Telemonitoring in patients with heart failure

Prediction of heart failure events based on physiologic sensor data in HINODE defibrillator patients

AIMS

Hospitalizations are common in patients with heart failure and are associated with high mortality, readmission and economic burden. Detecting early signs of worsening heart failure may enable earlier intervention and reduce hospitalizations. The HeartLogic algorithm is designed to predict worsening heart failure using diagnostic data from multiple device sensors. The main objective of this analysis was to evaluate the sensitivity of the HeartLogic alert calculation in predicting worsening heart failure events (HFEs). We also evaluated the false positive alert rate (FPR) and compared the incidence of HFEs occurring in a HeartLogic alert state to those occurring out of an alert state.

METHODS

The HINODE study enrolled 144 patients (81 ICD and 63 CRT-D) with device sensor data transmitted via a remote monitoring system. HeartLogic alerts were then retrospectively simulated using relevant sensor data. Clinicians and patients were blinded to calculated alerts. Reported adverse events with HF symptoms were adjudicated and classified by an independent HFE committee. Sensitivity was defined as the ratio of the number of detected usable HFEs (true positives) to the total number of usable HFEs. A false positive alert was defined as an alert with no usable HFE between the alert onset date and the alert recovery date plus 30 days. The patient follow-up period was categorized as in alert state or out of alert state. The event rate ratio was the HFE rate calculated in alert to out of alert.

RESULTS

The patient cohort was 79% male and had an average age of 68 ± 12 years. This analysis yielded 244 years of follow-up data with 73 HFEs from 37 patients. A total of 311 HeartLogic alerts at the nominal threshold (16) occurred across 106 patients providing an alert rate of 1.27 alerts per patient-year. The HFE rate was 8.4 times greater while in alert compared with out of alert (1.09 vs. 0.13 events per patient-year; P < 0.001). At the nominal alert threshold, 80.8% of HFEs were detected by a HeartLogic alert [95% confidence interval (CI): 69.9%-89.1%]. The median time from first true positive alert to an adjudicated clinical HFE was 53 days. The FPR was 1.16 (95% CI: 0.98-1.38) alerts per patient-year.

CONCLUSIONS

Results suggest that signs of worsening HF can be detected successfully with remote patient follow-up. The use of HeartLogic may predict periods of increased risk for HF or clinically significant events, allowing for early intervention and reduction of hospitalization in a vulnerable patient population.

The War Against Heart Failure Hospitalizations: Remote Monitoring and the Case for Expanding Criteria

Successful remote patient monitoring depends on bidirectional interaction between patients and multidisciplinary clinical teams. Invasive pulmonary artery pressure monitoring has been shown to reduce heart failure (HF) hospitalizations, facilitate guideline-directed medical therapy optimization, and improve quality of life. Cardiac implantable electronic device-based multiparameter monitoring has shown encouraging results in predicting future HF-related events. Potential expanded indications for remote monitoring include guideline-directed medical therapy optimization, application to specific populations, and subclinical detection of HF. Voice analysis, inferior vena cava diameter monitoring, and artificial intelligence-based remote electrocardiogram show potential to gain some merit in remote patient monitoring in HF.

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

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

Which heart failure patients benefit most from non-invasive telemedicine? An overview of current evidence and future directions

Telemedicine in heart failure (HF) management may positively impact health outcomes, but varied effects in studies hinder guidance in HF guidelines. Evidence on the effectiveness of telemedicine in HF subpopulations is limited. We conducted a scoping review to evaluate and synthesise evidence on the effectiveness of telemedicine across HF subpopulations that could guide telemedicine strategies in routine practice. Meta-analyses concerning randomised controlled trials (RCTs) with subgroup analyses on telemedicine effectives were identified in PubMed. We identified 15 RCTs, encompassing 21 different subgroups based on characteristics of HF patients. Findings varied across studies and no definite evidence was found about which patients benefit most from telemedicine. Subgroup definitions were inconsistent, not always a priori defined and subgroups contained few patients. Some studies found heterogeneous effects of telemedicine on mortality and hospitalisation across subgroups defined by: New York Heart Association (NYHA) classification, previous HF decompensation, implantable device, concurrent depression, time since hospital discharge and duration of HF. Patients represented in the RCTs were mostly male, aged 65-75 years, with HF with reduced ejection fraction and NYHA class II/III. Traditional RCTs have not been able to provide clinicians with guidance; continuous real-world evidence generation could enhance monitoring and identify who benefits from telemedicine.

The rise of Telecardiology in developing countries

Telecardiology, the remote diagnosis and treatment of cardiac conditions, is experiencing a significant increase in developing nations. This article explores the driving forces behind this trend and its implications. Limited access to healthcare facilities, especially in rural, isolated, and underdeveloped regions, has propelled the adoption of telecardiology as a cost-effective solution to bridge the gap in cardiac care provision. Technological advancements, such as portable diagnostic devices and improvements in telecommunication infrastructure, have facilitated the expansion of telecardiology services. Moreover, the COVID-19 pandemic has accelerated the acceptance and deployment of telehealth solutions worldwide. Nevertheless, challenges persist, including regulatory hurdles, data privacy concerns, and disparities in digital literacy. Despite these obstacles, the rise of telecardiology in developing countries presents a promising opportunity to enhance access to cardiac care and improve health outcomes among underserved populations.

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

OBJECTIVES

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.

MATERIALS AND METHODS

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.

RESULTS

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.

DISCUSSION AND CONCLUSION

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.

Telehealth-aided outpatient management of acute heart failure in a specialist virtual ward compared with standard care

AIMS

The aim of this propensity score matched cohort study was to assess the outcomes of telehealth-guided outpatient management of acute heart failure (HF) in our virtual ward (HFVW) compared with hospitalized acute HF patients.

