Monitoring Of Heart Failure Patients Research Articles

Blood urea monitoring in heart failure patients - an important predictor of mortality

Abstract Background Recent ESC position statement regarding worsening renal failure recommends the use of blood urea monitoring of patients with heart failure with reduced ejection fraction (HFrEF). Although both serum creatinine and blood urea nitrogen are markers for renal dysfunction, blood urea nitrogen levels are also affected by reabsorption in the renal tubules, a process modulated by renin-angiotensin-aldosterone activity, sympathetic nervous activity and arginine-vasopressin activity. Thus, neurohormonal activity is reflected in the BUN/creatinine ratio (bUCR) which effectively ‘normalizes’ BUN for the degree of renal dysfunction, as measured by the creatinine level. Previous studies have demonstrated increased mortality at bUCR >100mmol/l. however, most of the prognostic data has come from patients admitted with acute heart failure. The use of bUCR in patients with chronic HFrHF receiving intensive titration of guideline directed medical therapy (GDMT) has not been studied. Purpose To identify the extent of blood urea monitoring in primary care in HFrEF and whether bUCR remains a significant prognostic indicator despite intensive GDMT. Methods We analysed the electronic health records of all patients referred to the Heart Failure Nurse Service (HFNS) in an NHS population approx. 400,000 in 2022. Inclusion criteria consists of patients with symptomatic heart failure NYHA II-IV with echocardiogram demonstrating HFrEF. Patients were segregated into two cohorts, with a urea/creatinine ratio greater or less than 100mmol/l and analysed. Results Data from 338 patients [mean age 72.3 ± 15.6 years; 218 (64.5%) males; 143 (42.3%) ischaemic cardiomyopathy; 141 (41.7%) AF; 49 (14.5%)] were analysed. Of these, 112 (33.1%) had chronic kidney disease (CKD) with eGFR <60 ml/min/1.73m2 at the time of HF diagnosis and 181 (53.6%) had CKD on discharge from the HFNS. During follow-up, 132 (39%) had further admission with HF and 76 (22.5%) died. Sixty-eight (20.1%) patients did not have blood urea checked despite the availability of serum creatinine. While an eGFR < 60 ml/min/1.73m2 at discharge was associated with a twofold increased risk of death (OR 2.4, 95% CI 1.1-5.3, p=0.029), a bUCR > 100mmol/l at discharge was associated with a four-times greater risk of death (OR 4.2, 95% CI 2.2-7.9, p <0.001). Conclusion Blood urea/creatinine ratio is an important predictor of outcome and can be utilised to help identify at-risk patients with HFrEF despite intensive GDMT.Survival from diagnosis bUCR

The nurse consultant in remote medical monitoring: an innovative, patient-centered approach

Telemedical monitoring of heart failure patients is revolutionizing the traditional approach to care, thanks to the crucial role played by nurse consultants. Based on two years' experience in a telemonitoring unit, where the practice model is outside the conventional nursing context, we aim to highlight this innovative method, which is helping to improve the care and benefits of patients with chronic pathologies. This patient-centered approach offers holistic, individualized care through personalized remote monitoring, fostering a relationship of trust and encouraging patient autonomy.

Increasing adherence and collecting symptom-specific biometric signals in remote monitoring of heart failure patients: a randomized controlled trial.

Mobile health (mHealth) regimens can improve health through the continuous monitoring of biometric parameters paired with appropriate interventions. However, adherence to monitoring tends to decay over time. Our randomized controlled trial sought to determine: (1) if a mobile app with gamification and financial incentives significantly increases adherence to mHealth monitoring in a population of heart failure patients; and (2) if activity data correlate with disease-specific symptoms. We recruited individuals with heart failure into a prospective 180-day monitoring study with 3 arms. All 3 arms included monitoring with a connected weight scale and an activity tracker. The second arm included an additional mobile app with gamification, and the third arm included the mobile app and a financial incentive awarded based on adherence to mobile monitoring. We recruited 111 heart failure patients into the study. We found that the arm including the financial incentive led to significantly higher adherence to activity tracker (95% vs 72.2%, P = .01) and weight (87.5% vs 69.4%, P = .002) monitoring compared to the arm that included the monitoring devices alone. Furthermore, we found a significant correlation between daily steps and daily symptom severity. Our findings indicate that mobile apps with added engagement features can be useful tools for improving adherence over time and may thus increase the impact of mHealth-driven interventions. Additionally, activity tracker data can provide passive monitoring of disease burden that may be used to predict future events.

