of HF leading to hospitalization, inaudible changes in the third heart sound (S3) strength that were probably derived from the right heart were observed. Although the values of the fourth heart sound (S4) strength were high during the stable and pre-exacerbation period, values decreased markedly during hospitalization. These findings suggest that CABs including S3 and S4 are useful for the early detection of signs of HF exacerbation.

Learning Objective

In a case of chronic right-sided heart failure, the change in the third heart sound (S3) caused by the right ventricle could be detected using cardiac acoustic biomarkers in exacerbations of heart failure. Even if S3 is inaudible by auscultation, it is possible to observe its changes using quantification technology.

Remote Monitoring of Cardiac Implantable Electronic Devices: What is the Evidence?

PURPOSE OF REVIEW

This review offers an overview of the evidence in diagnostic and therapeutic applications of remote monitoring implantable devices.

RECENT FINDINGS

Remote monitoring of cardiac implantable devices has become more and more popular in recent years as healthcare is moving towards a more patient centralized system. For heart failure patients with an ICD or pacemaker, there is controversial evidence regarding improvements in the clinical outcome, e.g., reduction of hospitalization rates or overall mortality. New developments as hemodynamic remote monitoring via measurement of the pulmonary artery pressure are promising technical achievements showing encouraging results. In cardiac remote monitoring of syncope and arrhythmias, implantable loop recorder plays an important role in diagnostic algorithms. Although there is controversial evidence according to remote monitoring of implantable devices, its use is rapidly expanding, giving healthcare providers the opportunity to react promptly to worsening of their patients. Adequate evaluation of the data created by remote monitoring systems remains an unsolved challenge of contemporary healthcare services.

Assessing Correlation Between Thoracic Impedance and Remotely Monitored Pulmonary Artery Pressure in Chronic Systolic Heart Failure

Background

Heart failure (HF) readmission continues to be a major health problem. Monitoring pulmonary artery pressure (PAP) and thoracic impedance (TI) are the two modalities utilized for early identification of decompensation in HF patients. We aimed to assess the correlation between these two modalities in patients who simultaneously had both the devices.

Methods

Patients with history of New York Heart Association class III systolic HF with a pre-implanted intracardiac defibrillator (ICD) capable of monitoring TI and pre-implanted CardioMEMs™ remote HF monitoring device were included. Hemodynamic data including TI and PAPs were measured at baseline and then weekly. Weekly percentage change was then calculated as: Weekly percentage change = (week 2 - week1)/week 1 × 100. Variability between the methods was expressed by Bland-Altman analysis. Significance was determined as a P-value < 0.05.

Results

Nine patients met the inclusion criteria. There was no significant correlation between the assessed weekly percentage changes in pulmonary artery diastolic pressure (PAdP) and TI measurements (r = -0.180, P = 0.065). Using Bland-Altman analytic methods, both methods had no significant difference in agreement (0.011±0.094%, P = 0.215). With the linear regression model applied for Bland-Altman analysis, the two methods appeared to have proportional bias without agreement (unstandardized beta-coefficient of 1.91, t 22.9, P ≤ 0.001).

Conclusion

Our study demonstrated that variations exist between measurement of PAdP and TI; however, there is no significant correlation between weekly variations between them.

Rationale and Design of the Proactive-HF Trial for Managing Patients With NYHA Class III Heart Failure by Using the Combined Cordella Pulmonary Artery Sensor and the Cordella Heart Failure System

BACKGROUND

Optimizing guideline-directed medical therapy (GDMT) and monitoring congestion in patients with heart failure (HF) are key to disease management and preventing hospitalizations. A pulmonary artery pressure (PAP)-guided HF management system providing access to body weight, blood pressure, heart rate, blood oxygen saturation, PAP, and symptoms, may provide new insights into the effects of patient engagement and comprehensive care for remote GDMT titration and congestion management.