METHODS AND RESULTS

This cohort study (May 2022-October 2023) assessed outcomes of telehealth-guided outpatient acute HF management using bolus intravenous furosemide in a HF-specialist VW. Propensity score matching (PSM) was performed using logistic regression to adjust for potential differences in baseline patient characteristics between HFVW and standard care [Get With The Guidelines-HF score, clinical frailty score (CFS), Charlson co-morbidity index (CCI), NT-proBNP, and ejection fraction]. Clinical outcomes (re-hospitalizations and mortality) were compared at 1, 3, 6, and 12 months versus standard care-SC (acute HF patients managed without telehealth in 2021). Five hundred fifty-four HFVW ADHF patients (age 73.1 ± 10.9 years; 46% female) were compared with 404 ADHF patients (74.2 ± 11.8; P = 0.15 and 49% female) in the standard care-SC cohort. After propensity score matching for baseline patient characteristics, re-hospitalizations were significantly lower in the HFVW compared with SC (1 month-HFVW 8.6% vs. SC-21.5%, P < 0.001; 3 months-21% vs. 30%, P = 0.003; 6 months-28% vs 41%, P < 0.001 and 12 months-47% vs. 57%, P = 0.005) and mortality was also lower at 1 month (5% vs. 13.7%; P < 0.001), 3 months (9.5% vs. 15%; P = 0.001), 6 months (15% vs. 21%; P = 0.03), and 12 months (20% vs. 26%; P = 0.04). Multivariate logistic regression analysis showed that compared with standard care, HFVW management was associated with lower odds of readmission (1-month odds ratio (OR) = 0.3 [95% Confidence Interval CI 0.2-0.5], P < 0.0001; 3 month OR = 0.15 [0.1-0.3], P < 0.0001; 6-month OR = 0.35 [0.2-0.6], P = 0.0002; 12-month OR = 0.25 [0.15-0.4], P ≤ 0.001 and mortality (1-month OR = 0.26 [0.14-0.48], P < 0.0001; 3-month OR = 0.11 [0.04-0.27], P < 0.0001; 6-month OR = 0.35, [0.2; 0.61], P = 0.0002; 12-month OR = 0.6 [0.48; 0.73], P = 0.03. Higher GWTG-HF score independently predicted increased odds of re-hospitalization (1-month OR = 1.2 [1.1-1.3], P < 0.001; 3-month OR = 1.5 [1.37; 1.64], P < 0.0001; 6-month OR = 1.3 [1.2-1.4], P < 0.0001; 12-month OR = 1.1 [1.05-1.2], P = 0.03) as well as mortality (1-month OR = 1.21 [1.1-1.3], P < 0.0001; 3-month OR = 1.3 [1.2-1.4], P < 0.0001; 6-month OR = 1.2 [1.1-1.3], P < 0.0001; 12-month OR = 1.3 [1.1-1.7], P = 0.02). Similarly higher CFS also independently predicted increased odds of re-hospitalizations (1-month OR = 1.9 [1.5-2.4], P < 0.0001; 3-month OR = 1.8 [1.3-2.4], P = 0.0003; 6-month OR = 1.4 [1.1-1.8], P = 0.015; 12-month OR 1.9 [1.2-3], P = 0.01]) and mortality (1-month OR = 2.1 [1.6-2.8], P < 0.0001; 3-month OR = 1.8 [1.2-2.6], P = 0.006; 6-month OR = 2.34 [1.51-5.6], P = 0.0001; 12-month OR = 2.6 [1.6-7], P = 0.02). Increased daily step count while on HFVW independently predicted reduced odds of re-hospitalizations (1-month OR = 0.85[0.7-0.9], P = 0.005), 3-month OR = 0.95 [0.93-0.98], P = 0.003 and 1-month mortality (OR = 0.85 [0.7-0.95], P = 0.01), whereas CCI predicted adverse 12-month outcomes (OR = 1.2 [1.1-1.4], P = 0.03).

CONCLUSIONS

Telehealth-guided specialist HFVW management for ADHF may offer a safe and efficacious alternative to hospitalization in suitable patients. Daily step count in HFVW can help predict risk of short-term adverse clinical outcomes.

Clinical Utility of Machine Learning-Derived Vocal Biomarkers in the Management of Heart Failure

Background

This study aimed to systematically evaluate voice symptoms during heart failure (HF) treatments and to exploratorily extract HF-related vocal biomarkers.

Methods and Results

This single-center, prospective study longitudinally acquired 839 audio files from 59 patients with acute decompensated HF. Patients' voices were analyzed along with conventional HF indicators (New York Heart Association [NYHA] class, presence of pulmonary congestion and pleural effusion on chest X-ray, and B-type natriuretic peptide [BNP]) and GOKAN scores based on the assessment of a cardiologist. Machine-learning (ML) models to estimate HF conditions were created using a Light Gradient Boosting Machine. Voice analysis identified 27 acoustic features that correlated with conventional HF indicators and GOKAN scores. When creating ML models based on the acoustic features, there was a significant correlation between actual and ML-derived BNP levels (r=0.49; P<0.001). ML models also identified good diagnostic accuracies in determining HF conditions characterized by NYHA class ≥2, BNP ≥300 pg/mL, presence of pulmonary congestion or pleural effusion on chest X-ray, and decompensated HF (defined as NYHA class ≥2 and BNP levels ≥300 pg/mL; accuracy: 75.1%, 69.1%, 68.7%, 66.4%, and 80.4%, respectively).

Conclusions

The present study successfully extracted HF-related acoustic features that correlated with conventional HF indicators. Although the data are preliminary, ML models based on acoustic features (vocal biomarkers) have the potential to infer various HF conditions, which warrant future studies.

Serial cardiac biomarkers, pulmonary artery pressures and traditional parameters of fluid status in relation to prognosis in patients with chronic heart failure: Design and rationale of the BioMEMS study

AIMS

Heart failure (HF), a global pandemic affecting millions of individuals, calls for adequate predictive guidance for improved therapy. Congestion, a key factor in HF-related hospitalizations, further underscores the need for timely interventions. Proactive monitoring of intracardiac pressures, guided by pulmonary artery (PA) pressure, offers opportunities for efficient early-stage intervention, since haemodynamic congestion precedes clinical symptoms.

METHODS

The BioMEMS study, a substudy of the MONITOR-HF trial, proposes a multifaceted approach integrating blood biobank data with traditional and novel HF parameters. Two additional blood samples from 340 active participants in the MONITOR-HF trial were collected at baseline, 3-, 6-, and 12-month visits and stored for the BioMEMS biobank. The main aims are to identify the relationship between temporal biomarker patterns and PA pressures derived from the CardioMEMS-HF system, and to identify the biomarker profile(s) associated with the risk of HF events and cardiovascular death.

CONCLUSION

Since the prognostic value of single baseline measurements of biomarkers like N-terminal pro-B-type natriuretic peptide is limited, with the BioMEMS study we advocate a dynamic, serial approach to better capture HF progression. We will substantiate this by relating repeated biomarker measurements to PA pressures. This design rationale presents a comprehensive review on cardiac biomarkers in HF, and aims to contribute valuable insights into personalized HF therapy and patient risk assessment, advancing our ability to address the evolving nature of HF effectively.

A Quality Improvement-based Approach to Implementing a Remote Monitoring-Based Bundle in Transitional Care Patients for Heart Failure

BACKGROUND

Congestive heart failure (HF) is a leading cause of hospitalization and readmission, leading to increased health care utilization and cost. This is complicated by high incidence, prevalence, and hospitalization rates among racial and ethnic minorities, with a widening in the mortality disparity gap. Remote patient monitoring (RPM) has the potential to proactively engage patients after discharge to optimize medication management and intervene to avoid rehospitalization. However, it also may widen the equity gap due to technological barriers and bias.

METHODS

A prospective, observational quality improvement (QI) initiative leveraging an amended tool from the Institute for Healthcare Improvement Model for Improvement was incorporated with an equity lens and five Plan-Do-Study-Act (PDSA) cycles at a single site. The intervention used an HF bundle that included RPM, clinical telepharmacy, remote therapeutic monitoring, and community paramedicine.

