Review Article

Device-based Strategies for Monitoring Congestion and Guideline-directed Therapy in Heart Failure: The Who, When and How of Personalised Care

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Abstract

Despite therapeutic and technological advances, the prognosis for patients with heart failure (HF) remains poor. One reason for this poor prognosis lies in the limited usage of disease-modifying therapies, such as β-blockers, renin–angiotensin system inhibitors, mineralocorticoid receptor antagonists and sodium–glucose cotransporter 2 inhibitors, namely guideline-directed medical therapy (GDMT). Concurrently, technological advances have led to the development of numerous strategies for both invasive and non-invasive telemonitoring of HF patients, potentially intercepting a phase of decompensation before its overt clinical manifestation. As clinical guidelines and the healthcare landscape continue to evolve, HF management is increasingly focusing on integrating advanced technologies and empowering patients and care teams. Traditionally, diuretics have been the cornerstone of preventing HF decompensation because of their decongestive effects. However, emerging evidence suggests that the components of GDMT also exert decongestive effects, alongside their broader positive prognostic impact. The synergistic relationship between GDMT and telemonitoring devices offers a promising approach to congestion management. By adopting protocols that leverage both the pharmacological and non-pharmacological mechanisms of GDMT, care teams can maximise patient outcomes while addressing therapeutic inertia. This narrative review explores the potential for a paradigm shift, emphasising the early and consistent implementation of GDMT, supported by digital health solutions, to improve outcomes from the early stages of HF decompensation.

Keywords

Guideline-directed medical therapy, heart failure, review, telemonitoring, therapeutic inertia,

Received:

Accepted:

Published online:

DOI: https://doi.org/10.15420/cfr.2025.01

Disclosure: MV is on the Cardiac Failure Review editorial board; this did not influence peer review. All other authors have no conflicts of interest to declare.

Funding: This work was supported by funding from the Italian Ministry of Health (Ricerca Corrente) and grant (GR-2021-12375403).

Correspondence: Domenico D’Amario, Department of Translational Medicine, Università del Piemonte Orientale, Corso Mazzini n.18 – 28100 Novara, Italy. E: domenico.damario@uniupo.it.

Copyright:

© The Author(s). This work is open access and is licensed under CC-BY-NC 4.0. Users may copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly.

Heart failure (HF) may be considered a global pandemic, with 2–3% of individuals affected worldwide.1 Its prevalence is increasing due to the ageing of the population and improved survival from ischaemic and valvular heart diseases.1 As a result, the management of HF patients is becoming more challenging because of the increase in concomitant comorbidities and the expansion of available disease-modifying therapies.1 Nevertheless, despite treatment advances, morbidity and mortality still remain high.2

One reason may arise from the limited implementation of guideline-directed medical therapy (GDMT) in daily clinical practice, a phenomenon known as therapeutic inertia.3,4 The STRONG-HF trial showed that a rapid implementation of GDMT early after a decompensation event is safe, although the study protocol involved a high number of follow-up visits in the first few weeks after discharge in the experimental group, hampering its feasibility in daily clinical practice.5 Traditionally, remote monitoring strategies have been developed with the aim of identifying and managing congestion at an early pre-symptomatic stage by modifying medical therapies, mainly loop diuretics.6 Nevertheless, there is growing evidence for the decongestant effect of GDMT.7 Therefore, remote monitoring, supported by rapidly evolving digital technology, could be leveraged to promote the implementation of GDMT in daily clinical practice.

The aims of this narrative review are to assess the evidence for the effectiveness of all remote monitoring strategies (both invasive and non-invasive), to evaluate the evidence for the decongestant effect of GDMT and to explore the reasons for therapeutic inertia and how they could be eventually overcome by remote monitoring strategies empowered by the use of digital technologies.

Central Illustration: Heart Failure Management

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Decongestant Effect of GDMT

In patients hospitalised for a decompensation event, the cornerstone of treatment for acute HF with fluid overload is intravenous loop diuretics.8 These mainly reduce the signs and symptoms of congestion, but their effect on long-term prognosis seems unfavourable.9 Conversely, the prognostic benefit of GDMT, already starting in the first few months after implementation, is well established across left ventricular ejection fraction subtypes.10,11

Accumulating data seem to favour a minimalist strategy for loop diuretics, in terms of both their dosage and their duration of administration. The DOSE trial, which enrolled 308 patients with acute HF, showed that a low-dose strategy (IV dose equal to the total daily dose) was as effective as the high-dose regimen (IV dose 2.5 times higher than the total daily oral dose) in relieving symptoms, but was safer, as evidenced by a lower rate of renal deterioration.12 Furthermore, the ReBIC-1 trial, involving 188 HF patients, shed light on the duration of loop diuretic therapy and showed the safety of their withdrawal, once euvolemia had been achieved.13

Two recent randomised controlled trials (RCTs), CLOROTIC and ADVOR, have further confirmed that an intensified decongestion strategy using combined diuretic therapy (loop diuretics plus hydrochlorothiazide or acetazolamide, respectively) in patients with acute HF yields only a modest impact on symptoms and does not translate into improved clinical outcomes.14,15 Notably, loop diuretics are not the sole medications with decongestant properties.7,8 Fluid accumulation is the common final pathway of a self-sustaining process involving various mediators, such as sympathetic and renin–angiotensin–aldosterone systems, which increase sodium avidity and make HF patients prone to sodium and fluid accumulation.16 Therefore, acting on other pathways, such as the sympathetic and the renin–angiotensin–aldosterone systems, which can be modulated by components of GDMT, could represent an alternative or complementary strategy to alleviate congestion and fluid overload, and to maintain a state of volemic compensation. In the STRONG-HF trial, early initiation and up-titration of GDMT led to faster resolution of congestion, despite lower doses of diuretics administered compared with the control arm.5 The diuretic and decongestant effects of GDMT was specifically evaluated for each component.

Angiotensin receptor–neprilysin inhibitors (ARNIs) have been reported in several studies.17–19 In two sub-analyses of the PARADIGM-HF and Paragon-HF studies, patients treated with ARNI exhibited a greater reduction in the dose of loop diuretic, as well as a greater improvement in congestive status compared with the group receiving enalapril.17–19 A study by Mebazaa et al., which enrolled 229 stable patients with reduced ejection fraction, showed also that ARNI improved the ability of HF patients to handle an external fluid overload by increasing diuresis and natriuresis.20 Interestingly, less dyspnoea and fewer clinical signs of congestion during fluid challenge were also observed after ARNI initiation.20

Of note, a recent real-world analysis from the Generator HF Datamart revealed the feasibility and prognostic significance of early implementation of angiotensin-converting enzyme inhibitor (ACEi)/angiotensin II receptor blocker (ARB)/ARNI therapy in patients with acute HF.21 A diuretic role for mineralocorticoid receptor antagonists (MRAs) also emerged, as well as the safety of early use in patients with acute HF.22,23 A recent post hoc analysis of the PROACTIVE-HF trial further confirmed the haemodynamic effects of ARNI and MRA on seated pulmonary arterial pressure (PAP).24

Finally, sodium–glucose cotransporter 2 inhibitors (SGLT2Is) have also been demonstrated to exert a diuretic effect, particularly in patients with acute HF.7,25 Two RCTs evaluated diuretic response to SGLT2Is in patients with acutely decompensated HF, showing that it produced an immediate and persistent increase in urinary volume due to glycosuria.26,27 However, their use was not accompanied by significant changes in urinary sodium excretion due to the activation of distal counterregulatory sodium re-absorptive mechanisms.28 This potentially results in a greater electrolyte-free water clearance compared with the effect of loop diuretics and, consequently, in a greater fluid clearance from the interstitial fluid space than from the circulation, ultimately leading to a relief of congestion with minimal impact on blood volume, arterial filling and organ perfusion.29,30 The decongestant effect of SGLT2Is was further confirmed in the EMBRACE-HF trial, which demonstrated early (within the first week) and persistent PAP reduction measured by CardioMEMS (Abbott) after SGLT2I initiation.31