METHODS

The PROACTIVE-HF study was originally approved in 2018 as a prospective, randomized, controlled, single-blind, multicenter trial to evaluate the safety and effectiveness of the Cordella PAP Sensor in patients with HF and with New York Heart Association (NYHA) functional class III symptoms. Since then, robust clinical evidence supporting PAP-guided HF management has emerged, making clinical equipoise and enrolling patients into a standard-of-care control arm challenging. Therefore, PROACTIVE-HF was changed to a single-arm trial in 2021 with prespecified safety and effectiveness endpoints to provide evidence for a similar risk/benefit profile as the CardioMEMS HF System.

CONCLUSION

The single-arm PROACTIVE-HF trial is expected to further demonstrate the benefits of PAP-guided HF management of patients with NYHA class III HF. The addition of vital signs, patient engagement and self-reported symptoms may provide new insights into remote GDMT titration and congestion management.

Patients' Information Needs Related to a Monitoring Implant for Heart Failure: Co-designed Study Based on Affect Stories

BACKGROUND

RealWorld4Clinic is a European consortium that is currently developing an implantable monitoring device for acute heart failure prevention.

OBJECTIVE

This study aimed to identify the main issues and information needs related to this new cardiac implant from the patients' perspective.

METHODS

A total of 3 patient collaborators were recruited to help us design the study. During 4 remotely held meetings (each lasting for 2 hours), we defined the main questions and hypotheses together. Next, 26 additional interviews were conducted remotely to test these hypotheses. During both phases, we used affect stories, which are life narratives focusing on affect and the relationship between patients and the care ecosystem, to highlight the main social issues that should be addressed by the research according to the patients.

RESULTS

Context of diagnosis, age, and severity of illness strongly influence patient experience. However, these variables do not seem to influence the choice regarding being implanted, which relies mostly on the individual patient's trust in their physicians. It seems that the major cause of anxiety for the patient is not the implant but the disease itself, although some people may initially be concerned over the idea of becoming a cyborg. Remote monitoring of cardiac implants should draw on existing remote disease management programs focusing on a long-term relationship between the patient and their medical team.

CONCLUSIONS

Co-design with affect stories is a useful method for quickly identifying the main social issues related to information about a new health technology.

Assessment of filling pressures and fluid overload in heart failure: an updated perspective

Congestion plays a major role in the pathogenesis, presentation, and prognosis of heart failure and is an important therapeutic target. However, its severity and organ and compartment distribution vary widely among patients, illustrating the complexity of this phenomenon. Although clinical symptoms and signs are useful to assess congestion and manage volume status in individual patients, they have limited sensitivity and do not allow identification of congestion phenotype. This leads to diagnostic uncertainty and hampers therapeutic decision-making. The present article provides an updated overview of circulating biomarkers, imaging modalities (ie, cardiac and extracardiac ultrasound), and invasive techniques that might help clinicians to identify different congestion profiles and guide the management strategy in this diverse population of high-risk patients with heart failure.

Device-based remote monitoring strategies for congestion-guided management of patients with heart failure: a systematic review and meta-analysis

AIMS

Pre-clinical congestion markers of worsening heart failure (HF) can be monitored by devices and may support the management of patients with HF. We aimed to assess whether congestion-guided HF management according to device-based remote monitoring strategies is more effective than standard therapy.

METHODS AND RESULTS

A comprehensive literature research for randomized controlled trials (RCTs) comparing device-based remote monitoring strategies for congestion-guided HF management versus standard therapy was performed on PubMed, Embase, and CENTRAL databases. Incidence rate ratios (IRRs) and associated 95% confidence intervals (CIs) were calculated using the Poisson regression model with random study effects. The primary outcome was a composite of all-cause death and HF hospitalizations. Secondary endpoints included the individual components of the primary outcome. A total of 4347 patients from eight RCTs were included. Findings varied according to the type of parameters monitored. Compared with standard therapy, haemodynamic-guided strategy (4 trials, 2224 patients, 12-month follow-up) reduced the risk of the primary composite outcome (IRR 0.79, 95% CI 0.70-0.89) and HF hospitalizations (IRR 0.76, 95% CI 0.67-0.86), without a significant impact on all-cause death (IRR 0.93, 95% CI 0.72-1.21). In contrast, impedance-guided strategy (4 trials, 2123 patients, 19-month follow-up) did not provide significant benefits.