Early relevant alerts from remote monitoring in heart failure patients with a cardiac implanted electronic device: what implications for long term outcome?

Abstract Background Alarms generated by remote monitoring (RM) of cardiac implantable electronic devices (CIEDs) have been associated with worse clinical outcomes in patients with heart failure (HF). However, whether the timing of RM alerts impact on the clinical trajectories of HF patients is still debated. Purpose To examine the impact of alerts occurring in the first 180 days after CIED implant on clinical outcomes, as well as potential predictors. Methods we retrospectively enrolled all patients with a history of HF implanted with a CRT-D or an ICD at our tertiary. We collected data regarding ATP, shock and HF score above threshold (defined as multiparametric scores provided and validated by all CIED manufacturers). We defined early relevant alerts (Early-RA) as alarms received during the first 180 days after implant. The primary clinical outcome of the study was a composite of death or HF hospitalization. Logistic and Cox regression analyses were used to determine associations. The occurrence of early-RA was used as a time dependent covariate. Results A total of 272 patients were included in the analysis (median age 67.4 years, IQR 58.6-74.6, 19.9% female). Twenty patients had an early-RA (7.3% of the overall study population) and were found to be older, more severely symptomatic for HF, with a higher prevalence of atrial fibrillation (AF) and chronic kidney disease (CKD) (all p values<0.05). On the other hand, HF etiology and prevalence of CRT-D did not differ between the two groups. At univariate logistic regression analysis, we found the following factors as significantly associated with early-RA: age (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.00-1.10), NYHA class (OR 2.44, 95% CI 1.01-5.82) and CKD (OR 3.41, 95% CI 1.21-8.98), but these results were not confirmed at the multivariable logistic regression. After a median follow-up of 959 days (IQR 432-1484), patients reporting an early-RA had more primary outcome events (45.0% vs 12.3% p<0.001). At time-dependent multivariable Cox regression analysis adjusted for age, sex, left ventricular ejection fraction and type of CIED, we found that early-RA were independently associated with a higher risk of the primary outcome (hazard ratio [HR] 3.61, 95%CI 1.42-9.18) (Figure). Early-RA were also associated with a higher risk of death (HR 5.58, 95% CI 1.68-18.50) while no significant association was found for HF hospitalization (HR 2.46, 95% CI 0.80-7.57, p=0.116). Conclusions The occurrence of alerts detected by RM of CIEDs in a relatively early phase (within 180 days from implant), is associated with a higher risk of a composite of death and HF hospitalization in HF patients.Study Outcome according to Early RATime dependent Cox regression

MEMS Technology in Cardiology: Advancements and Applications in Heart Failure Management Focusing on the CardioMEMS Device.

Heart failure (HF) is a complex clinical syndrome associated with significant morbidity, mortality, and healthcare costs. It is characterized by various structural and/or functional abnormalities of the heart, resulting in elevated intracardiac pressure and/or inadequate cardiac output at rest and/or during exercise. These dysfunctions can originate from a variety of conditions, including coronary artery disease, hypertension, cardiomyopathies, heart valve disorders, arrhythmias, and other lifestyle or systemic factors. Identifying the underlying cause is crucial for detecting reversible or treatable forms of HF. Recent epidemiological studies indicate that there has not been an increase in the incidence of the disease. Instead, patients seem to experience a chronic trajectory marked by frequent hospitalizations and stagnant mortality rates. Managing these patients requires a multidisciplinary approach that focuses on preventing disease progression, controlling symptoms, and preventing acute decompensations. In the outpatient setting, patient self-care plays a vital role in achieving these goals. This involves implementing necessary lifestyle changes and promptly recognizing symptoms/signs such as dyspnea, lower limb edema, or unexpected weight gain over a few days, to alert the healthcare team for evaluation of medication adjustments. Traditional methods of HF monitoring, such as symptom assessment and periodic clinic visits, may not capture subtle changes in hemodynamics. Sensor-based technologies offer a promising solution for remote monitoring of HF patients, enabling early detection of fluid overload and optimization of medical therapy. In this review, we provide an overview of the CardioMEMS device, a novel sensor-based system for pulmonary artery pressure monitoring in HF patients. We discuss the technical aspects, clinical evidence, and future directions of CardioMEMS in HF management.