In addition, the increased sodium delivery to the macula densa may result in a relative suppression of the renin–angiotensin–aldosterone system, which is responsible for sodium avidity and, thus, the tendency to congestion in HF patients. Consequently, SGLT2Is could be regarded as a modulator of the volume set point, restoring it to levels observed in healthy individuals.32 Finally, evidence is accumulating for the role of SGLT2Is in reducing resistance to loop diuretics, probably through its action in increasing distal chloride delivery, thereby sensitising the Na+, K+, 2Cl− cotransporter to pharmacological inhibition by loop diuretics.33,34 Of note, a real-world analysis revealed that the vast majority of patients with HF, upon discharge following a decompensated event, are eligible to receive MRAs or SGLT2Is (90% and 79% of patients, respectively), based on the absence of both contraindications or cautions.21

Overall, the indiscriminate and extensive use of loop diuretics can lead to sympathetic hyperactivation, hypotension, renal dysfunction and electrolyte abnormalities, which may contribute to diuretic resistance, suboptimal titration of GDMT and – ultimately – worse clinical outcomes.34,35 Recently, two observational studies from real-world registries confirmed an association between diuretic use and adverse events, regardless of ejection fraction.21,36 Accordingly, the implementation of GDMT should serve as the primary approach to alleviate congestion and maintain euvolemia, with loop diuretics administered at the lowest effective dose and for the shortest necessary duration. Furthermore, GDMT may contribute to the restoration of physiological adaptation mechanisms intended to prevent a decompensation event in healthy subjects by increasing the capacity of the cardiorenal system to accommodate volume and sodium stressors Figure 1).37

Figure 1: Guideline-directed Medical Therapy-centred Personalised Therapy in Heart Failure

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Invasive Pressure Monitoring Devices

The assumption underpinning the benefit of invasive pressure monitoring devices is that the elevation of left ventricular pressures often precedes clinical decompensation, allowing clinicians to detect early signs of congestion and thus to intervene at a pre-symptomatic stage, potentially preventing HF hospitalisation with therapy modifications.6 CardioMEMS is the only currently approved invasive implantable haemodynamic monitoring system. The 2021 European HF guidelines weakly recommend its use to improve clinical outcomes in HF patients (class 2b, level of evidence b).9 Conversely, American HF guidelines restrict its use, albeit with a similar weak recommendation, in a specific subgroup of HF patients (those with a HF hospitalisation in the previous year or those with elevated natriuretic peptide levels on maximally tolerated stable doses of GDMT).38 A promising line of research is the use of lung echo for non-invasive haemodynamic monitoring of HF patients, but adequately powered RCTs are needed to assess its benefit on prognosis.39

Pulmonary Arterial Pressure Monitoring Devices

To date, two devices that directly and invasively measure PAP have been evaluated in trials: CardioMEMS and Cordella (Endotronix; Figure 2).

Figure 2: Invasive Pressure Monitoring Devices and Clinical Trials Assessing Their Safety and Efficacy

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CardioMEMS

CardioMEMS measures PAP using microelectromechanical (MEMS) technology through a sensor permanently implanted in a distal branch of the pulmonary artery via a right heart catheterisation.40 The efficacy and safety of this device were evaluated in three RCTs (CHAMPION, GUIDE-HF and MONITOR-HF) and, subsequently, in a meta-analysis, which included 1,898 patients with chronic HF and showed a clear benefit of this monitoring system in reducing total HF hospitalisations by almost one-third, regardless of ejection fraction.41–44 One of the primary limitations of this pooled analysis, apart from the absence of a placebo group, was the heterogeneity in background disease-modifying medical therapies across the included RCTs, largely attributable to the varying time periods in which they were conducted. The CHAMPION trial pre-dated the use of ARNIs and SGLT2Is, while both the GUIDE-HF and MONITOR-HF trials preceded the adoption of SGLT2Is in real-world clinical practice, leading to low adoption of current GDMT Table 1). As a result, these findings are not directly applicable to current clinical practice. Conversely, the most used and titrated drugs in all the above three RCTs were diuretics, although their efficacy in improving clinical outcomes in HF patients remains controversial.44

Table 1: Haemodynamic-guided Management

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A post hoc analysis of the CHAMPION trial showed that the most common therapeutic changes were related to diuretics (60.4% of the overall changes), mainly in the interventional group compared with the control group (62.6% versus 55.1%, respectively).45 Conversely, therapeutic changes in β-blockers, ACEi/ARBs and MRAs constituted only a small amount of overall medical changes (12.4%, 11.3%, 4.7%, respectively). Similarly, the most frequent medication changes in the GUIDE-HF trial were diuretics, which occurred in 83.3% of subjects in the treatment group versus 59.2% in the control group.46

A single-arm post-approval study of CardioMEMS, involving 1,800 patients in the US between 2014 and 2017, confirmed the tendency of acting mainly on diuretics in cases of changes in filling pressures.47 A partial reversal of this trend occurred in the MONITOR-HF trial.43 Although diuretics remained the most prescribed drug, an increase in the administration of other disease-modifying drugs was observed at 12 months after enrolment.43 Of note, in the first 6 months after enrolment, most therapeutic changes in the CardioMEMS-implanted group involved GDMT, rather than diuretics.43

MONITOR-HF showed the greatest effect of treatment on PAP compared with the other two RCTs, further confirming the decongestant effect of GDMT.44 A real-world study highlighted the potential of CardioMEMS in optimising levosimendan therapy and enhancing its efficacy, ultimately reducing the risk of future HF hospitalisations and mitigating healthcare costs.48 Therefore, the shared approach of adjusting diuretics instead of up-titrating other disease-modifying drugs (i.e., ACEi/ARB/ARNIs, MRAs, SGLT2Is) in the above-mentioned RCTs may have hindered the overall effectiveness of CardioMEMS-guided therapy. A meta-analysis of individual patient data, correlating specific therapeutic modifications with clinical events, may confirm this hypothesis.

Cordella

Cordella is a device similar in function (i.e., a wireless MEMS sensor) and implantation technique to CardioMEMS Figure 2).40 In contrast with CardioMEMS, Cordella enables a multi-parameter assessment, consisting not only of PAP measurement but also of daily health information (body weight, blood pressure, saturations and heart rate). To date, no RCT data have been published with this device. The PROACTIVE-HF 2 trial will be the first RCT to provide data on the safety and efficacy of Cordella compared with an active control group. However, three single-arm studies (i.e., SIRONA, SIRONA 2 and PROACTIVE-HF) showed that Cordella significantly reduced PAP in patients with high PAP baseline levels, with an excellent safety profile and a low number of HF hospitalisations and all-cause mortality at follow-up Figure 2).49–51

As in RCTs evaluating CardioMEMS, diuretics were the most used drug and those for which the most therapeutic changes were performed Table 1). Similarly, a real-world analysis of Cordella usage demonstrated a tendency to prioritise adjustments in diuretic therapy over modifications to components of GDMT.52 The implementation of GDMT before increasing diuretic dosage in the setting of elevated PAP should be considered in the management guidelines of future RCTs to maximise the benefit of a haemodynamic-guided therapy.

Right Ventricle Pressure Monitoring Devices

Chronicle

The Chronicle device (Medtronic) consists of a lead-mounted pressure sensor placed in the outflow tract of the right ventricle and connected to a box implanted subcutaneously in the pectoral area Figure 2).40 It measures the systolic and diastolic pressures of the right ventricle, indirectly estimating the diastolic pressure of the pulmonary artery.40 The efficacy and safety of this device were evaluated in the COMPASS-HF trial, which involved 274 patients with chronic HF, and showed no benefit in reducing HF hospitalisations compared with the control group Figure 2; Table 1).53 This trial predated the use of SGLT2Is and ARNIs, and most therapeutic variations in both groups affected the dose of diuretics.53 A further development of the Chronicle is the Chronicle-ICD, in which the pressure sensor is located close to the ICD.40 It was tested in the REDUCEhf trial, which was stopped early at 400 patients due to a high rate of device malfunctions and failed to demonstrate a benefit in reducing HF hospitalisations Figure 2 and Table 1).54 No data were provided on which types of medication were changed during the trial. Overall, the results of these trials did not allow Chronicle to be launched on the market.

Left Atrial Pressure Monitoring Devices

In some clinical contexts (acute HF, non-cardiac pulmonary hypertension and advanced chronic HF), PAP may not adequately correlate with left-sided pressures, resulting in an inaccurate estimation of left-sided filling pressure.55 To overcome this limitation, left atrial pressure (LAP) measuring devices have been developed.