CONCLUSION

Haemodynamic-guided HF management is associated with better clinical outcomes as compared to standard clinical care.

Noninvasive Venous Waveform Analysis Correlates With Pulmonary Capillary Wedge Pressure and Predicts 30-Day Admission in Patients With Heart Failure Undergoing Right Heart Catheterization

BACKGROUND

Heart failure is the leading cause of hospitalization in the elderly and readmission is common. Clinical indicators of congestion may not precede acute congestion with enough time to prevent hospital admission for heart failure. Thus, there is a large and unmet need for accurate, noninvasive assessment of congestion. Noninvasive venous waveform analysis in heart failure (NIVAHF) is a novel, noninvasive technology that monitors intravascular volume status and hemodynamic congestion. The objective of this study was to determine the correlation of NIVAHF with pulmonary capillary wedge pressure (PCWP) and the ability of NIVAHF to predict 30-day admission after right heart catheterization.

METHODS AND RESULTS

The prototype NIVAHF device was compared with the PCWP in 106 patients undergoing right heart catheterization. The NIVAHF algorithm was developed and trained to estimate the PCWP. NIVA scores and central hemodynamic parameters (PCWP, pulmonary artery diastolic pressure, and cardiac output) were evaluated in 84 patients undergoing outpatient right heart catheterization. Receiver operating characteristic curves were used to determine whether a NIVA score predicted 30-day hospital admission. The NIVA score demonstrated a positive correlation with PCWP (r = 0.92, n = 106, P < .0001). The NIVA score at the time of hospital discharge predicted 30-day admission with an AUC of 0.84, a NIVA score of more than 18 predicted admission with a sensitivity of 91% and specificity of 56%. Residual analysis suggested that no single patient demographic confounded the predictive accuracy of the NIVA score.

CONCLUSIONS

The NIVAHF score is a noninvasive monitoring technology that is designed to provide an estimate of PCWP. A NIVA score of more than 18 indicated an increased risk for 30-day hospital admission. This noninvasive measurement has the potential for guiding decongestive therapy and the prevention of hospital admission in patients with heart failure.

Effects of remote haemodynamic-guided heart failure management in patients with different subtypes of pulmonary hypertension: insights from the MEMS-HF study

AIM

The CardioMEMS European Monitoring Study for Heart Failure (MEMS-HF) investigated safety and efficacy of pulmonary artery pressure (PAP)-guided remote patient management (RPM) in New York Heart Association (NYHA) class III outpatients with at least one heart failure hospitalization (HFH) during the previous 12 months. This pre-specified subgroup analysis investigated whether RPM effects depended on presence and subtype of pulmonary hypertension (PH).

METHODS AND RESULTS

In 106/234 MEMS-HF participants, Swan-Ganz catheter tracings obtained during sensor implant were available for off-line manual analysis jointly performed by two experts. Patients were classified into subgroups according to current PH definitions. Isolated post-capillary PH (IpcPH) and combined post- and pre-capillary PH (CpcPH) were present in 38 and 36 patients, respectively, whereas 31 patients had no PH. Clinical characteristics were comparable between subgroups, but among patients with PH pulmonary vascular resistance was higher (p = 0.029) and pulmonary artery compliance lower (p = 0.003) in patients with CpcPH. During 12 months of PAP-guided RPM, all PAPs declined in IpcPH and CpcPH subgroups (all p < 0.05), whereas only mean and diastolic PAP decreased in patients without PH (both p < 0.05). Improvements in post- versus pre-implant HFH rates were similar in CpcPH (0.639 events/patient-year; hazard ratio [HR] 0.37) and IpcPH (0.72 events/patient-year; HR 0.45) patients. Participants without PH benefited most (0.26 events/patient-year; HR 0.17, p = 0.04 vs. IpcPH/CpcPH patients). Quality of life and NYHA class improved significantly in all subgroups.