Healthcare Monitoring-based IoT framework for heart disease detection and classification

Background: Chronic diseases like diabetes, heart disease, and cancer pose significant global health challenges, contributing to a substantial portion of worldwide mortality. Diagnosing heart disease, with its diverse signs and symptoms, remains a complex task. The growing market for connected wearable devices presents opportunities for leveraging Internet of Things (IoT) technologies in healthcare. However, diagnosing and managing heart disease effectively remains a critical concern due to its high fatality rates. Integrating IoT into the traditional healthcare system holds promise for enhancing patient outcomes, particularly for those with heart disease. Methods: A Healthcare Monitoring-based IoT framework (HM-IoT) has been developed to enable continuous monitoring of heart disease patients, eliminating the need for manual feature extraction. This framework facilitates real-time monitoring of heart failure patients through IoT-enabled devices. Data encryption using the Enhanced Encryption Standard algorithm ensures the security of patient information within the cloud platform. An Artificial Neural Network (ANN) model is employed to classify encrypted data, promptly alerting healthcare professionals to abnormal physiological conditions. Results: Evaluation in Matlab revealed impressive processing capabilities, with decryption and encryption rates of 1085 milliseconds and 1075 milliseconds, respectively. Data protection level reached 91%, while the Security Rate level attained 99%. Performance metrics, including Accuracy (98%), Sensitivity (96%), Specificity (98%), and Precision (99.4%), demonstrated the reliability of the system in detecting potential instances of heart disease. Conclusion: The Healthcare Monitoring-based IoT framework represents a significant advancement in smart healthcare solutions for heart disease management. By integrating IoT technologies with healthcare infrastructure, the framework enables real-time monitoring, enhancing prognostic capabilities and facilitating timely interventions.

Novel Pulse Waveform Index by Ambulatory Blood Pressure Monitoring and Cardiac Function: A Pilot Study

BackgroundA simple ambulatory measure of cardiac function could be helpful for monitoring heart failure patients. ObjectivesThe purpose of this paper was to determine whether a novel pulse waveform analysis using data obtained by our developed multisensor-ambulatory blood pressure monitoring (ABPM) device, the 'Sf/Am' ratio, is associated with echocardiographic left ventricular ejection fraction (LVEF). MethodsMultisensor-ABPM was conducted twice at baseline in 20 heart failure (HF) patients with HF-reduced LVEF or HF-preserved LVEF (median age 66 years, male 65%) and over a 6- to 12-month follow-up after patient-tailored treatment. We assessed the changes in the pulse waveform index Sf/Am and LVEF that occurred between the baseline and follow-up. The Sf/Am consists of the area of the ejection part in the square forward wave (Sf) and the amplitude of the measured wave (Am). We divided the patients into the recovered (n = 11) and not-recovered (n = 9) groups defined by a ≥10% increase in LVEF. ResultsAlthough the ambulatory BP levels and variabilities did not change in either group, the Sf/Am increased significantly in the recovered group (baseline 21.4 ± 4.5; follow-up, 25.6 ± 3.7, P = 0.004). The not-recovered group showed no difference between the baseline and follow-up. The follow-up/baseline Sf/Am ratio was significantly associated with the LVEF ratio (r = 0.469, P = 0.037). The Sf/Am was significantly correlated with the LVEF in overall measurements (n = 40, r = 0.491, P = 0.001). ConclusionsThese results demonstrated that a novel noninvasive pulse waveform index, the Sf/Am measured by multisensor-ABPM is associated with LVEF. The Sf/Am may be useful for estimating cardiac function.