RESULTS

Between May 2022 and March 2023, five PDSA cycles were run involving 90 enrolled patients. In total, 38 (42.2%) patients received the complete HF bundle, 42 (46.7%) a partial bundle, and 10 (11.1%) only RPM. The patients with the complete bundle had a readmission rate of 2.6% compared to 14.3% in the partial bundle and 20.0% in RPM alone. The biggest impact of this program was the incorporation of community paramedicine. The program also noted an improvement in equitable enrollment after adjusting mid-program by avoiding cellular phone-enabled devices and transitioning to a hub-based model.

CONCLUSION

This single-site QI-based initiative implemented an HF-based RPM program that leveraged clinical telepharmacy and community paramedicine. This program identified a disparity of care gap regarding the equitable distribution of services and made mid-study adjustments to improve the disparity gap. The program found that use of the HF bundle resulted in a decreased hospital readmission rate.

Personalized care in dilated cardiomyopathy: Rationale and study design of the activeDCM trial

BACKGROUND

Dilated cardiomyopathy (DCM) is a leading cause of heart failure, particularly in younger individuals. Low physical strength is a global risk factor for cardiovascular mortality, and physical activity and a healthy lifestyle have been shown to improve outcomes in patients with heart failure. However, inappropriate exercise may increase the risk of arrhythmias in certain individuals with DCM. The determinants for predicting individual risks in this setting are poorly understood, and clinicians are hesitant to recommend sports for cardiomyopathy patients. The activeDCM trial aims to assess the safety and efficacy of a personalized exercise and activity programme for individuals with DCM.

STUDY DESIGN

The activeDCM trial is a prospective, randomized, interventional trial with a 12 month follow-up. Three hundred patients, aged 18-75 years with DCM, left ventricular ejection fraction (LVEF) ≤ 50% and New York Heart Association (NYHA) classes I-III, will be enrolled. The intervention includes a personalized exercise and activity programme. The primary outcome is the increase in peak oxygen uptake (VO2max, mL/kg/min) from baseline to 12 months. Secondary endpoints include adherence to personalized activity programmes, freedom from clinically relevant arrhythmia, unplanned hospitalization for heart failure and changes in NYHA class, quality of life scores, 6 min walk distance, muscular strength, N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity troponin T (hsTnT) levels and cardiac function. Advanced research questions include high-density phenome and omics analysis combined with digital biomarkers derived from Apple Watch devices.

DISCUSSION

The activeDCM trial will provide valuable insights into the safety and efficacy of personalized exercise training in DCM patients, inform clinical practice and contribute to the development of heart failure management programmes. The study will generate data on the impact of exercise on various aspects of cardiovascular disease, including genetic, metabolic, phenotypic and longitudinal aspects, facilitating the development of future digital tools and strategies, including the incorporation of smart wearable devices.

Randomised pilot study comparing a coach to SMARTPhone reminders to aid the management of heart failure (HF) patients: humans or machines

Ambulatory management of congestive heart failure (HF) continues to be a challenging clinical problem. Recent studies have focused on the role of HF clinics, nurse practitioners and disease management programmes to reduce HF readmissions. This pilot study is a pragmatic factorial study comparing a coach intervention, a SMARTPHONE REMINDER system intervention and BOTH interventions combined to Treatment as USUAL (TAU). We determined that both modalities were acceptable to patients prior to randomisation. Fifty-four patients were randomised to the four groups. The COACH group had no readmissions for HF 6 months after enrolment compared with 18% for the SMARTPHONE REMINDER Group, 8% for the BOTH intervention group and 13% for TAU. Medium-to-high medication adherence was maintained in all four groups although sodium consumption was lower at 3 months for the COACH and combined (BOTH) groups. This pilot study suggests a beneficial effect on rehospitalisation with the use of support measures including coaches and telephone reminders that needs confirmation in a larger trial.

Effectiveness of remote pulmonary artery pressure estimating in heart failure: systematic review and meta-analysis

Heart failure (HF) poses a significant challenge, often leading to frequent hospitalizations and compromised quality of life. Continuous pulmonary artery pressure (PAP) monitoring offers a surrogate for congestion status in ambulatory HF care. This meta-analysis examines the efficacy of PAP monitoring devices (CardioMEMS and Chronicle) in preventing adverse outcomes in HF patients, addressing gaps in prior randomized controlled trials (RCTs). Five RCTs (2572 participants) were systematically reviewed. PAP monitoring significantly reduced HF-related hospitalizations (RR 0.72 [95% CI 0.6-0.87], p = 0.0006) and HF events (RR 0.86 [95% CI 0.75-0.99], p = 0.03), with no impact on all-cause or cardiovascular mortality. Subgroup analyses highlighted the significance of CardioMEMS and blinded studies. Meta-regression indicated a correlation between prolonged follow-up and increased reduction in HF hospitalizations. The risk of bias was generally high, with evidence certainty ranging from low to moderate. PAP monitoring devices exhibit promise in diminishing HF hospitalizations and events, especially in CardioMEMS and blinded studies. However, their influence on mortality remains inconclusive. Further research, considering diverse patient populations and intervention strategies with extended follow-up, is crucial for elucidating the optimal role of PAP monitoring in HF management.

Implementation of an epicardial implantable MEMS sensor for continuous and real-time postoperative assessment of left ventricular activity in adult minipigs over a short- and long-term period

The sensing of left ventricular (LV) activity is fundamental in the diagnosis and monitoring of cardiovascular health in high-risk patients after cardiac surgery to achieve better short- and long-term outcome. Conventional approaches rely on noninvasive measurements even if, in the latest years, invasive microelectromechanical systems (MEMS) sensors have emerged as a valuable approach for precise and continuous monitoring of cardiac activity. The main challenges in designing cardiac MEMS sensors are represented by miniaturization, biocompatibility, and long-term stability. Here, we present a MEMS piezoresistive cardiac sensor capable of continuous monitoring of LV activity over time following epicardial implantation with a pericardial patch graft in adult minipigs. In acute and chronic scenarios, the sensor was able to compute heart rate with a root mean square error lower than 2 BPM. Early after up to 1 month of implantation, the device was able to record the heart activity during the most important phases of the cardiac cycle (systole and diastole peaks). The sensor signal waveform, in addition, closely reflected the typical waveforms of pressure signal obtained via intraventricular catheters, offering a safer alternative to heart catheterization. Furthermore, histological analysis of the LV implantation site following sensor retrieval revealed no evidence of myocardial fibrosis. Our results suggest that the epicardial LV implantation of an MEMS sensor is a suitable and reliable approach for direct continuous monitoring of cardiac activity. This work envisions the use of this sensor as a cardiac sensing device in closed-loop applications for patients undergoing heart surgery.

Evaluation of Ambient Sensor Systems for the Early Detection of Heart Failure Decompensation in Older Patients Living at Home Alone: Protocol for a Prospective Cohort Study

BACKGROUND

The results of telemedicine intervention studies in patients with heart failure (HF) to reduce rehospitalization rate and mortality by early detection of HF decompensation are encouraging. However, the benefits are lower than expected. A possible reason for this could be the fact that vital signs, including blood pressure, heart rate, heart rhythm, and weight changes, may not be ideal indicators of the early stages of HF decompensation but are more sensitive for acute events triggered by ischemic episodes or rhythm disturbances. Preliminary results indicate a potential role of ambient sensor-derived digital biomarkers in this setting.