CONCLUSIONS

Outpatients with NYHA class III symptoms with at least one HFH during 1 year pre-implant benefitted significantly from PAP-guided RPM during post-implant follow-up irrespective of presence or subtype of PH at baseline.

The evolving landscape of pulmonary arterial hypertension clinical trials

Although it is a rare disease, the number of available therapeutic options for treating pulmonary arterial hypertension has increased since the late 1990s, with multiple drugs developed that are shown to be effective in phase 3 randomised controlled trials. Despite considerable advancements in pulmonary arterial hypertension treatment, prognosis remains poor. Existing therapies target pulmonary endothelial dysfunction with vasodilation and anti-proliferative effects. Novel therapies that target proliferative vascular remodelling and affect important outcomes are urgently needed. There is need for additional innovations in clinical trial design so that all emerging candidate therapies can be rigorously studied. Pulmonary arterial hypertension trial design has shifted from short-term submaximal exercise capacity as a primary endpoint, to larger clinical event-driven trial outcomes. Event-driven pulmonary arterial hypertension trials could face feasibility and efficiency issues in the future because increasing sample sizes and longer follow-up durations are needed, which would be problematic in such a rare disease. Enrichment strategies, innovative and alternative trial designs, and novel trial endpoints are potential solutions that could improve the efficiency of future pulmonary arterial hypertension trials while maintaining robustness and clinically meaningful evidence.

Performance of a HeartLogicTM Based Care Path in the Management of a Real-World Chronic Heart Failure Population

Aim

Early detection of impending fluid retention and timely adjustment of (medical) therapy can prevent heart failure related hospitalizations. The multisensory cardiac implantable electronic device (CIED) based algorithm HeartLogicTM aims to alert in case of impending fluid retention. The aim of the current analysis is to evaluate the performance of the HeartLogicTM guided heart failure care path in a real-world heart failure population and to investigate whether the height of the index and the duration of the alert state are indicative of the degree of fluid retention.

Methods

Consecutive adult heart failure patients with a CIED and an activated HeartLogicTM algorithm were eligible for inclusion. Patients were followed up according to the hospital's heart failure care path. The device technician reviewed alerts for a technical CIED checkup. Afterwards, the heart failure nurse contacted the patient to identify impending fluid retention. An alert was either true positive or false positive. Without an alert a patient was true negative or false negative.

Results

Among 107 patients, [82 male, 70 (IQR 60–77) years, left ventricular ejection fraction 37 ± 11%] 130 HeartLogicTM alerts were available for analysis. Median follow up was 14 months [IQR 8–23]. The sensitivity to detect impending fluid retention was 79%, the specificity 88%. The positive predictive was value 71% and the negative predictive value 91%. The unexplained alert rate was 0.23 alerts/patient year and the false negative rate 0.17 alerts/patient year. True positive alerts [42 days (IQR 28–63)] lasted longer than false positive alerts [28 days (IQR 21–44)], p = 0.02. The maximal HeartLogicTM index was higher in true positive alerts [26 (IQR 21–34)] compared to false positive alerts [19 (IQR 17–24)], p &lt; 0.01. Patients with higher HeartLogicTM indexes required more intense treatment (index height in outpatient setting 25 [IQR 20–32], day clinic treatment 28 [IQR 24–36] and hospitalized patients 45 [IQR 35–58], respectively), p &lt; 0.01.

Conclusion

The CIED-based HeartLogicTM algorithm facilitates early detection of impending fluid retention and thereby enables clinical action to prevent this at early stage. The current analysis illustrates that higher and persistent alerts are indicative for true positive alerts and higher index values are indicative for more severe fluid retention.