Weak grip strength predicts higher unplanned healthcare utilization among patients with heart failure.

Frailty increases healthcare utilization and costs for patients with heart failure but is challenging to assess in clinical settings. Hand grip strength (GS) is a single-item measure of frailty yet lacks evidence as a potential screening tool to identify patients at risk of higher unplanned events and related healthcare costs. We examined the association of baseline and longitudinal GS measurements with healthcare utilization and costs among patients with advanced heart failure. Between July 2017 and April 2019, we enrolled 251 patients with symptoms of advanced heart failure (New York Heart Association class III or IV) in a prospective cohort study in Singapore. We measured GS at baseline and every 4months for 2years and linked patients' survey data with their medical and billing records. We categorized patients as having weak GS if their GS measurement was below the 5th percentile of the age- and gender-specific normative GS values in Singapore. We assessed the association between baseline GS and healthcare utilization (unplanned and planned events and healthcare costs, total costs, and length of inpatient stay) over the next 2years using regression models. We investigated the association between longitudinal 4-monthly GS assessments and the ensuing 4months of healthcare utilization and costs using mixed-effects logistic and two-part regression models. At baseline, 22.5% of patients had weak GS. Baseline and longitudinal GS measurements were significantly associated with longer length of inpatient stay, greater likelihood of unplanned events, and higher related costs. Patients with weak GS had higher odds of an unplanned event occurring by 8 percentage points [95% confidence interval (CI) (0.01, 0.14), P=0.026], incurred longer inpatient stays by 4days [95% CI (1.97, 6.79), P=0.003], and additional SG$ 4792 [US$~3594, 95% CI (1894, 7689), P=0.014] in unplanned healthcare costs over the next 4months. GS is a simple tool to identify and monitor heart failure patients at risk of unplanned events, longer inpatient stays, and higher related healthcare costs. Findings support its routine use in clinical settings.

BNP and NT-proBNP Thresholds for the Assessment of Prognosis in Patients Without Heart Failure

BackgroundBrain natriuretic peptide (BNP)/N-terminal-pro hormone brain natriuretic peptides (NT-proBNP) enable risk stratification, diagnosing, and monitoring of heart failure patients. An additional prognostic value for BNP/NT-proBNP in nonheart failure patients and general population cohorts is described in the literature, but specific cut-off levels are only described for heart failure patients. ObjectivesThis study aimed to determine thresholds for risk stratification in nonheart failure patients. MethodsBased on the Essen Coronary Artery Disease registry we excluded patients with known heart failure or elevated BNP/NT-pro BNP levels. The resulting cohort was divided into a derivation and validation cohort using random sampling. The prognostic value of BNP/NT-proBNP of incident mortality was evaluated in the derivation cohort using univariate and multivariable cox regression analysis. In receiver operating characteristic analysis and corresponding area under the curve the optimal threshold was determined using Youdens J index. The findings were verified in the validation cohort. ResultsA total of 3,690 patients (age 62.9 ± 12.5 years, 71% male, 68% patients with coronary artery disease) were included. During a mean follow-up of 2.6 ± 3.4 years (median 1.2 [IQR: 0.4-2.88]), 169 deaths of any cause occurred. Based on Youden’s J index, BNP-thresholds of 9.6 and 29pg/ml and NT-proBNP thresholds of 65 and 77pg/ml for men and women, respectively, were determined. BNP/NT-proBNP levels above these thresholds were associated with increased mortality in the derivation cohort (HR: 2.44 [95% CI: 1.32-4.53], P = 0.005). The predictive value was confirmed in the validation cohort (HR: 2.78 [95% CI: 1.26-6.14], P = 0.01). ConclusionsWe here describe sex-specific BNP/NT-proBNP thresholds that allow prediction of impaired survival in patients without heart failure, independent of traditional cardiovascular risk factors.