OBJECTIVE

The aim of this study is to identify changes in ambient sensor system-derived digital biomarkers with a high potential for early detection of HF decompensation.

METHODS

This is a prospective interventional cohort study. A total of 24 consecutive patients with HF aged 70 years and older, living alone, and hospitalized for HF decompensation will be included. Physical activity in the apartment and toilet visits are quantified using a commercially available, passive, infrared motion sensing system (DomoHealth SA). Heart rate, respiration rate, and toss-and-turns in bed are recorded by using a commercially available Emfit QS device (Emfit Ltd), which is a contact-free piezoelectric sensor placed under the participant's mattress. Sensor data are visualized on a dedicated dashboard for easy monitoring by health professionals. Digital biomarkers are evaluated for predefined signs of HF decompensation, including particularly decreased physical activity; time spent in bed; increasing numbers of toilet visits at night; and increasing heart rate, respiration rate, and motion in bed at night. When predefined changes in digital biomarkers occur, patients will be called in for clinical evaluation, and N-terminal pro b-type natriuretic peptide measurement (an increase of >30% considered as significant) will be performed. The sensitivity and specificity of the different biomarkers and their combinations for the detection of HF decompensation will be calculated.

RESULTS

The study is in the data collection phase. Study recruitment started in February 2024. Data analysis is scheduled to start after all data are collected. As of manuscript submission, 5 patients have been recruited. Results are expected to be published by the end of 2025.

CONCLUSIONS

The results of this study will add to the current knowledge about opportunities for telemedicine to monitor older patients with HF living at home alone by evaluating the potential of ambient sensor systems for this purpose. Timely recognition of HF decompensation could enable proactive management, potentially reducing health care costs associated with preventable emergency presentations or hospitalizations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06126848; https://clinicaltrials.gov/study/NCT06126848.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/55953.

Intervention effects of telenursing based on M-O-A model in empty-nest older adult individuals with chronic diseases: a randomized controlled trial

Aim

This study aims to verify the effectiveness of M-O-A telenursing intervention model in improving the health status and quality of life of the empty-nest older adult individuals with chronic diseases by a randomized comparative trial.

Methods

M-O-A telenursing intervention model was constructed based on the needs of the participants. The control group (N = 39) received routine nursing, the experimental group (N = 39) received M-O-A telenursing intervention in addition to routine nursing. After 12 weeks of intervention, the intervention effects of being a participant in the two groups were evaluated. SPSS 26.0 was used for data analysis.

Results

After 12 weeks of intervention, for the experimental group, each dimension of quality of life based on EQ-5D-3L became better, especially for "pain/discomfort," "anxiety/depression," "HRQoL" and "EQ-VAS" (all p < 0.05) and each dimension of quality of life based on SF-36 became better too, especially for "GH," "BP," "RE," "MH," "VT," "SF," "PCS," "MCS," "SF-36" (all p < 0.05). In addition, there was a statistical downward trend in blood pressure, blood glucose, weight, BMI, fat rate, nap duration, number of nocturnal awakenings, light sleep rate and a statistical upward trend in water rate, basal metabolic rate, nighttime sleep duration, deep sleep rate, rapid eye movement sleep rate, especially at the end of intervention (all p < 0.05). While for the control group, there was no statistical improvement in all these aspects.

Conclusion

The M-O-A telenursing model could effectively regulate quality of life and health condition of the empty-nest older adult individuals with chronic diseases, making it worthy of further promotion and application.

Implementation of remote monitoring strategies to improve chronic heart failure management

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Telemedicine and patients with heart failure: evidence and unresolved issues

BACKGROUND

Heart failure is the leading cause of cardiac-related hospitalizations. Limited access to reevaluations and outpatient appointments restricts the application of modern therapies. Telemedicine has become an essential resource in the healthcare system because of its countless benefits, such as higher and more frequent appointments and faster titration of medications. This narrative review aimed to demonstrate the evidence and unresolved issues related to the use of telemedicine in patients with heart failure. No studies have examined heart failure prevention; however, several studies have addressed the prevention of decompensation with positive results. Telemedicine can be used to evaluate all patients with heart failure, and many telemedicine platforms are available. Several strategies, including both noninvasive (phone calls, weight measurement, and virtual visits) and invasive (implantable pulmonary artery catheters) strategies can be implemented. Given these benefits, telemedicine is highly desirable, particularly for vulnerable groups. Although some questions remain unanswered, the development of new technologies can complement remote visits and improve patient care.

Mapping trends and hotspots regarding the use of telenursing for elderly individuals with chronic diseases: A bibliometric analysis

BACKGROUND

Telenursing is receiving extensive attention from scholars and medical staff. However, there are few studies on the knowledge structure of telenursing for elderly individuals with chronic diseases. This study aims to demonstrate current research status and development trend of telenursing for elderly individuals with chronic diseases through a visual analysis of CiteSpace, so as to provide a more comprehensive perspective for future researches.

METHODS

Literature about telenursing for elderly patients with chronic diseases from 2002 to 2022 was retrieved from the Web of Science Core Collection using CiteSpace 6.1.R3.

RESULTS

A total of 375 records were obtained. Annual publication and citation frequency gradually increased over the investigated period, reaching a peak in 2022. Journal of Telemedicine and Telecare was the most prolific and the most cited journal. The United States was the most productive country, the University of Melbourne was the most productive institution, and the author CHEN C ranked the highest in the number of publications. The most popular keywords were "care," "telemedicine," "management," "older adult," "chronic disease," "health," and "heart failure," which had a high frequency and centrality. The keywords "telehealth," "randomized controlled trail," "chronic obstructive pulmonary disease," "implementation" and "time" showed the strongest citation burst. The keywords were clustered to form 10 labels. The article published in 2010 by Chaudhry SI was cited the most. The top 3 cited journals were all special journal of telemedicine.

CONCLUSION

This study revealed current research status and development trend of telenursing for elderly individuals with chronic diseases. The bibliometric analysis of telenursing expands the knowledge field of telemedicine and provides new insights into the management of elderly patients with chronic diseases.

Systems of care for ambulatory management of decompensated heart failure

Heart failure (HF) represents a worldwide health burden and the annual per patient cost to treat HF in the US is estimated at $24,383, with most of this expense driven by HF related hospitalizations. Decompensated HF is a leading cause for hospital admissions and is associated with an increased risk of subsequent morbidity and mortality. Many hospital admissions for decompensated HF are considered preventable with timely recognition and effective intervention.Systems of care that include interventions to facilitate early recognition, timely and appropriate intervention, intensification of care, and optimization to prevent recurrence can help successfully manage decompensated HF in the ambulatory setting and avoid hospitalization.

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

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

Prognostic impact of acute decompensated heart failure in patients with heart failure with mildly reduced ejection fraction

AIMS

This study sought to determine the prognostic impact of acute decompensated heart failure (ADHF) in patients with heart failure with mildly reduced ejection fraction (HFmrEF). ADHF is a major complication in patients with heart failure (HF). However, the prognostic impact of ADHF in patients with HFmrEF has not yet been clarified.