HeartPOD

The HeartPOD (Abbott) left atrial sensing device consists of an implantable sensor coupled with a subcutaneous antenna coil Figure 2).56 It was evaluated in a prospective, observational, open-label, single-arm registry (i.e., HOMEOSTASIS), which enrolled 40 subjects with HF, prior to the availability of ARNIs and SGLT2Is Table 1).57 At baseline all enrolled patients were receiving loop diuretics. During the study, there was a reduction in their prescription and dosage, with an increase in the prescription and dosage of ACEi/ARBs and β-blockers, ultimately leading to a reduction in the incidence of HF decompensation events and LAP mean values, and in an improvement of New York Heart Association class.57 Interestingly, patients with adverse clinical events took 40% fewer ACE/ARBs, 43% fewer β-blockers and 94% more loop diuretics than patients without events.57 Overall, these results further demonstrated the diuretic-like effect of GDMT, which was also associated with an improvement in symptoms and prognosis.

HeartPOD was then tested in LAPTOP-HF, a randomised, prospective, controlled clinical trial Figure 2; Table 1).58 Although it was stopped early due to a perceived excess of procedural complications, this device was found to be safe and reduced the rate of HF hospitalisation at 12 months.58 Data about the use of diuretics and GDMT were not provided.

V-LAP

V-LAP (Vectorious Medical Technologies) is a leadless implantable LAP sensor, opened on both sides of the interatrial septum and remotely powered by the external reader Figure 2).59 Its safety and usability have been evaluated in VECTOR-HF, a prospective, single-arm, clinical trial enrolling 30 patients with HF.60 The monitoring system was found to be safe, with no acute complications during implantation, and was shown to reduce symptoms and improve exercise capacity in enrolled patients.60 The most prescribed drugs were diuretics, the dosage of which increased over the course of the study. Conversely, only a slight increase in the prescription of SGLT2Is and ARNIs occurred, while the percentage of MRA prescriptions even decreased Table 1).60 No correlation has been established between changes in treatment and clinical or congestion outcomes.

The outbreak of the COVID-19 pandemic underscored the true potential of this surveillance system, with a remarkable compliance rate (>99%) to the trial protocol.61 Furthermore, this system has also proven to be an invaluable asset in facilitating the management of patients during HF hospitalisation. Specifically, in a recent pioneering case report, the V-LAP system proved to be a useful tool capable of capturing haemodynamic status earlier and more reliably than standard haemodynamic parameters, such as central venous pressure, ultimately guiding a safely weaning from inotropes and ventilatory support.62 Further research involving a larger patient cohort is required to validate this finding.62,63 Finally, an innovative invasive device currently in development, the FIRE1, is positioned in the inferior vena cava, with its safety and feasibility being assessed in the FUTURE-HF trial.64

ICD and CRT Devices

ICD and CRT devices are recommended in patients with HF with reduced ejection fraction (HFrEF), without and with certain conduction disturbances, respectively, to improve their prognosis and quality of life on top of maximum tolerable GDMT.9 Of note, the risk of sudden cardiac death in HF patients has changed over time with the sequential introduction of medications including ACEi/ARB/ARNIs, β-blockers, MRAs and SGLT2Is.65 As this recommendation is based on pivotal RCTs conducted between 1996 and 2016 when standard medical therapy included only a combination of ACEis, β-blockers and MRAs, their efficacy should be re-assessed in new trials with a comparison arm that also receives ARNIs and SGLT2Is.65 However, emerging data from observational studies show that ICD/CRT shows an additional prognostic benefit even in patients who receive the four pillars.66,67

To date, although guidelines recommend the use of such devices on top of optimised medical therapy, real-world data reported suboptimal use of GDMT in HFrEF patients undergoing ICD/CRT implantation.66,68,69 Therefore, ICD/CRT therapy could be considered not as the final common pathway in the care process of these patients, but as another tool leading to the implementation of GDMT.70 The findings supporting ICD/CRT as enablers for optimising GDMT are various.

First, modern ICD/CRT devices are empowered with sensors allowing automatic daily remote monitoring of multiple parameters.71–76 These include factors of autonomic adaptation (iheart rate variability, the onset of arrhythmias, the rate of biventricular pacing), patient activity and intrathoracic impedance. The alteration of all these parameters typically follows the increase in cardiac filling pressure, potentially intercepting a decompensation event before its overt clinical manifestation.71 In a recent meta-analysis of six RCTs with a total of 4,869 patients, invasive multiparametric monitoring by ICD/CRT was shown to reduce both all-cause mortality and HF hospitalisation compared with standard of care.71 However, this evidence derives from studies conducted between 2013 and 2020. Even in the most recent studies, the use of GDMT was suboptimal, with no patients receiving ARNIs and SGLT2Is, while diuretic therapy constituted the most common treatment in most of them Table 2). It is reasonable to assume that the preferential implementation of GDMT – which also exerts a decongestant effect – instead of diuretics, guided by multiparametric ICD/CRT monitoring, could represent an additional weapon to reduce therapeutic inertia and provide an even greater prognostic benefit in this subset of patients.

Table 2: Cardiac Implantable Electronic Device-based Multiparameter-guided Management

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Second, the acute and chronic haemodynamic effects of CRT might significantly change tolerability and acceptance of medical therapy.77–79 In the CARE-HF and COMPANION trials, CRT was associated with a 6–7mmHg increase in systolic blood pressure.80,81 Furthermore, CRT protects patients from bradyarrhythmias, allowing safer uptitration of β-blockers.82 Real-world data show that CRT implantation allows further safe uptitration in ACEi/ARB and β-blockers doses, as well as a concomitant reduction in diuretic dose requirements with an overall prognostic benefit.83,84

Third, the decision to implant an ICD or CRT often occurs within the context of specialised HF or electrophysiology clinics, involving extensive patient education, which can improve adherence to both device-related care and prescribed medications.70 Further data from real-world registries and RCTs are needed to re-evaluate the indication for ICD/CRT implantation in the context of new drug therapies and the individual patient profile.85

Non-invasive Wearable Devices

According to 2021 European Society of Cardiology HF guidelines, non-invasive home telemonitoring may be considered to reduce the risk of recurrent HF hospitalisations and cardiovascular death (class 2b, level of evidence b).9 Modern wearable devices, including smartwatches, bands, patches, rings, medical earbuds and clothing-embedded devices, can remotely control physiological parameters, such as heart rate, heart rate variability, respiratory frequency, arterial oxygen saturation, thoracic fluid content, blood pressure, sleep and temperature.86 Among the 10 studies evaluating the impact of non-invasive remote monitoring on the optimisation of GDMT, nine (i.e., 90%) showed a positive result Table 3).87,88 Therefore, non-invasive remote monitoring could be considered as one of the strategies to implement GDMT and overcome therapeutic inertia.

Table 3: Non-invasive Multiparameter-guided Management

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In contrast, the impact of non-invasive remote monitoring on hard clinical endpoints is more controversial. A recent meta-analysis of 65 studies and 21,457 patients showed a reduction in all-cause mortality and HF hospitalisation with non-invasive telemonitoring compared with standard of care.89 Interestingly, the TEMA-HF trial, which was one of the few included trials to show a reduction in all-cause mortality per se, reported a significant implementation of ACEi/ARBs and β-blockers in the experimental group compared with the control group, with minimal change in diuretic therapy.90 Similarly, the TIM-HF2 trial, which also showed a reduction in all-cause mortality in the telemonitoring group, reported 3,546 therapeutic changes (presumably GDMT) in the experimental group.91 This supports the hypothesis that prioritising the implementation of GDMT over loop diuretics may maximise the benefits derived from early detection of subclinical decompensation.