A-003 Point of Care BNP Values Obtained by the Abbott i-STAT are not Interchangeable With Laboratory Determined Values Using Beckman DXI 800 Analyzer

Abstract Background B-type natriuretic peptide (BNP) is used as a biomarker of heart failure. In our hospital, point of care (POCT) BNP test is performed on whole blood using the i-STAT (Abbott, Abbott Park, IL) while in clinical laboratory, the DXI 800 analyzer is used (Beckman, Brea, CA) for determination of BNP in EDTA plasma. Sometimes clinicians interchangeably use POCT BNP with laboratory BNP test for monitoring heart failure patients, but values are sometimes significantly different causing diagnostic confusion. We compared POCT BNP values in 88 patients with laboratory-based BNP values analyzed between less than one hour to less than 12 h. In addition, 12 specimens were simultaneously analyzed for POCT BNP and lab-based BNP. No additional blood was drawn from patients and medical record was not accessed. The study had exempt status: by the IRB of University of Kansas Medical Center. Methods POCT BNP values were obtained using the i-STAT analyzer following manufacturer’s protocol. It is a two-site enzyme-linked immunosorbent assay (ELISA) with an analytical measurement range of 15–5000 pg/mL. In the laboratory BNP concentrations were obtained using the DXI 800 analyzer. It is also a sandwich immunoassay with the analytical measurement range of 5–5000 pg/mL. Results Overall comparison using lab-based BNP as x-axis and POCT BNP as y-axis produced the following regression equation; y = 1.48 x − 23.45 (n = 88, r = 0.96) indicating that although POCT BNP values correlated well with lab-based BNP values, POCT values showed an average 48% positive bias. When specimens analyzed within 4 h were compared, the regression equation was: y = 1.40 x + 74.12 (n = 20, r = 91) and when specimens analyzed within 1 h were compared, the regression equation was: y = 1.56 + 59.0 (n = 23, r = 0.97). In contrast, when 12 specimens were analyzed simultaneously using POCT and lab-based BNP, using x-axis as the lab-based BNP and y-axis as the POCT BNP, the following regression equation was observed: y = 1.83 x − 102.8 (n = 12, r = 0.99). Conclusion Higher positive bias in specimens analyzed simultaneously indicates true positive bias with POCT BNP compared to lab-based BNP because lab-based BNP in real patients were ordered later after POCT BNP. To our knowledge i-STAT BNP values were never compared with DXI 800 BNP values. We communicated with our clinicians not to use lab-based BNP test and POCT BNP in monitoring patients being treated for heart failure interchangeably. POCT BNP can be used for initial screening to identify potential patients with heart failure.

Telemonitoring patients with chronic heart failure. Results from a pilot study in the Veneto Region, Italy