METHODS AND RESULTS

Consecutive patients hospitalized with HFmrEF (i.e. left ventricular ejection fraction 41-49% and signs and/or symptoms of HF) were retrospectively included at one institution from 2016 to 2022. The prognosis of patients with ADHF was compared with those without (i.e. non-ADHF). The primary endpoint was long-term all-cause mortality. Secondary endpoints included in-hospital all-cause mortality and long-term HF-related re-hospitalization. Kaplan-Meier, multivariable Cox proportional regression, and propensity score matched analyses were performed for statistics. Long-term follow-up was set at 30 months. A total of 2184 patients with HFmrEF were included, ADHF was present in 22%. The primary endpoint was higher in ADHF compared to non-ADHF patients with HFmrEF [50% vs. 26%; hazard ratio (HR) = 2.269; 95% confidence interval (CI) 1.939-2.656; P = 0.001]. Accordingly, the secondary endpoint of long-term HF-related re-hospitalization was significantly higher (27% vs. 10%; HR = 3.250; 95% CI 2.565-4.118; P = 0.001). A history of previous ADHF before the index hospitalization was associated with higher rates of long-term HF-related re-hospitalization (42% vs. 23%; HR = 2.073; 95% CI 1.420-3.027; P = 0.001), but not with long-term all-cause mortality (P = 0.264).

CONCLUSION

ADHF is a common finding in patients with HFmrEF associated with an adverse impact on long-term prognosis.

Remote management in patients with heart failure (from new onset to advanced): A practical guide

Heart failure is a chronic condition that affects millions of people worldwide and is associated with high morbidity and mortality. Remote monitoring, which includes the use of non-invasive connected devices, cardiac implantable electronic devices and haemodynamic monitoring systems, has the potential to improve outcomes for patients with heart failure. Despite the conceptual and clinical advantages, there are still limitations in the widespread use of these technologies. Moreover, a significant proportion of studies evaluating the benefit of remote monitoring in heart failure have focused on the limited area of prevention of rehospitalization after an episode of acute heart failure. A group of experts in the fields of heart failure and digital health worked on this topic in order to provide a practical paper for the use of remote monitoring in clinical practice at the different stages of the heart failure syndrome: (1) discovery of heart failure; (2) acute decompensation of chronic heart failure; (3) heart failure in stable period; and (4) advanced heart failure. A careful and critical analysis of the available literature was performed with the aim of providing caregivers with some recommendations on when and how to use remote monitoring in these different situations, specifying which variables are essential, optional or useless.

Telemedical management in patients waiting for transcatheter aortic valve implantation: the ResKriVer-TAVI study design

Aims

The majority of patients with severe aortic stenosis (AS) planned for transcatheter aortic valve implantation (TAVI) are elective outpatients. During the COVID-19 pandemic, the time between the heart team's decision and TAVI increased due to limited healthcare resources. We therefore implemented telemedical approaches to identify AS patients at risk for clinical deterioration during the waiting time. The purpose of the prospective, randomized, controlled ResKriVer-TAVI study (DRKS00027842) is to investigate whether a digital concept of telemedical interventional management (TIM) in AS patients waiting for TAVI improves the clinical outcomes. In the present article, we report the study protocol of the ResKriVer-TAVI trial.

Methods

ResKriVer-TAVI will enroll AS patients planned for elective TAVI. Randomization to the TIM group or standard care will be made on the day of the heart team's decision. TIM will include a daily assessment of weight, blood pressure, a 2-channel electrocardiogram, peripheral capillary oxygen saturation, and a self-rated health status until admission for TAVI. TIM will allow optimization of medical therapy or an earlier admission for TAVI if needed. Standard care will not include any additional support for patients with AS. All patients of the TIM group will receive a rule-based TIM including standard operating procedures when a patient is crossing prespecified values of a vital sign.

Results

The primary endpoint consists of days lost due to cardiovascular hospitalization and death of any cause within 180 days after the heart team's decision. Major secondary endpoints include all-cause mortality within 365 days, the number of telemedical interventions, and adherence to TIM. Follow-up visits will be conducted at admission for TAVI as well as 6 and 12 months after the heart team's decision.

Conclusions

ResKriVer-TAVI will be the first randomized, controlled trial investigating a telemedical approach before TAVI in patients with AS. We hypothesize that primary and secondary endpoints of AS patients with TIM will be superior to standard care. The study will serve to establish TIM in the clinical routine and to increase the resilience of TAVI centers in situations with limited healthcare resources.

Post-hospitalization remote monitoring for patients with heart failure or chronic obstructive pulmonary disease in an accountable care organization

BACKGROUND

Post-hospitalization remote patient monitoring (RPM) has potential to improve health outcomes for high-risk patients with chronic medical conditions. The purpose of this study is to determine the extent to which RPM for patients with congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD) is associated with reductions in post-hospitalization mortality, hospital readmission, and ED visits within an Accountable Care Organization (ACO).

METHODS

Nonrandomized prospective study of patients in an ACO offered enrollment in RPM upon hospital discharge between February 2021 and December 2021. RPM comprised of vital sign monitoring equipment (blood pressure monitor, scale, pulse oximeter), tablet device with symptom tracking software and educational material, and nurse-provided oversight and triage. Expected enrollment was for at least 30-days of monitoring, and outcomes were followed for 6 months following enrollment. The co-primary outcomes were (a) the composite of death, hospital admission, or emergency care visit within 180 days of eligibility, and (b) time to occurrence of this composite. Secondary outcomes were each component individually, the composite of death or hospital admission, and outpatient office visits. Adjusted analyses involved doubly robust estimation to address confounding by indication.

RESULTS

Of 361 patients offered remote monitoring (251 with CHF and 110 with COPD), 140 elected to enroll (106 with CHF and 34 with COPD). The median duration of RPM-enrollment was 54 days (IQR 34-85). Neither the 6-month frequency of the co-primary composite outcome (59% vs 66%, FDR p-value = 0.47) nor the time to this composite (median 29 vs 38 days, FDR p-value = 0.60) differed between the groups, but 6-month mortality was lower in the RPM group (6.4% vs 17%, FDR p-value = 0.02). After adjustment for confounders, RPM enrollment was associated with nonsignificantly decreased odds for the composite outcome (adjusted OR [aOR] 0.68, 99% CI 0.25-1.34, FDR p-value 0.30) and lower 6-month mortality (aOR 0.41, 99% CI 0.00-0.86, FDR p-value 0.20).

CONCLUSIONS

RPM enrollment may be associated with improved health outcomes, including 6-month mortality, for selected patient populations.

RELEASE-HF study: a protocol for an observational, registry-based study on the effectiveness of telemedicine in heart failure in the Netherlands

INTRODUCTION

Meta-analyses show postive effects of telemedicine in heart failure (HF) management on hospitalisation, mortality and costs. However, these effects are heterogeneous due to variation in the included HF population, the telemedicine components and the quality of the comparator usual care. Still, telemedicine is gaining acceptance in HF management. The current nationwide study aims to identify (1) in which subgroup(s) of patients with HF telemedicine is (cost-)effective and (2) which components of telemedicine are most (cost-)effective.