Furthermore, a nationwide real-world study including 35,275 HF patients demonstrated the prognostic benefits of a non-invasive monitoring system based on symptom and weight fluctuation assessments in reducing mortality and hospitalisations due to HF. However, the limited usage of certain GDMT components (i.e., MRA, SGLT2I) and the lack of correlation analyses between clinical events and GDMT modifications preclude a clear delineation of the underlying mechanism driving this association.92 Actually, one of the main limitations of non-invasive remote monitoring studies may lie in their reliance on diuretic-centred action protocols. Future RCTs with GDMT-based treatment protocols are needed to confirm this hypothesis. Finally, numerous non-invasive strategies for detecting haemodynamic congestion are currently under development, such as patch-based devices for monitoring tissue fluid, smartphone-based speech analysis and digital immunoassay for N-terminal pro B-type natriuretic peptide measurement.93,94

Therapeutic Inertia

Despite the broadening of the therapeutic armamentarium for HF patients, its implementation in daily clinical practice is still poor.4 Several large national and multinational registries have shown an under-prescription of GDMT, both in terms of use and sub-optimal dosing.4 This concerns both outpatients and patients discharged after a decompensation event. Two contemporary registries have shown that the under-prescription of GDMT after an episode of decompensation is more prominent for newer drugs (iSGLT2Is and MRAs), highlighting that the sequential implementation paradigm rather than the simultaneous one is still embedded in daily clinical practice.3,21,95 This issue was further confirmed by a recent international survey of 423 cardiologists, in which only 25% of HFrEF patients received simultaneous implementation of all four pillars together.96 The process of prescribing and adhering to GDMT involves three main actors: the patient, the prescribing physician and the patient’s supportive team (i.e., caregiver, nurse and pharmacist). Acting on each of these can be a lever for optimising GDMT.

Patients

According to a recent international survey, the most common patient-related barriers to GDMT implementation, in descending order of frequency, were hypotension (selected by 70% of survey respondents), creatinine increase (47%), hyperkalaemia (45%), patient adherence (42%), mild but symptomatic hypotension (33%) and bradycardia (19%).96 Each of these issues could be addressed by both invasive and non-invasive remote monitoring strategies. Regarding hypotension, invasive devices – measuring left ventricular filling pressure or its surrogates – provide an indirect measure of arterial blood pressure and, thus, the risk of hypotension and hypovolaemia.97 Furthermore, CRT has been shown to increase cardiac output, mitigating the risk of hypotension.84 In addition, arterial blood pressure is one of the most frequently measured parameters by non-invasive devices, and its daily monitoring may reduce the fear of hypotension or its actual occurrence.98

Well-structured biochemical surveillance regarding creatinine clearance and hyperkalaemia could be sent regularly via mobile app, electronic health records and other non-invasive monitoring systems. One such system, the CardioRenal remote monitoring solution, combines an innovative microfluidic technology for home monitoring of haemoglobin, potassium and creatinine concentrations with a remote monitoring for data transfer, as well as an innovative expert algorithmic decision support system to provide personalised therapeutic advice to the physician.99 Its efficacy in improving the prognosis of HFrEF patients will be tested in the CARE-MOST HF trial. Furthermore, a system for measuring creatinine using a photochemical point-of-care biosensor connected to a smartphone has also been developed.100 Similarly, some algorithms have been created to indirectly extrapolate potassium levels by automatically analysing a single-lead ECG recorded via a smartwatch.101,102 Its validation and applicability in HF patients to aid the implementation of GDMT could be evaluated in subsequent studies.

Patient adherence is one of the most suitable aspects to be addressed by non-invasive devices and digital support systems. The EPIC-HF trial, which enrolled 306 patients with stable HFrEF, specifically evaluated the use of digital support tools to improve patient education and revealed that a 3-minute patient activation video plus a one-page medication checklist significantly improved GDMT prescription, especially in terms of dose intensification.103 The tools encouraged patients to collaborate with their clinicians to “make one positive change” in their medication regimen. These could be integrated into a multi-parameter remote monitoring system and tested in further RCTs.

Mobile apps of various types have been extensively studied to support patients with HF, with mixed results in terms of GDMT optimisation and patient education improvement, mainly because of differences in application design, patient selection and drop-out rates.104 Furthermore, certain socio-demographic features predispose patients to GDMT underuse, which could be addressed through tailored remote monitoring strategies.105 Specifically, HF patients from rural areas or with a lower socio-economic status receive less GDMT, exhibit higher rates of medication non-adherence and have a worse prognosis than those from urban areas or with a higher socio-economic level.106 Several reports have shown that digital interventions could play a promising role in improving self-care and knowledge and reducing cardiovascular mortality in patients with HF living in underserved rural areas or from ethnic minority groups.107 Further studies, especially with a randomised design and focused on clinical outcomes, are needed to corroborate these findings.

Physicians

Another target for tackling therapeutic inertia is the physicians themselves.4 There are numerous factors contributing to therapeutic inertia related to healthcare providers. First, HF management is a rapidly evolving field, and the failure to remain up to date may contribute to suboptimal treatment. Other physician-related factors associated with therapeutic inertia include high patient volumes, underestimation of disease severity and time constraints in daily clinical practice.108 The impact of educating clinicians, through a trained HF group of experts and feedback audits, on GDMT implementation has been evaluated in five RCTs with mixed results, mostly inconclusive.109 In contrast, the use of electronic health records-based alerts has been tested in six RCTs with encouraging results in terms of GDMT optimisation, both in inpatient and outpatient settings.109 They provided clinicians with automated medication suggestions based on vital signs, laboratory tests, comorbidities and ejection fraction.109 Their efficacy on hard clinical endpoints should be evaluated in adequately powered RCTs.

Nurses, Caregivers and Pharmacists

HF patients are often elderly and multimorbid, and other professionals, such as nurses or caregivers, are involved in their care, representing potential targets for GDMT implementation.87 Nurses have been involved in both experimental teleconsultation and telemonitoring strategies. A video consultation led by nurses has been shown to improve GDMT in the first 90 days after discharge in HF patients.110 In addition, nurses participated in two remote monitoring RCTs in which they were involved in reviewing vital signs data from wireless devices and laboratory tests. Overall, there was a significant increase in GDMT prescription in the interventional arm compared with the control group.111,112

Nurses have also been engaged in the new ‘Hospital at Home’ model of care.113 This is an emerging nurse-centred model in which patients with worsening HF receive inpatient-level care at home, including intravenous medication, meal delivery, laboratory draws, physiotherapy, occupational therapy, echocardiography and radiology services.113 To date, data on its safety and efficacy is limited and, mainly, out-of-date.114 Nevertheless, this system holds immense potential, particularly given its feasibility for implementation and integration through digital support and telemonitoring. The INTERCOACH trial will evaluate the feasibility and acceptability of a comprehensive approach combining nurse-led counselling with home-based self-monitoring of vital signs, following a HF decompensation event.115

Caregivers play an invaluable role in supporting people with HF through symptoms and medication management, self-care and decision-making, particularly during the transition from hospital to home.116 Some studies have investigated caregiver support strategies and have shown beneficial effects mainly on patient and caregiver quality of life.116 Conversely, there is a paucity of data on the use of digital technologies to assist caregivers in improving medication adherence. In a RCT involving 331 HF patients, a mobile health intervention for caregiver support was shown to improve medication adherence.117

Dedicated digital caregiver support algorithms, as part of a broader multidimensional programme, could represent a further weapon against therapeutic inertia. Moreover, the incorporation of a nurse or caregiver-like avatars into telemonitoring strategies may represent another promising advancement, particularly in assisting patients with low literacy or visual impairments.118 However, further studies are required to elucidate its role in HF telemedicine.

Pharmacists could play a crucial role in the implementation of HF therapy, because they often interact with the patient or his caregiver during the medication dispensing process. In a meta-analysis of RCTs, the active intervention of a physician-supervised pharmacist with prescribing privileges for GDMT led to a significant increase in medication adherence, as well as in the number and dosage of medications prescribed.119 This support strategy was further implemented using digital technologies and the creation of a virtual care team composed of a cardiologist and a pharmacist, which showed encouraging results in optimising GDMT.120 A recent prospective single-arm study involving 38 HF patients enhanced this concept by integrating the expertise of all stakeholders involved in the care process (i.e., physicians, pharmacists and nurses) and using a proactive remote telehealth system to monitor patients.121 Overall, it showed an increase in the number and dose of GDMTs prescribed, as well as a reduction in HF readmissions, compared with the pre-enrolment period.121

In conclusion, there is a significant unmet need in generating high-quality evidence regarding the use of non-invasive digital technologies in HF management. This gap is, at least in part, attributable to the heterogeneity of the devices, tools and services available, as well as the diversity of the target populations and service designs. Most importantly, current research paradigms, particularly RCTs, are poorly suited to address these complexities. In this context, challenges arise in masking sham or control groups, leading to inherent biases in both the interpretation and reporting of patient-reported experience measures and patient-reported outcome measures. These biases are difficult to mitigate, further complicating the evidence-generation process.