Remote monitoring of patients with chronic heart failure (HF) can prevent acute episodes of HF, optimize treatment, reduce emergency room (ER) visits and hospitalizations, and improve quality of life of patients and caregivers. In current clinical practice, however, the most appropriate model is still under debate. We aimed to evaluate the impact of a new remote telemonitoring (TM) system in the clinical management of HF patients on the reduction of hospitalizations and ER admissions and on possible related-economic benefits. A working group participated by primary care and family practitioners, cardiologists, home care nurses of the 8th Local Health Unit of the Veneto Region, Italy, has established a new operating procedure for TM chronic HF patients, identifying the clinical profiles and the inclusion/exclusion criteria of enrollment, the clinical parameters to be monitored, the input/output modalities of the information to/from the call center, the alarm criteria and the response procedures. Patients were profiled into three risk categories based on age, clinical characteristics, prognosis assessment, and social needs and provided with appropriate devices for remote measurement and transmission of blood pressure, heart rate, peripheral oxygen saturation (SpO2) and body weight. Clinical data, self-measured at home according to a predetermined schedule based on the patient's risk profile, were automatically transmitted to the operating center, generating, if above the threshold, a grading of alarms (green/cyan, yellow, red) and the consequent activation of the most appropriate response (returned phone calls to check patient's status, reporting to primary physician/family practitioner for clinical evaluation, notification to the HF outpatient clinic for an early follow-up visit, alerting medical emergency services). The number of hospitalizations and ER visits during the TM period was compared with the pre-TM equivalent for each individual patient. Overall, 22 patients with chronic HF were enrolled (mean age 82.3 ± 8.6 years, 17 males). The average duration of TM was 18.7 ± 8.8 months. Overall, 62 108 home measurements were performed and transmitted. The alarms received by the operating center were 4120 (6.6% of all measurements): 62% cyan, 30% yellow, 8% red. Most of the data above the threshold concerned weight gain (42.0%) and SpO2 variations (28.0%). During the observation period (TM period and pre-TM equivalent interval calculated for each individual patient), a total of 127 hospitalizations and 181 ED visits were recorded. Compared to the pre-TM period, there was a 66% reduction in hospitalizations for all causes (95 vs 32, p<0.001) and a 68% decrease in ED visits (137 vs 44, p<0.001). Similarly, hospitalizations and ED visits due to HF were reduced by 82% (p<0.001) and 66% (p<0.001), respectively, with a decrease in days of HF-related hospitalization from 211 to 48. Despite a higher cost for TM of € 6911.15, a total saving of € 64 103.87 was obtained for the reduction of expenses from € 8665.45 to € 2664.00 for ED visits and from € 71 627.93 to € 13 525.51 for HF hospitalizations. This pilot experience on remote monitoring HF patients proved to be effective in determining a significant reduction in ED visits and hospitalizations with a consequent significant economic benefit. Larger studies are needed to confirm this favorable outcome.

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.

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

Real-time pulmonary artery pressure monitoring in heart failure patients: an updated cost-effectiveness analysis.

Previous cost-effectiveness analysis suggests that CardioMEMS is cost-effective compared with usual care for patients with persistent New York Heart Association class III symptoms and at least one heart failure (HF) hospitalization within 12months. The aim of the paper is to perform an update of the cost-effectiveness analysis of CardioMEMS using the most recent data from the published literature. A Microsoft Excel Markov model from a previous UK cost-effectiveness study of CardioMEMS was updated using the clinical effectiveness of pulmonary artery pressure (PAP)-guided treatment derived from the pivotal trials. The model included the device costs (and the implantation procedure and related complications), costs of remote monitoring, costs of HF-related hospitalizations, and costs of usual care. Quality-adjusted life years (QALYs) were estimated based on utilities from pivotal trials and published literature. Cost-effectiveness results were estimated as incremental cost per QALY gained of CardioMEMS compared with usual care. Scenario analyses were also performed using data from real-world studies that showed a significant decrease in HF-related hospitalizations. In the base case analysis over a time horizon of 10years, PAP-guided HF therapy increased cost compared with usual care by £6337 (i.e. from £22770 in usual care to £29107 in PAP-guided HF therapy) and the QALYs per patient for usual care and PAP-guided patients were 2.62 and 2.94, respectively, reflecting an increase of 0.32 QALYs with PAP-guided treatment. The resultant incremental cost-effectiveness ratio (ICER), the ratio between incremental costs and the QALYs, is estimated at £19761/QALY. Scenario analyses suggest that the ICER for CardioMEMS can range from being dominant to £27910/QALY. Probabilistic sensitivity analyses suggested that PAP-guided HF therapy has 81.9% probability of being cost-effective at a threshold of £30000/QALY. Our model suggests that CardioMEMS is likely to be cost-effective in the United Kingdom, at the currently considered thresholds of £20000-30000/QALY.