METHODS AND ANALYSIS

The RELEASE-HF ('REsponsible roLl-out of E-heAlth through Systematic Evaluation - Heart Failure') study is a multicentre, observational, registry-based cohort study that plans to enrol 6480 patients with HF using data from the HF registry facilitated by the Netherlands Heart Registration. Collected data include patient characteristics, treatment information and clinical outcomes, and are measured at HF diagnosis and at 6 and 12 months afterwards. The components of telemedicine are described at the hospital level based on closed-ended interviews with clinicians and at the patient level based on additional data extracted from electronic health records and telemedicine-generated data. The costs of telemedicine are calculated using registration data and interviews with clinicians and finance department staff. To overcome missing data, additional national databases will be linked to the HF registry if feasible. Heterogeneity of the effects of offering telemedicine compared with not offering on days alive without unplanned hospitalisations in 1 year is assessed across predefined patient characteristics using exploratory stratified analyses. The effects of telemedicine components are assessed by fitting separate models for component contrasts.

ETHICS AND DISSEMINATION

The study has been approved by the Medical Ethics Committee 2021 of the University Medical Center Utrecht (the Netherlands). Results will be published in peer-reviewed journals and presented at (inter)national conferences. Effective telemedicine scenarios will be proposed among hospitals throughout the country and abroad, if applicable and feasible.

TRIAL REGISTRATION NUMBER

NCT05654961.

Remote Monitoring Devices and Heart Failure

Remote patient monitoring (RPM) in patients with heart failure (HF) involves transmitting physiological data from devices to a health-care provider via a wireless connection with targeted interventions when values exceed the preset threshold. Devices used in telemonitoring range from weighing scales, blood pressure cuffs, and pulse oximeters to devices used to measure cardiac filling pressure and intrathoracic impedance using cardiac implantable electronic devices and wearables. Accordingly, RPM devices can potentially engage patients in their cardiovascular care and reduce the burden of HF in society.

New technologies for the diagnosis, treatment, and monitoring of cardiovascular diseases

Telemedicine enables the remote provision of medical care through information and communication technologies, facilitating data transmission, patient participation, promotion of heart-healthy habits, diagnosis, early detection of acute decompensation, and monitoring and follow-up of cardiovascular diseases. Wearable devices have multiple clinical applications, ranging from arrhythmia detection to remote monitoring of chronic diseases and risk factors. Integrating these technologies safely and effectively into routine clinical practice will require a multidisciplinary approach. Technological advances and data management will increase telemonitoring strategies, which will allow greater accessibility and equity, as well as more efficient and accurate patient care. However, there are still unresolved issues, such as identifying the most appropriate technological infrastructure, integrating these data into medical records, and addressing the digital divide, which can hamper patients' adoption of remote care. This article provides an updated overview of digital tools for a more comprehensive approach to atrial fibrillation, heart failure, risk factors, and treatment adherence.

Home telemonitoring in heart failure patients and the effect of study design on outcome: A literature review

INTRODUCTION

A wide range of study designs have been utilized in evaluations of home telemonitoring and these studies have produced conflicting outcomes over the years. While some of the research has shown that telemonitoring is beneficial in reducing all-cause mortality, hospital admission, length of stay in hospital and emergency room visits, other studies have not shown such benefits. This study, therefore, aims to examine several home telemonitoring study designs and the influence of study design on study outcomes.

METHOD

Articles were obtained by searching PubMed database with the term heart failure combined with the following terms: telemonitoring, telehealth, home monitoring, and remote monitoring. Searches were limited to randomized controlled trial conducted between year January 1, 2000 and February 6, 2021. The characteristics of the study designs and study outcomes were extracted and analyzed.

RESULT

Our review of 34 randomized controlled trials of heart failure telemonitoring did not show any significant influence of study design on reduction in number of hospitalizations and/or decrease in mortality. Studies that were done outside North America (USA and Canada) and studies that selected patients at high risk of re-hospitalization were more likely to result in decreased hospitalization and/or mortality, though this was not statistically significant. All the studies that met our inclusion criteria were from high-income countries and only one study enrolled patients at high risk of re-hospitalization.

CONCLUSION

There is a need for more studies to understand why telemonitoring studies in Europe were more likely to reduce hospital admission and mortality compared to those in North America. There is also a need for more studies on the effect of telemonitoring in patients at high risk of hospital readmission.

Prognostic value of signs and symptoms in heart failure patients using remote telemonitoring

INTRODUCTION

Heart failure is a serious burden on health care systems due to frequent hospital admissions. Early recognition of outpatients at risk for clinical deterioration could prevent hospitalization. Still, the role of signs and symptoms in monitoring heart failure patients is not clear. The heart failure coach is a web-based telemonitoring application consisting of a 9-item questionnaire assessment of heart failure signs and symptoms and developed to identify outpatients at risk for clinical deterioration. If deterioration was suspected, patients were contacted by a heart failure nurse for further evaluation.

METHODS

Heart failure coach questionnaires completed between 2015 and 2018 were collected from 287 patients, completing 18,176 questionnaires. Adverse events were defined as all-cause mortality, heart failure- or cardiac-related hospital admission or emergency cardiac care visits within 30 days after completion of each questionnaire. Multilevel logistic regression analyses were performed to assess the association between the heart failure coach questionnaire items and the odds of an adverse event.

RESULTS

No association between dyspnea and adverse events was observed (odds ratio 1.02, 95% confidence interval 0.79-1.30). Peripheral edema (odds ratio 2.21, 95% confidence interval 1.58-3.11), persistent chest pain (odds 2.06, 95% confidence interval 1.19-3.58), anxiety about heart failure (odds ratio 2.12, 95% confidence interval 1.44-3.13), and extensive struggle to perform daily activities (odds ratio 2.23, 95% confidence interval 1.38-3.62) were significantly associated with adverse outcome.

DISCUSSION

Regular assessment of more than the classical signs and symptoms may be helpful to identify heart failure patients at risk for clinical deterioration and should be an integrated part of heart failure telemonitoring programs.

New models for heart failure care delivery

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

Association Between Participation in a Heart Failure Telemonitoring Program and Health Care Utilization and Death Within an Integrated Health Care Delivery System

BACKGROUND

The clinical usefulness of remote telemonitoring to reduce postdischarge health care use and death in adults with heart failure (HF) remains controversial.

METHODS AND RESULTS

Within a large integrated health care delivery system, we matched patients enrolled in a postdischarge telemonitoring intervention from 2015 to 2019 to patients not receiving telemonitoring at up to a 1:4 ratio on age, sex, and calipers of a propensity score. Primary outcomes were readmissions for worsening HF and all-cause death within 30, 90, and 365 days of the index discharge; secondary outcomes were all-cause readmissions and any outpatient diuretic dose adjustments. We matched 726 patients receiving telemonitoring to 1985 controls not receiving telemonitoring, with a mean age of 75 ± 11 years and 45% female. Patients receiving telemonitoring did not have a significant reduction in worsening HF hospitalizations (adjusted rate ratio [aRR] 0.95, 95% confidence interval [CI] 0.68-1.33), all-cause death (adjusted hazard ratio 0.60, 95% CI 0.33-1.08), or all-cause hospitalization (aRR 0.82, 95% CI 0.65-1.05) at 30 days, but did have an increase in outpatient diuretic dose adjustments (aRR 1.84, 95% CI 1.44-2.36). All associations were similar at 90 and 365 days postdischarge.