The Plan-Do-Study-Act (PDSA) cycle, a well-established improvement process in healthcare, offers an underutilised approach to pragmatic research. The PDSA framework, based on small iterative tests of change, can potentially address the limitations of traditional RCTs by embedding research within real-world care delivery settings. Unlike standard RCTs that emphasise internal validity through highly controlled environments and selected populations, pragmatic studies prioritise external validity and accommodate the unique needs of diverse clinical contexts. Additionally, designing trials that leverage emerging technologies such as the Internet of Things and artificial intelligence presents an opportunity to revolutionise clinical research.85 However, the structure of clinical trials has remained largely unchanged for over three decades, posing significant challenges in integrating these innovations. Data silos, poor patient engagement and low retention rates continue to hinder progress. As it stands, most clinical trials remain manually driven, with technology used in isolated, piecemeal solutions. A more holistic, integrated approach is urgently needed to keep pace with technological advancements and optimise patient outcomes in HF management.

Conclusion

The ageing population of HF patients, coupled with the increasing burden of comorbidities, is creating new complexities in managing the condition. The recent expansion of disease-modifying therapies further adds to these challenges. In this evolving landscape, the role of remote monitoring, both invasive and non-invasive, bolstered by advanced digital technologies, is gaining momentum. These tools have shown promise in detecting early signs of decompensation, potentially enabling earlier intervention and more personalised care. With the new ‘Medical Device Regulation’ legislation in the European Union supporting the integration of digital health solutions, there is a unique opportunity to shift care paradigms toward more effective GDMT, reducing reliance on diuretics and using them selectively. However, the true impact of this approach on clinical outcomes, particularly in terms of reducing hospitalisations and improving quality of life, needs to be confirmed by future RCTs. At the same time, the rise of empowered and engaged patients and care teams, supported by policies that educate and advocate for patient groups, is essential to ensure that these advancements are translated into meaningful, accessible care. This collective shift in policy, technology and patient involvement holds the potential to transform HF management into a more proactive, patient-centred model. Nevertheless, numerous challenges persist in the field of device research. First, digital solutions must carefully regulate the frequency of alerts to maintain effectiveness while preventing alert fatigue among clinicians, which could otherwise result in the oversight of critical notifications. Secondly, a well-structured design is essential to ensuring long-term engagement and adherence without placing excessive burden on patients. Furthermore, proper longitudinal data are needed to validate the sustained benefits over time, while also accounting for Hawthorne bias.122 Thirdly, the feasibility and clinical impact of pharmacological self-management guided by device-generated data require thorough investigation.