Breath analysis combined with cardiopulmonary exercise testing and echocardiography for monitoring heart failure patients: the AEOLUS protocol

This paper describes the AEOLUS pilot study which combines breath analysis with cardiopulmonary exercise testing (CPET) and an echocardiographic examination for monitoring heart failure (HF) patients. Ten consecutive patients with a prior clinical diagnosis of HF with reduced left ventricular ejection fraction were prospectively enrolled together with 15 control patients with cardiovascular risk factors, including hypertension, type II diabetes or chronic ischemic heart disease. Breath samples were collected at rest and during CPET coupled with exercise stress echocardiography (CPET-ESE) protocol by means of needle trap micro-extraction and were analyzed through gas-chromatography coupled with mass spectrometry. The protocol also involved using of a selected ion flow tube mass spectrometer for a breath-by-breath isoprene and acetone analysis during exercise. At rest, HF patients showed increased breath levels of acetone and pentane, which are related to altered oxidation of fatty acids and oxidative stress, respectively. A significant positive correlation was observed between acetone and the gold standard biomarker NT-proBNP in plasma (r = 0.646, p < 0.001), both measured at rest. During exercise, some exhaled volatiles (e.g., isoprene) mirrored ventilatory and/or hemodynamic adaptation, whereas others (e.g., sulfide compounds and 3-hydroxy-2-butanone) depended on their origin. At peak effort, acetone levels in HF patients differed significantly from those of the control group, suggesting an altered myocardial and systemic metabolic adaptation to exercise for HF patients. These preliminary data suggest that concomitant acquisition of CPET-ESE and breath analysis is feasible and might provide additional clinical information on the metabolic maladaptation of HF patients to exercise. Such information may refine the identification of patients at higher risk of disease worsening.

Practical Recommendations for the Use of Angiotensin Receptor-Neprilysin Inhibitors (ARNI) in Heart Failure: Insights from Indian Cardiologists.

Heart failure is a significant public health concern characterized by notable rates of morbidity and mortality. Despite the presence of guideline-directed medical therapy (GDMT), its utilization remains inadequate. This practical recommendation paper focuses on the utilization of angiotensin receptor-neprilysin inhibitor (ARNI) as a pivotal treatment for heart failure with reduced ejection fraction (HFrEF), heart failure with preserved ejection fraction (HFpEF), and heart failure with improved ejection fraction (HFimpEF). The recommendations presented in this paper have been developed by a group of cardiologists in India who convened six advisory board meetings to discuss the utilization of ARNI in the management of heart failure. The paper emphasizes the importance of accurate biomarkers for diagnosing heart failure, particularly N-terminal pro-B-type natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP), which are commonly used. Additionally, the paper advocates the use of imaging, specifically echocardiography, in diagnosing and monitoring heart failure patients. Moreover, the paper highlights the role of ARNI in heart failure management, with numerous clinical trials that have demonstrated its effectiveness in reducing cardiovascular death or heart failure hospitalization, enhancing quality of life, and diminishing the risk of ventricular arrhythmias. This practical recommendation paper offers valuable insights into the utilization of ARNI in the management of heart failure, aiming to enhance the implementation of GDMT and ultimately alleviate the burden of heart failure on society.

P340 REMOTE MONITORING IN HEART FAILURE: EFFECTIVE TOOL TO REDUCE HOSPITALIZATIONS AND MORTALITY

Abstract Introduction The prevalence of heart failure in the general population in the idustrialized countries is estimated to be around 2%, a prevalence that increases with age until it reaches 10% at 70 aa of age. The disease is burdened by a high mortality rate and high expense related mainly to repeated hospitalizations. Patients with low ejection fraction heart failure are often implanted with devices, which have the ability to be monitored remotely. The Ministry of Health‘s 2017 annual report on hospitalization activity shows dramatic data: 60% of patients with heart failure are re–hospitalized within one year of discharge and in 14% of cases even within one month of discharge with an annual mortality rate of 18%. The aim of our study is to investigate whether remote monitoring allows improving the outcome of patients with heart failure in terms of reduction of hospitalizations and reduction of all–cause mortality. Materials and Methods In the year 2021, 241 patients with heart failure and reduced ejection fraction, implanted with devices of mean age 73 yr (+/– 11 yr) were remotely monitored in our center; Other population data: see Table 1. On the occasion of transmissions presenting with alarm events, our operational flow chart provides: first telephone contact and possible subsequent outpatient follow–up within 24 h working hours. Results During the year 2021, all–cause mortality in our population was 10.7% (26 patients), while re–hospitalizations were 70 (28.8%). As a result of alarms reported to remote monitoring, 83 patients were contacted whose therapy was changed or device reprogrammed. The causes of alarms were in order: reduced thoracic impedance, arrhythmic events, and reduced biventricular pacing rate. Conclusions The use of remote monitoring in heart failure patients and device wearers allows early and timely diagnosis of clinical changes that anticipate heart failure exacerbation and active intervention by modifying the clinical course, often avoiding hospitalization, with a significant social and economic impact. Thanks to the operational organization of our center, the management of remote monitoring has allowed a low rate of hospitalization and low mortality year compared with literature data.