Heart failure decompensation alerts in a patient's home using an automated, AI-driven, point-of-care device

Heart failure (HF) is a major challenge worldwide and needs continuous monitoring of patients even after hospital discharge. This case report summarises the data collected and experience gained from the first usage of an automated, point-of-care device (Heartfelt device) in a patient’s home in the UK. The device monitors the onset of peripheral oedema and alerts clinicians if an increase in volume outside an expected normal range for the patient is detected. This may provide a reliable method of remotely and automatically monitoring HF patients in the home for those who do not reliably use weighing scales. The device successfully provided data for about 15 months and generated alerts in advance, which supported decisions for the patient’s care. The rate of data acquisition was very high and consistent throughout this period. The patient was satisfied with the device and agreed that it helped in her decision to seek medical attention.

Reduction of Hospitalization and Mortality by Echocardiography-Guided Treatment in Advanced Heart Failure

In advanced heart failure (AHF) clinical evaluation fails to detect subclinical HF deterioration in outpatient settings. The aim of the study was to determine whether the strategy of intensive outpatient echocardiographic monitoring, followed by treatment modification, reduces mortality and re-hospitalizations at 12 months. Methods: 214 patients with ejection fraction < 30% and >1 hospitalization during the last year underwent clinical evaluation and echocardiography at discharge and were divided into intensive (IMG; N = 143) or standard monitoring group (SMG; N = 71). In IMG, volemic status and left ventricular filling pressure were assessed 14, 30, 90, 180 and 365 days after discharge. HF treatment, particularly diuretic therapy, was temporarily intensified when HF deterioration signs and E/e’ > 15 were detected. In SMG, standard outpatient monitoring without obligatory echocardiography at outpatient visits was performed. Results: We observed lower hospitalization (absolute risk reduction [ARR]-0.343, CI-95%: 0.287−0.434, p < 0.05; number needed to treat [NNT]-2.91) and mortality (ARR-0.159, CI 95%: 0.127−0.224, p < 0.05; NNT-6.29) in IMG at 12 months. One-year survival was 88.8% in IMG and 71.8% in SMG (p < 0.05). Conclusion: In AHF, outpatient monitoring of volemic status and intracardiac filling pressures to individualize treatment may potentially reduce hospitalizations and mortality at 12 months follow-up. Echocardiography-guided outpatient therapy is feasible and clinically beneficial, providing evidence for the larger application of this approach.

Estimation of Changes in Intracardiac Hemodynamics Using Wearable Seismocardiography and Machine Learning in Patients with Heart Failure: A Feasibility Study

OBJECTIVE

Tracking changes in hemodynamic congestion and the consequent proactive readjustment of treatment has shown efficacy in reducing hospitalizations for patients with heart failure (HF). However, the cost-prohibitive nature of these invasive sensing systems precludes their usage in the large patient population affected by HF. The objective of this research is to estimate the changes in pulmonary artery mean pressure (PAM) and pulmonary capillary wedge pressure (PCWP) following vasodilator infusion during right heart catheterization (RHC), using changes in simultaneously recorded wearable seismocardiogram (SCG) signals captured with a small wearable patch.

METHODS

A total of 20 patients with HF (20% women, median age 55 (interquartile range (IQR), 44-64) years, ejection fraction 24 (IQR, 16-43)) were fitted with a wearable sensing patch and underwent RHC with vasodilator challenge. We divided the dataset randomly into a trainingtesting set (n=15) and a separate validation set (n=5). We developed globalized (population) regression models to estimate changes in PAM and PCWP from the changes in simultaneously recorded SCG.

RESULTS

The regression model estimated both pressures with good accuracies: root-mean-square-error (RMSE) of 2.5 mmHg and R2 of 0.83 for estimating changes in PAM, and RMSE of 1.9 mmHg and R2 of 0.93 for estimating changes in PCWP for the training-testing set, and RMSE of 2.7 mmHg and R2 of 0.81 for estimating changes in PAM, and RMSE of 2.9 mmHg and R2 of 0.95 for estimating changes in PCWP for the validation set respectively.

CONCLUSION

Changes in wearable SCG signals may be used to track acute changes in intracardiac hemodynamics in patients with HF.

SIGNIFICANCE

This method holds promise in tracking longitudinal changes in hemodynamic congestion in hemodynamically-guided remote home monitoring and treatment for patients with HF.