CONCLUSIONS

A postdischarge HF telemonitoring intervention was associated with more diuretic dose adjustments but was not significantly associated with HF-related morbidity and mortality.

The War Against Heart Failure Hospitalizations: Remote Monitoring and the Case for Expanding Criteria

Successful remote patient monitoring depends on bidirectional interaction between patients and multidisciplinary clinical teams. Invasive pulmonary artery pressure monitoring has been shown to reduce heart failure (HF) hospitalizations, facilitate guideline-directed medical therapy optimization, and improve quality of life. Cardiac implantable electronic device-based multiparameter monitoring has shown encouraging results in predicting future HF-related events. Potential expanded indications for remote monitoring include guideline-directed medical therapy optimization, application to specific populations, and subclinical detection of HF. Voice analysis, inferior vena cava diameter monitoring, and artificial intelligence-based remote electrocardiogram show potential to gain some merit in remote patient monitoring in HF.

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

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

Combined telemonitoring and telecoaching for heart failure improves outcome

Telemedicine has been shown to improve the outcome of heart failure (HF) patients in addition to medical and device therapy. We investigate the effectiveness of a comprehensive telehealth programme in patients with recent hospitalisation for HF on subsequent HF hospitalisations and mortality compared to usual care in a real-world setting. The telehealth programme consists of daily remote telemonitoring of HF signs/symptoms and regular individualised telecoaching sessions. Between January 2018 and September 2020, 119,715 patients of a German health insurer were hospitalised for HF and were eligible for participation in the programme. Finally, 6065 HF patients at high risk for re-hospitalisation were enroled. Participants were retrospectively compared to a propensity score matched usual care group (n = 6065). Median follow-up was 442 days (IQR 309-681). Data from the health insurer was used to evaluate outcomes. After one year, the number of hospitalisations for HF (17.9 vs. 21.8 per 100 patient years, p < 0.001), all-cause hospitalisations (129.0 vs. 133.2 per 100 patient years, p = 0.015), and the respective days spent in hospital (2.0 vs. 2.6 days per year, p < 0.001, and 12.0 vs. 13.4, p < 0.001, respectively) were significantly lower in the telehealth than in the usual care group. Moreover, participation in the telehealth programme was related to a significant reduction in all-cause mortality compared to usual care (5.8 vs. 11.0 %, p < 0.001). In a real-life setting of ambulatory HF patients at high risk for re-hospitalisation, participation in a comprehensive telehealth programme was related to a reduction of HF hospitalisations and all-cause mortality compared to usual care.

Trends and frontiers of research on telemedicine from 1971 to 2022: A scientometric and visualisation analysis

BACKGROUND

With the continuous development of the Internet and information technology, telemedicine has gradually become a popular medical model, which has always attracted much attention. Especially in recent years, research has shown a rapid increase in the use of telemedicine due to the impact of COVID-19. We have conducted a scientific metrological analysis of telemedicine to identify its hot spots and frontiers and promote cooperation and development.

METHODS

We retrieved 19,171 articles related to telemedicine published from 1971 to 2022 in the Web of Science (WOS) database. Then, we conducted co-author network analysis (author, institution, country), co-citation analysis (author, journal, literature) and burst analysis (thematic trends and frontier topics).

RESULTS

The number of publications has been on the rise since 1993 and began to rise rapidly in 1997. Influenced by the COVID-19 pandemic, the number of articles doubled in 2020 compared to the prior year. The United States produced the greatest number of articles (43.4%). Although studies in Greece are fewer and more recent, the country is demonstrating tremendous development potential in this field and is an active contributor to telemedicine research. The main research topics identified include the application, system and services of telemedicine; the application of telemedicine in providing medical services to rural and remote areas where medical resources are scarce; the quality control of medical images in telemedicine; the application of telemedicine in chronic disease care; and the comparison of in-person medical care and telemedicine. Emerging topics include the application and impact of telemedicine during the COVID-19 pandemic.

CONCLUSION

The main telemedicine research fields over the past 52 years are identified, the meanings of analyses results are discussed, and emerging trends are highlighted.

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

ABSTRACT

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Telemedicine: an Effective and Low-Cost Lesson From the COVID-19 Pandemic for the Management of Heart Failure Patients

PURPOSE

The purpose of this review is to explore the benefits and controversies that telemedicine (TM), applied to patients with heart failure (HF), can provide in terms of diagnosis, therapeutic management, and prognosis improvement. During the coronavirus disease 19 (COVID-19) outbreak, TM emerged as the most effective and feasible method available to ensure continuous care for chronic diseases. Among these, HF, characterized by high mortality, morbidity, and the need for frequent visits, may benefit of the TM role. HF patients are affected by frequent exacerbations undergoing a progressive prognosis impoverishment, strongly depending on the disease's management. A precise clinical handling is always required, with a constant optimization of the therapy, a continuous control of risk factors, and a sensitive attention to any change in symptoms, clinical signs, and laboratory tests. In this context, TM has shown to improve therapy adherence and HF: patients' self-care, impacting the prognosis even if specific results are controversial. Major evidence shows that TM may allow an adequate primary prevention, reducing the impact of the main cardiovascular risk factors. TM can also be useful for the secondary prevention, early detecting a likely HF exacerbation before it becomes clinically manifest, thereby lowering the need for hospitalization. Moreover, an optimal up-titration of the therapy and an increase in treatment adherence are feasible by using TM. However, some studies did not show unambiguous results, and uncertainties still remain.

In-silico enhanced animal study of pulmonary artery pressure sensors: assessing hemodynamics using computational fluid dynamics

To assess whether in-silico models can be used to predict the risk of thrombus formation in pulmonary artery pressure sensors (PAPS), a chronic animal study using pigs was conducted. Computed tomography (CT) data was acquired before and immediately after implantation, as well as one and three months after the implantation. Devices were implanted into 10 pigs, each one in the left and right pulmonary artery (PA), to reduce the required number of animal experiments. The implantation procedure aimed at facilitating optimal and non-optimal positioning of the devices to increase chances of thrombus formation. Eight devices were positioned non-optimally. Three devices were positioned in the main PA instead of the left and right PA. Pre-interventional PA geometries were reconstructed from the respective CT images, and the devices were virtually implanted at the exact sites and orientations indicated by the follow-up CT after one month. Transient intra-arterial hemodynamics were calculated using computational fluid dynamics. Volume flow rates were modelled specifically matching the animals body weights. Wall shear stresses (WSS) and oscillatory shear indices (OSI) before and after device implantation were compared. Simulations revealed no relevant changes in any investigated hemodynamic parameters due to device implantation. Even in cases, where devices were implanted in a non-optimal manner, no marked differences in hemodynamic parameters compared to devices implanted in an optimal position were found. Before implantation time and surface-averaged WSS was 2.35 ± 0.47  Pa, whereas OSI was 0.08 ± 0.17 , respectively. Areas affected by low WSS magnitudes were 2.5 ± 2.7  cm2 , whereas the areas affected by high OSI were 18.1 ± 6.3  cm2 . After device implantation, WSS and OSI were 2.45 ± 0.49  Pa and 0.08 ± 0.16 , respectively. Surface areas affected by low WSS and high OSI were 2.9 ± 2.7  cm2 , and 18.4 ± 6.1  cm2 , respectively. This in-silico study indicates that no clinically relevant differences in intra-arterial hemodynamics are occurring after device implantation, even at non-optimal positioning of the sensor. Simultaneously, no embolic events were observed, suggesting that the risk for thrombus formation after device implantation is low and independent of the sensor position.