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

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

Heart failure clinic: the role of nurses

Heart failure is one of the most common cardiovascular conditions with a steadily increasing incidence. Management of such patients only by general practitioners and cardiologists make it impossible to provide high-quality medical care. To ensure multidisciplinary monitoring of heart failure patients in many countries, including Russia, heart failure clinics are actively developing. Specially trained nursing staff play a particular role in the implementation of the clinics’ purposes. Working at Heart Failure Clinic requires advanced training, which in turn determines the priority for the development of new educational programs and expanding the competencies of nursing staff in our country. This article describes the foreign experience of nursing staff in outpatient monitoring of patients with heart failure.

Recent Advances in Remote Pulmonary Artery Pressure Monitoring for Patients with Chronic Heart Failure: Current Evidence and Future Perspectives.

Chronic heart failure (HF) is associated with high hospital admission rates and has an enormous burden on hospital resources worldwide. Ideally, detection of worsening HF in an early phase would allow physicians to intervene timely and proactively in order to prevent HF-related hospitalizations, a concept better known as remote hemodynamic monitoring. After years of research, remote monitoring of pulmonary artery pressures (PAP) has emerged as the most successful technique for ambulatory hemodynamic monitoring in HF patients to date. Currently, the CardioMEMS and Cordella HF systems have been tested for pulmonary artery pressure monitoring and the body of evidence has been growing rapidly over the past years. However, several ongoing studies are aiming to fill the gap in evidence that is still very clinically relevant, especially for the European setting. In this comprehensive review, we provide an overview of all available evidence for PAP monitoring as well as a detailed discussion of currently ongoing studies and future perspectives for this promising technique that is likely to impact HF care worldwide.

68Ga]Ga-NODAGA-E[(cRGDyK)]2 and [64Cu]Cu-DOTATATE PET Predict Improvement in Ischemic Cardiomyopathy.

An increasing number of patients are living with chronic ischemic cardiomyopathy (ICM) and/or heart failure. Treatment options and prognostic tools are lacking for many of these patients. Our aim was to investigate the prognostic value of imaging angiogenesis and macrophage activation via positron emission tomography (PET) in terms of functional improvement after cell therapy. Myocardial infarction was induced in rats. Animals were scanned with [18F]FDG PET and echocardiography after four weeks and randomized to allogeneic adipose tissue-derived stromal cells (ASCs, n = 18) or saline (n = 9). Angiogenesis and macrophage activation were assessed before and after treatment by [68Ga]Ga-RGD and [64Cu]Cu-DOTATATE. There was no overall effect of the treatment. Rats that improved left ventricular ejection fraction (LVEF) had higher uptake of both [68Ga]Ga-RGD and [64Cu]Cu-DOTATATE at follow-up (p = 0.006 and p = 0.008, respectively). The uptake of the two tracers correlated with each other (r = 0.683, p = 0.003 pre-treatment and r = 0.666, p = 0.004 post-treatment). SUVmax at follow-up could predict improvement in LVEF (p = 0.016 for [68Ga]Ga-RGD and p = 0.045 for [64Cu]Cu-DOTATATE). High uptake of [68Ga]Ga-RGD and [64Cu]Cu-DOTATATE PET after injection of ASCs or saline preceded improvement in LVEF. The use of these tracers could improve the monitoring of heart failure patients in treatment.