References

  1. Savarese G, Becher PM, Lund LH, et al. Global burden of heart failure: a comprehensive and updated review of epidemiology. Cardiovasc Res 2023;118:3272–87. 
    Crossref | PubMed
  2. Lindberg F, Benson L, Dahlström U, et al. Trends in heart failure mortality in Sweden between 1997 and 2022. Eur J Heart Fail 2025;27:366–76. 
    Crossref | PubMed
  3. D’Amario D, Rodolico D, Delvinioti A, et al. Eligibility for the 4 pharmacological pillars in heart failure with reduced ejection fraction at discharge. J Am Heart Assoc 2023;12:e029071. 
    Crossref | PubMed
  4. Savarese G, Lindberg F, Cannata A, et al. How to tackle therapeutic inertia in heart failure with reduced ejection fraction. A scientific statement of the Heart Failure Association of the ESC. Eur J Heart Fail 2024;26:1278–97. 
    Crossref | PubMed
  5. Mebazaa A, Davison B, Chioncel O, et al. Safety, tolerability and efficacy of up-titration of guideline-directed medical therapies for acute heart failure (STRONG-HF): a multinational, open-label, randomised, trial. Lancet 2022;400:1938–52. 
    Crossref | PubMed
  6. Stevenson LW, Ross HJ, Rathman LD, Boehmer JP. Remote monitoring for heart failure management at home. J Am Coll Cardiol 2023;81:2272–91. 
    Crossref | PubMed
  7. Laborante R, Paglianiti DA, Bianchini E, et al. Safety and efficacy of early initiation of sodium–glucose co-transporter inhibitors 2 in patients hospitalized for acute heart failure: a meta-analysis of randomized controlled trials. Eur J Intern Med 2025:S0953-6205(25)00024-X. 
    Crossref | PubMed
  8. Metra M, Tomasoni D, Adamo M, et al. Worsening of chronic heart failure: definition, epidemiology, management and prevention. A clinical consensus statement by the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2023;25:776–91. 
    Crossref | PubMed
  9. McDonagh TA, Metra M, Adamo M, et al. ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2021;42:3599–726. 
    Crossref | PubMed
  10. Tromp J, Ouwerkerk W, van Veldhuisen DJ, et al. A systematic review and network meta-analysis of pharmacological treatment of heart failure with reduced ejection fraction. JACC Heart Fail 2022;10:73–84. 
    Crossref | PubMed
  11. Zafeiropoulos S, Farmakis IT, Milioglou I, et al. Pharmacological treatments in heart failure with mildly reduced and preserved ejection fraction: systematic review and network meta-analysis. JACC Heart Fail 2024;12:616–27. 
    Crossref | PubMed
  12. Felker GM, Lee KL, Bull DA, et al. Diuretic strategies in patients with acute decompensated heart failure. N Engl J Med 2011;364:797–805. 
    Crossref | PubMed
  13. Bertrand OF, Larose É, Bagur R, et al. A randomized double-blind placebo-controlled study comparing intracoronary versus intravenous abciximab in patients with ST-elevation myocardial infarction undergoing transradial rescue percutaneous coronary intervention after failed thrombolysis. Am J Cardiol 2018;122:47–53. 
    Crossref | PubMed
  14. Trullàs JC, Morales-Rull JL, Casado J, et al. Combining loop with thiazide diuretics for decompensated heart failure: the CLOROTIC trial. Eur Heart J 2023;44:411–21. 
    Crossref | PubMed
  15. Mullens W, Dauw J, Martens P, et al. Acetazolamide in acute decompensated heart failure with volume overload. N Engl J Med 2022;387:1185–95. 
    Crossref | PubMed
  16. Mentz RJ, O’Connor CM. Pathophysiology and clinical evaluation of acute heart failure. Nat Rev Cardiol 2016;13:28–35. 
    Crossref | PubMed
  17. Vardeny O, Claggett B, Kachadourian J, et al. Reduced loop diuretic use in patients taking sacubitril/valsartan compared with enalapril: the PARADIGM-HF trial. Eur J Heart Fail 2019;21:337–41. 
    Crossref | PubMed
  18. Chatur S, Claggett BL, Vardeny O, et al. Sacubitril/valsartan and loop diuretic requirement in heart failure with preserved ejection fraction in the Paragon-HF trial. Eur J Heart Fail 2023;25:87–94. 
    Crossref | PubMed
  19. Velazquez EJ, Morrow DA, DeVore AD, et al. Angiotensin–neprilysin inhibition in acute decompensated heart failure. N Engl J Med 2019;380:539–48. 
    Crossref | PubMed
  20. Mebazaa A, Davison BA, Biegus J, et al. Reduced congestion and improved response to a fluid/sodium challenge in chronic heart failure patients after initiation of sacubitril/valsartan: the NATRIUM-HF study. Eur J Heart Fail 2024;26:1507–17. 
    Crossref | PubMed
  21. Laborante R, Delvinioti A, Tudor AM, et al. Temporal trends in guideline-recommended medical therapy after an acute heart failure decompensation event: an observational analysis from Generator Heart Failure DataMart. BMJ Open 2025;15:e088998. 
    Crossref | PubMed
  22. Kobayashi M, Ferreira JP, Matsue Y, et al. Effect of eplerenone on clinical stability of Japanese patients with acute heart failure. Int J Cardiol 2023;374:73–8. 
    Crossref | PubMed
  23. Pitt B, Remme W, Zannad F, et al. Eplerenone, a selective aldosterone blocker, in patients with left ventricular dysfunction after myocardial infarction. N Engl J Med 2003;348:1309–21. 
    Crossref | PubMed
  24. Zalawadiya SK, Kiernan M, Borlaug BA, et al. Changes in seated pulmonary artery pressure in response to titration of heart failure medications during ambulatory monitoring. J Card Fail 2025:S1071-9164(25)00052-1. 
    Crossref | PubMed
  25. Biegus J, Fudim M, Salah HM, et al. Sodium–glucose cotransporter-2 inhibitors in heart failure: potential decongestive mechanisms and current clinical studies. Eur J Heart Fail 2023;25:1526–36. 
    Crossref | PubMed
  26. Boorsma EM, Beusekamp JC, Ter Maaten JM, et al. Effects of empagliflozin on renal sodium and glucose handling in patients with acute heart failure. Eur J Heart Fail 2021;23:68–78. 
    Crossref | PubMed
  27. Schulze PC, Bogoviku J, Westphal J, et al. Effects of early empagliflozin initiation on diuresis and kidney function in patients with acute decompensated heart failure (EMPAG-HF). Circulation 2022;146:289–98. 
    Crossref | PubMed
  28. Asakura-Kinoshita M, Masuda T, Oka K, et al. Sodium–glucose cotransporter 2 inhibitor combined with conventional diuretics ameliorate body fluid retention without excessive plasma volume reduction. Diagnostics (Basel) 2024;14:1194. 
    Crossref | PubMed
  29. Packer M. Critical reanalysis of the mechanisms underlying the cardiorenal benefits of SGLT2 inhibitors and reaffirmation of the nutrient deprivation signaling/autophagy hypothesis. Circulation 2022;146:1383–405. 
    Crossref | PubMed
  30. Omar M, Jensen J, Burkhoff D, et al. Effect of empagliflozin on blood volume redistribution in patients with chronic heart failure and reduced ejection fraction: an analysis from the empire HF randomized clinical trial. Circ Heart Fail 2022;15:e009156. 
    Crossref | PubMed
  31. Nassif ME, Qintar M, Windsor SL, et al. Empagliflozin effects on pulmonary artery pressure in patients with heart failure: results from the EMBRACE-HF trial. Circulation 2021;143:1673–86. 
    Crossref | PubMed
  32. Borlaug BA, Testani JM. SGLT2 inhibitors and diuretics in heart failure: clicking reset on the renal volume setpoint? Eur Heart J 2023;44:2944–6. 
    Crossref | PubMed
  33. Wilcox CS, Shen W, Boulton DW, et al. Interaction between the sodium–glucose-linked Transporter 2 inhibitor dapagliflozin and the loop diuretic bumetanide in normal human subjects. J Am Heart Assoc 2018;7:e007046. 
    Crossref | PubMed
  34. Damman K, Kjekshus J, Wikstrand J, et al. Loop diuretics, renal function and clinical outcome in patients with heart failure and reduced ejection fraction. Eur J Heart Fail 2016;18:328–36. 
    Crossref | PubMed
  35. Ter Maaten JM, Martens P, Damman K, et al. Higher doses of loop diuretics limit uptitration of angiotensin-converting enzyme inhibitors in patients with heart failure and reduced ejection fraction. Clin Res Cardiol 2020;109:1048–59. 
    Crossref | PubMed
  36. Chouairi F, Fudim M, Savarese G, et al. Utility of loop diuretics as a marker of risk in clinical trials of heart failure with preserved ejection fraction: analysis from the Swedish Heart Failure Registry. Eur J Heart Fail 2025. 
    Crossref | PubMed
  37. Florea VG, Cohn JN. The autonomic nervous system and heart failure. Circ Res 2014;114:1815–26. 
    Crossref | PubMed
  38. Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association joint committee on clinical practice guidelines. Circulation 2022;145:e895–1032. 
    Crossref | PubMed
  39. Cruz M, Ferreira JP, Diaz SO, et al. Lung ultrasound and diuretic therapy in chronic heart failure: a randomised trial. Clin Res Cardiol 2024;113:425–32. 
    Crossref | PubMed
  40. Iaconelli A, Pellicori P, Caiazzo E, et al. Implanted haemodynamic telemonitoring devices to guide management of heart failure: a review and meta-analysis of randomised trials. Clin Res Cardiol 2023;112:1007–19. 
    Crossref | PubMed
  41. Abraham WT, Adamson PB, Bourge RC, et al. Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomised controlled trial. Lancet 2011;377:658–66. 
    Crossref | PubMed
  42. Lindenfeld J, Zile MR, Desai AS, et al. Haemodynamic-guided management of heart failure (GUIDE-HF): a randomised controlled trial. Lancet 2021;398:991–1001. 
    Crossref | PubMed
  43. Brugts JJ, Radhoe SP, Clephas PRD, et al. Remote haemodynamic monitoring of pulmonary artery pressures in patients with chronic heart failure (MONITOR-HF): a randomised clinical trial. Lancet 2023;401:2113–23. 