Remote patient management of heart failure across the ejection fraction spectrum: A pre-specified analysis of the TIM-HF2 trial

AIMS

The benefit of non-invasive remote patient management (RPM) for patients with heart failure (HF) has been demonstrated. We evaluated the effect of left ventricular ejection fraction (LVEF) on treatment outcomes in the TIM-HF2 (Telemedical Interventional Management in Heart Failure II; NCT01878630) randomized trial.

METHODS AND RESULTS

TIM-HF2 was a prospective, randomized, multicentre trial investigating the effect of a structured RPM intervention versus usual care in patients who had been hospitalized for HF within 12 months before randomization. The primary endpoint was the percentage of days lost due to all-cause death or unplanned cardiovascular hospitalization. Key secondary endpoints were all-cause and cardiovascular mortality. Outcomes were assessed by LVEF in guideline-defined subgroups of ≤40% (HF with reduced EF [HFrEF]), 41-49% (HF with mildly reduced EF [HFmrEF]), and ≥50% (HF with preserved EF [HFpEF]). Out of 1538 participants, 818 (53%) had HFrEF, 224 (15%) had HFmrEF, and 496 (32%) had HFpEF. Within each LVEF subgroup, the primary endpoint was lower in the treatment group, i.e. the incidence rate ratio [IRR] remained below 1.0. Comparing intervention and control group, the percentage of days lost was 5.4% versus 7.6% for HFrEF (IRR 0.72, 95% confidence interval [CI] 0.54-0.97), 3.3% versus 5.9% for HFmrEF (IRR 0.85, 95% CI 0.48-1.50) and 4.7% versus 5.4% for HFpEF (IRR 0.93, 95% CI 0.64-1.36). No interaction between LVEF and the randomized group became apparent. All-cause and cardiovascular mortality were also reduced by RPM in each subgroup with hazard ratios <1.0 across the LVEF spectrum for both endpoints.

CONCLUSION

In the clinical set-up deployed in the TIM-HF2 trial, RPM appeared effective irrespective of the LVEF-based HF phenotype.

[Telemonitoring of patients with chronic respiratory failure in France]

The year 2023 is marked by the officialization in French law of medical telemonitoring. Adult patients suffering from severe chronic respiratory failure (CRF) and being treated non-invasive ventilation (NIV) and/or oxygen therapy in a home setting are eligible for telemonitoring, of which the costs are to be covered by French health insurance. Telemonitoring allows a medical professional to remotely interpret the data necessary for follow-up and, if necessary, to make decisions regarding management of a given patient. Its objectives are, at the very least, to stabilize the disease through appropriate monitoring, to improve efficiency and quality of care, and to improve that patient's quality of life. The objective of this synthesis is to review the current state of remote monitoring of CRF patients by identifying, through a narrative analysis of the literature, its current benefits and limitations, and to compare present-day telemonitoring with the guidelines of the official French health authority (Haute Autorité de santé) for its nationwide application.

Digital Transformation in the Diagnostics and Therapy of Cardiovascular Diseases: Comprehensive Literature Review

BACKGROUND

The digital transformation of our health care system has experienced a clear shift in the last few years due to political, medical, and technical innovations and reorganization. In particular, the cardiovascular field has undergone a significant change, with new broad perspectives in terms of optimized treatment strategies for patients nowadays.

OBJECTIVE

After a short historical introduction, this comprehensive literature review aimed to provide a detailed overview of the scientific evidence regarding digitalization in the diagnostics and therapy of cardiovascular diseases (CVDs).

METHODS

We performed an extensive literature search of the PubMed database and included all related articles that were published as of March 2022. Of the 3021 studies identified, 1639 (54.25%) studies were selected for a structured analysis and presentation (original articles: n=1273, 77.67%; reviews or comments: n=366, 22.33%). In addition to studies on CVDs in general, 829 studies could be assigned to a specific CVD with a diagnostic and therapeutic approach. For data presentation, all 829 publications were grouped into 6 categories of CVDs.

RESULTS

Evidence-based innovations in the cardiovascular field cover a wide medical spectrum, starting from the diagnosis of congenital heart diseases or arrhythmias and overoptimized workflows in the emergency care setting of acute myocardial infarction to telemedical care for patients having chronic diseases such as heart failure, coronary artery disease, or hypertension. The use of smartphones and wearables as well as the integration of artificial intelligence provides important tools for location-independent medical care and the prevention of adverse events.

CONCLUSIONS

Digital transformation has opened up multiple new perspectives in the cardiovascular field, with rapidly expanding scientific evidence. Beyond important improvements in terms of patient care, these innovations are also capable of reducing costs for our health care system. In the next few years, digital transformation will continue to revolutionize the field of cardiovascular medicine and broaden our medical and scientific horizons.

Telemonitoring for heart failure: a meta-analysis

AIMS

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

METHODS AND RESULTS

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

CONCLUSION

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

Optimizing outcomes in heart failure: 2022 and beyond

Although the development of therapies and tools for the improved management of heart failure (HF) continues apace, day-to-day management in clinical practice is often far from ideal. A Cardiovascular Round Table workshop was convened by the European Society of Cardiology (ESC) to identify barriers to the optimal implementation of therapies and guidelines and to consider mitigation strategies to improve patient outcomes in the future. Key challenges identified included the complexity of HF itself and its treatment, financial constraints and the perception of HF treatments as costly, failure to meet the needs of patients, suboptimal outpatient management, and the fragmented nature of healthcare systems. It was discussed that ongoing initiatives may help to address some of these barriers, such as changes incorporated into the 2021 ESC HF guideline, ESC Heart Failure Association quality indicators, quality improvement registries (e.g. EuroHeart), new ESC guidelines for patients, and the universal definition of HF. Additional priority action points discussed to promote further improvements included revised definitions of HF 'phenotypes' based on trial data, the development of implementation strategies, improved affordability, greater regulator/payer involvement, increased patient education, further development of patient-reported outcomes, better incorporation of guidelines into primary care systems, and targeted education for primary care practitioners. Finally, it was concluded that overarching changes are needed to improve current HF care models, such as the development of a standardized pathway, with a common adaptable digital backbone, decision-making support, and data integration, to ensure that the model 'learns' as the management of HF continues to evolve.