    Crossref | PubMed
  44. Clephas PRD, Radhoe SP, Boersma E, et al. Efficacy of pulmonary artery pressure monitoring in patients with chronic heart failure: a meta-analysis of three randomized controlled trials. Eur Heart J 2023;44:3658–68. 
    Crossref | PubMed
  45. Costanzo MR, Stevenson LW, Adamson PB, et al. Interventions linked to decreased heart failure hospitalizations during ambulatory pulmonary artery pressure monitoring. JACC Heart Fail 2016;4:333–44. 
    Crossref | PubMed
  46. Zile MR, Mehra MR, Ducharme A, et al. Hemodynamically-guided management of heart failure across the ejection fraction spectrum: the GUIDE-HF trial. JACC Heart Fail 2022;10:931–44. 
    Crossref | PubMed
  47. Shavelle DM, Desai AS, Abraham WT, et al. Lower rates of heart failure and all-cause hospitalizations during pulmonary artery pressure-guided therapy for ambulatory heart failure: one-year outcomes from the CardioMEMS Post-Approval Study. Circ Heart Fail 2020;13:e006863. 
    Crossref | PubMed
  48. Visco V, Esposito C, Rispoli A, et al. The favourable alliance between CardioMEMS and levosimendan in patients with advanced heart failure. ESC Heart Fail 2024;11:2835–48. 
    Crossref | PubMed
  49. Guichard Jason L, Bonno Eric L, Nassif Michael E, et al. Seated pulmonary artery pressure monitoring in patients with heart failure: results of the PROACTIVE-HF Trial. JACC Heart Fail 2024;12:1879–93. 
    Crossref | PubMed
  50. Sharif F, Rosenkranz S, Bartunek J, et al. Twelve-month follow-up results from the SIRONA 2 clinical trial. ESC Heart Fail 2024;11:1133–43. 
    Crossref | PubMed
  51. Mullens W, Sharif F, Dupont M, et al. Digital health care solution for proactive heart failure management with the Cordella Heart Failure System: results of the SIRONA first-in-human study. Eur J Heart Fail 2020;22:1912–9. 
    Crossref | PubMed
  52. Dauw J, Sokolski M, Middleton JT, et al. Ambulatory haemodynamic-guided management reduces heart failure hospitalizations in a multicentre European heart failure cohort. ESC Heart Fail 2022;9:3858–67. 
    Crossref | PubMed
  53. Bourge RC, Abraham WT, Adamson PB, et al. Randomized controlled trial of an implantable continuous hemodynamic monitor in patients with advanced heart failure: the COMPASS-HF study. J Am Coll Cardiol 2008;51:1073–9. 
    Crossref | PubMed
  54. Adamson PB, Gold MR, Bennett T, et al. Continuous hemodynamic monitoring in patients with mild to moderate heart failure: results of the reducing decompensation events utilizing intracardiac pressures in patients with chronic heart failure (REDUCEhf) trial. Congest Heart Fail 2011;17:248–54. 
    Crossref | PubMed
  55. Campbell P, Drazner MH, Kato M, et al. Mismatch of right- and left-sided filling pressures in chronic heart failure. J Card Fail 2011;17:561–8. 
    Crossref | PubMed
  56. De Rosa R, Piscione F, Schranz D, et al. Transcatheter implantable devices to monitoring of elevated left atrial pressures in patients with chronic heart failure. Transl Med UniSA 2017;17:19–21.
    PubMed
  57. Ritzema J, Troughton R, Melton I, et al. Physician-directed patient self-management of left atrial pressure in advanced chronic heart failure. Circulation 2010;121:1086–95. 
    Crossref | PubMed
  58. Abraham WT, Adamson PB, Costanzo MR, et al. Hemodynamic monitoring in advanced heart failure: results from the LAPTOP-HF trial. J Card Fail 2016;22:940. 
    Crossref
  59. Perl L, Soifer E, Bartunek J, et al. A novel wireless left atrial pressure monitoring system for patients with heart failure, first ex-vivo and animal experience. J Cardiovasc Transl Res 2019;12:290–8. 
    Crossref | PubMed
  60. D’Amario D, Meerkin D, Restivo A, et al. Safety, usability, and performance of a wireless left atrial pressure monitoring system in patients with heart failure: the VECTOR-HF trial. Eur J Heart Fail 2023;25:902–11. 
    Crossref | PubMed
  61. D’Amario D, Restivo A, Canonico F, et al. Experience of remote cardiac care during the COVID-19 pandemic: the V-LAP™ device in advanced heart failure. Eur J Heart Fail 2020;22:1050–2. 
    Crossref | PubMed
  62. Restivo A, Paglianiti DA, D’Amario D. Left atrial pressure-assisted acute heart failure management in the cardiac intensive care unit: a proof-of-concept. Eur Heart J 2023;44:5169–. 
    Crossref | PubMed
  63. Restivo A, D’Amario D, Paglianiti DA, et al. A 3-year single center experience with left atrial pressure remote monitoring: the long and winding road. Front Cardiovasc Med 2022;9:899656. 
    Crossref | PubMed
  64. Sheridan WS, Wetterling F, Testani JM, et al. Safety and performance of a novel implantable sensor in the inferior vena cava under acute and chronic intravascular volume modulation. Eur J Heart Fail 2023;25:754–63. 
    Crossref | PubMed
  65. Shen L, Jhund PS, Petrie MC, et al. Declining risk of sudden death in heart failure. N Engl J Med 2017;377:41–51. 
    Crossref | PubMed
  66. Mignone JL, Alexander KM, Dobbles M, et al. Outcomes with guideline-directed medical therapy and cardiac implantable electronic device therapies for patients with heart failure with reduced ejection fraction. Heart Rhythm 2024;5:168–73. 
    Crossref | PubMed
  67. Sahin A, Celik A, Ural D, et al. Impact of implantable cardioverter defibrillators on mortality in heart failure receiving quadruple guideline-directed medical therapy: a propensity score-matched study. BMC Med 2024;22:539. 
    Crossref | PubMed
  68. Dhande M, Rangavajla G, Canterbury A, et al. Guideline-directed medical therapy and the risk of death in primary prevention defibrillator recipients. JACC Clin Electrophysiol 2022;8:1024–30. 
    Crossref | PubMed
  69. Salimian S, Moghaddam N, Deyell MW, et al. Defining the gap in heart failure treatment in patients with cardiac implantable electronic devices. Clin Res Cardiol 2023;112:158–66. 
    Crossref | PubMed
  70. Mullens W, Auricchio A, Martens P, et al. Optimized implementation of cardiac resynchronization therapy: a call for action for referral and optimization of care: a joint position statement from the Heart Failure Association (HFA), European Heart Rhythm Association (EHRA), and European Association of Cardiovascular Imaging (EACVI) of the European Society of Cardiology. Eur J Heart Fail 2020;22:2349–69. 
    Crossref | PubMed
  71. Zito A, Restivo A, Ciliberti G, et al. Heart failure management guided by remote multiparameter monitoring: a meta-analysis. Int J Cardiol 2023;388:131163. 
    Crossref | PubMed
  72. Guédon-Moreau L, Lacroix D, Sadoul N, et al. A randomized study of remote follow-up of implantable cardioverter defibrillators: safety and efficacy report of the ECOST trial. Eur Heart J 2013;34:605–14. 
    Crossref | PubMed
  73. Morgan JM, Kitt S, Gill J, et al. Remote management of heart failure using implantable electronic devices. Eur Heart J 2017;38:2352–60. 
    Crossref | PubMed
  74. Hindricks G, Taborsky M, Glikson M, et al. Implant-based multiparameter telemonitoring of patients with heart failure (IN-TIME): a randomised controlled trial. Lancet 2014;384:583–90. 
    Crossref | PubMed
  75. Tajstra M, Sokal A, Gadula-Gacek E, et al. Remote Supervision to Decrease Hospitalization Rate (RESULT) study in patients with implanted cardioverter-defibrillator. Europace 2020;22:769–76. 
    Crossref | PubMed
  76. Varma N, Epstein AE, Irimpen A, et al. Efficacy and safety of automatic remote monitoring for implantable cardioverter-defibrillator follow-up: the Lumos-T Safely Reduces Routine Office Device Follow-up (TRUST) trial. Circulation 2010;122:325–32. 
    Crossref | PubMed
  77. Schlosshan D, Barker D, Pepper C, et al. CRT improves the exercise capacity and functional reserve of the failing heart through enhancing the cardiac flow- and pressure-generating capacity. Eur J Heart Fail 2006;8:515–21. 
    Crossref | PubMed
  78. Chwyczko T, Sterliński M, Maciag A, et al. Impact of cardiac resynchronisation therapy on adaptation of circulatory and respiratory systems to exercise assessed by cardiopulmonary exercise test in patients with chronic heart failure. Kardiol Pol 2008;66:406–12; discussion 13–4.
    PubMed
  79. Coksevim M, Akcay M, Yuksel S, et al. The effect of cardiac resynchronization therapy on arterial stiffness and central hemodynamic parameters. J Arrhythm 2020;36:498–507. 
    Crossref | PubMed
  80. Cleland JGF, Daubert JC, Erdmann E, et al. The effect of cardiac resynchronization on morbidity and mortality in heart failure. N Engl J Med 2005;352:1539–49. 
    Crossref | PubMed
  81. Bristow MR, Saxon LA, Boehmer J, et al. Cardiac-resynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure. N Engl J Med 2004;350:2140–50. 
    Crossref | PubMed
  82. D’Onofrio A, Palmisano P, Rapacciuolo A, et al. Effectiveness of a management program for outpatient clinic or remote titration of beta-blockers in CRT patients: the RESTORE study. Int J Cardiol 2017;236:290–5. 
    Crossref | PubMed
  83. Martens P, Verbrugge FH, Nijst P, et al. Feasibility and association of neurohumoral blocker up-titration after cardiac resynchronization therapy. J Card Fail 2017;23:597–605. 
    Crossref | PubMed
  84. Salimian S, Deyell MW, Andrade JG, et al. Heart failure treatment in patients with cardiac implantable electronic devices: opportunity for improvement. Heart Rhythm 2021;2;2:698–709. 
    Crossref | PubMed
  85. D’Amario D, Laborante R, Delvinioti A, et al. Generator heart failure DataMart: an integrated framework for heart failure research. Front Cardiovasc Med 2023;10:1104699. 
    Crossref | PubMed
  86. Hughes A, Shandhi MMH, Master H, et al. Wearable devices in cardiovascular medicine. Circ Res 2023;132:652–70. 
    Crossref | PubMed
  87. Man JP, Klopotowska J, Asselbergs FW, et al. Digital solutions to optimize guideline-directed medical therapy prescriptions in heart failure patients: current applications and future directions. Curr Heart Fail Rep 2024;21:147–61. 
    Crossref | PubMed
  88. Antonicelli R, Testarmata P, Spazzafumo L, et al. Impact of telemonitoring at home on the management of elderly patients with congestive heart failure. J Telemed Telecare 2008;14:300–5. 
    Crossref | PubMed
  89. Scholte NTB, Gürgöze MT, Aydin D, et al. Telemonitoring for heart failure: a meta-analysis. Eur Heart J 2023;44:2911–26. 
    Crossref | PubMed
  90. Dendale P, De Keulenaer G, Troisfontaines P, et al. Effect of a telemonitoring-facilitated collaboration between general practitioner and heart failure clinic on mortality and rehospitalization rates in severe heart failure: the TEMA-HF 1 (TElemonitoring in the MAnagement of Heart Failure) study. Eur J Heart Fail 2012;14:333–40. 
    Crossref | PubMed
  91. Koehler F, Koehler K, Deckwart O, et al. Efficacy of telemedical interventional management in patients with heart failure (TIM-HF2): a randomised, controlled, parallel-group, unmasked trial. Lancet 2018;392:1047–57. 
    Crossref | PubMed
  92. Girerd N, Barbet V, Seronde MF, et al. Association of a remote monitoring programme with all-cause mortality and hospitalizations in patients with heart failure: national-scale, real-world evidence from a 3-year propensity score analysis of the TELESAT-HF study. Eur J Heart Fail 2025. 
    Crossref | PubMed
  93. Myhre PL, Tromp J, Ouwerkerk W, et al. Digital tools in heart failure: addressing unmet needs. Lancet Digit Health 2024;6:e755–66. 
    Crossref | PubMed
  94. Chen C, Porter R, Zhou X, et al. Microfluidic digital immunoassay for point-of-care detection of NT-proBNP from whole blood. Anal Chem 2024;96:10569–76. 
    Crossref | PubMed
  95. Savarese G, Kishi T, Vardeny O, et al. Heart failure drug treatment-inertia, titration, and discontinuation: a multinational observational study (EVOLUTION HF). JACC Heart Fail 2023;11:1–14. 
    Crossref | PubMed
  96. Savarese G, Lindberg F, Christodorescu RM, et al. Physician perceptions, attitudes, and strategies towards implementing guideline-directed medical therapy in heart failure with reduced ejection fraction. A survey of the Heart Failure Association of the ESC and the ESC Council for Cardiology Practice. Eur J Heart Fail 2024;26:1408–18. 
    Crossref | PubMed
  97. Itelman E, Segel MJ, Kuperstein R, et al. Pulmonary hypertension is associated with systemic arterial hypertension among patients with normal left ventricular diastolic function. J Am Heart Assoc 2021;10:e023603. 
    Crossref | PubMed
  98. Schuuring MJ, Treskes RW, Castiello T, et al. Digital solutions to optimize guideline-directed medical therapy prescription rates in patients with heart failure: a clinical consensus statement from the ESC Working Group on e-Cardiology, the Heart Failure Association of the European Society of Cardiology, the Association of Cardiovascular Nursing & Allied Professions of the European Society of Cardiology, the ESC Digital Health Committee, the ESC Council of Cardio-Oncology, and the ESC Patient Forum. European Heart. Eur Heart J Digit Health 2024;5:670–82. 
    Crossref | PubMed
  99. Rossignol P, Coats AJ, Chioncel O, et al. Renal function, electrolytes, and congestion monitoring in heart failure. Eur Heart J Suppl 2019;21(Suppl M):M25–31. 
    Crossref | PubMed
  100. Cheng J, Guo J, Li X, Guo J. A smartphone-connected point-of-care photochemical biosensor for the determination of whole blood creatinine by differential optical signal readout. Biosens Bioelectron 2023;235:115410. 
    Crossref | PubMed
  101. Attia ZI, DeSimone CV, Dillon JJ, et al. Novel bloodless potassium determination using a signal-processed single-lead ECG. J Am Heart Assoc 2016;5:e002746. 
    Crossref | PubMed
  102. Chiu IM, Wu PJ, Zhang H, et al. Serum potassium monitoring using AI-enabled smartwatch electrocardiograms. JACC Clin Electrophysiol 2024;10:2644–54. 
    Crossref | PubMed
  103. Allen LA, Venechuk G, McIlvennan CK, et al. An electronically delivered patient-activation tool for intensification of medications for chronic heart failure with reduced ejection fraction: the EPIC-HF Trial. Circulation 2021;143:427–37. 
    Crossref | PubMed
  104. Bezerra Giordan L, Tong HL, Atherton JJ, et al. The use of mobile apps for heart failure self-management: systematic review of experimental and qualitative studies. JMIR Cardio 2022;6:e33839. 
    Crossref | PubMed
  105. Joseph J, S SP, James J, et al. Guideline-directed medical therapy in heart failure patients: impact of focused care provided by a heart failure clinic in comparison to general cardiology out-patient department. Egypt Heart J 2020;72:53. 
    Crossref | PubMed
  106. Mentias A, Keshvani N, Sumarsono A, et al. Patterns, prognostic implications, and rural-urban disparities in optimal GDMT following HFrEF diagnosis among Medicare beneficiaries. JACC Heart Fail 2024;12:1044–55. 
    Crossref | PubMed
  107. Azizi Z, Broadwin C, Islam S, et al. Digital health interventions for heart failure management in underserved rural areas of the United States: a systematic review of randomized trials. J Am Heart Assoc 2024;13:e030956. 
    Crossref | PubMed
  108. Usherwood T. Therapeutic inertia. Aust Prescr 2024;47:15–9. 
    Crossref | PubMed
  109. Tang AB, Brownell NK, Roberts JS, et al. Interventions for optimization of guideline-directed medical therapy: a systematic review. JAMA Cardiol 2024;9:397–404. 
    Crossref | PubMed
  110. Wakefield BJ, Holman JE, Ray A, et al. Outcomes of a home telehealth intervention for patients with heart failure. J Telemed Telecare 2009;15:46–50. 
    Crossref | PubMed
  111. Romero E, Yala S, Sellers-Porter C, et al. Remote monitoring titration clinic to implement guideline-directed therapy for heart failure patients with reduced ejection fraction: a pilot quality-improvement intervention. Front Cardiovasc Med 2023;10:1202615. 
    Crossref | PubMed
  112. Brahmbhatt DH, Ross HJ, O’Sullivan M, et al. The effect of using a remote patient management platform in optimizing guideline-directed medical therapy in heart failure patients: a randomized controlled trial. JACC Heart Fail 2024;12:678–90. 
    Crossref | PubMed
  113. Haywood HB, Fonarow GC, Khan MS, et al. Hospital at home as a treatment strategy for worsening heart failure. Circ Heart Fail 2023;16:e010456. 
    Crossref | PubMed
  114. Qaddoura A, Yazdan-Ashoori P, Kabali C, et al. Efficacy of hospital at home in patients with heart failure: a systematic review and meta-analysis. PLoS One 2015;10:e0129282. 
    Crossref | PubMed
  115. Basso I, Bassi E, Caristia S, et al. A nurse-led coaching intervention with home telemonitoring for patients with heart failure: protocol for a feasibility randomized clinical trial. MethodsX 2024;13:102832. 
    Crossref | PubMed
  116. Suksatan W, Tankumpuan T, Davidson PM. Heart failure caregiver burden and outcomes: a systematic review. J Prim Care Community Health 2022;13:21501319221112584. 
    Crossref | PubMed
  117. Piette JD, Striplin D, Marinec N, et al. A mobile health intervention supporting heart failure patients and their informal caregivers: a randomized comparative effectiveness trial. J Med Internet Res 2015;17:e142. 
    Crossref | PubMed
  118. Gingele AJ, Amin H, Vaassen A, et al. Integrating avatar technology into a telemedicine application in heart failure patients: a pilot study. Wien Klin Wochenschr 2023;135:680–4. 
    Crossref | PubMed
  119. Schumacher PM, Becker N, Tsuyuki RT, et al. The evidence for pharmacist care in outpatients with heart failure: a systematic review and meta-analysis. ESC Heart Fail 2021;8:3566–76. 
    Crossref | PubMed
  120. Bhatt AS, Varshney AS, Moscone A, et al. Virtual care team guided management of patients with heart failure during hospitalization. J Am Coll Cardiol 2023;81:1680–93. 
    Crossref | PubMed
  121. Lynch KA, Ganz DA, Saliba D, et al. Improving heart failure care and guideline-directed medical therapy through proactive remote patient monitoring-home telehealth and pharmacy integration. BMJ Open Qual 2022;11:e001901. 
    Crossref | PubMed
  122. Miles LM, Elbourne D, Farmer A, et al. Bias due to MEasurement Reactions In Trials to improve health (MERIT): protocol for research to develop MRC guidance. Trials 2018;19:653. 
    Crossref | PubMed
  123. Artanian V, Ross HJ, Rac VE, O’Sullivan M, Brahmbhatt DH, Seto E. Impact of remote titration combined with telemonitoring on the optimization of guideline-directed medical therapy for patients with heart failure: internal pilot of a randomized controlled trial. JMIR Cardio 2020;4:e21962. 
    Crossref | PubMed
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