CorVue algorithm efficacy to predict heart failure in real life: Unnecessary and potentially misleading information?

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

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

Heart Failure Management through Telehealth: Expanding Care and Connecting Hearts

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

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

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

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

Aim

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

Methods

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

Results

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

Conclusion

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

A reproducible sensor pattern to suspect COVID19 pulmonary infection with LATITUDETM . Case report and literature review

A 78 year‐old patient with postischaemic dilated cardiomyopathy and severely reduced ejection fraction was implanted with a Boston Scientific RESONATE X4 CRT‐D and followed by LATITUDE remote monitoring platform. From the end of January to the end of March 2021 he was hospitalized for COVID19 pneumonia followed by two episodes of acute heart decompensation with bilateral pleural effusion. We remotely followed the patient and identified a typical Heart Logic sensor pattern linked to the COVID19 pneumonia, different from the one linked to the heart failure (HF). We eventually made a literature review on the topic.

Remote Monitoring of Heart Failure in Patients with Implantable Cardioverter-Defibrillators: Current Status and Future Needs

The management of heart failure remains challenging despite evidence-based medical and pharmacological advances, especially in the ambulatory setting. There is an urgent need to develop strategies to reduce hospitalizations and readmission rates due to heart failure. Frequent monitoring of high-risk patients is imperative, and with the development of wireless and remote technology, frequent monitoring is now possible via remote monitoring. Nowadays, remote management of patients with cardiac implantable electronic devices is being increasingly adopted and integrated into clinical practice. Several clinical trials studied the impact of remote monitoring on clinical outcomes in patients with implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization defibrillators (CRT-Ds). This point of view will focus on the remote monitoring of ICDs and CRT-Ds in patients with heart failure and discusses whether remote monitoring can be used as a potential instrument for the early identification of patients at risk of worsening heart failure.

Changes in cardiac conduction time following cardiac resynchronization therapy: rationale and design of the RECOVER study

BACKGROUND

It has been known that ventricular conduction delays play a key role in the cardiac resynchronization therapy (CRT) response of patients with advanced heart failure (HF). However, no study to our knowledge has yet evaluated the serial changes in conduction times measured between different electrodes of CRT devices.

METHODS AND RESULTS

The Reduction or Extension of Conduction Time with Ventricular Electromechanical Remodeling (RECOVER) study (NCT04397224) was designed to investigate serial changes in interelectrode conduction times and to elucidate their prognostic value. We plan to enroll 100 patients implanted with CRT systems with endocardial quadripolar left ventricular leads. Patients will be scheduled for follow-up every 3 months over a period of 2 years, where they will undergo measurement of interelectrode conduction times to evaluate their serial changes. The primary outcome of the RECOVER study is the correlation between the degree of conduction time changes and the CRT response as defined by echocardiography. The time course and prognostic value of the serial changes in conduction times will be investigated as well.

CONCLUSION

The RECOVER study is investigating whether serial changes in interelectrode conduction times can be useful parameters in predicting the CRT response or detecting worsening HF at an early stage.

Clinical utility of CorVue intrathoracic impedance alert with device-measured physical activity in predicting heart failure events

Cardiac implantable electronic devices (CIEDs) offer heart failure (HF) diagnostic information, including intrathoracic impedance (ITI) or physical activity (PA). However, few studies have evaluated the utility of these parameters measured by CIEDs with CorVue algorithm. The purpose of this study was to investigate the relationship between ITI alerts triggered by the CorVue algorithm and HF development. We also examined the association between device-measured PA and ITI alerts associated with HF development. We retrospectively studied consecutive patients with CIEDs equipped with CorVue algorithm, which were implanted between June 1, 2011 and August 31, 2019. These patients were divided into two groups: patients with decreased ITI followed by the ITI alerts (ITI alert group) and those without the alerts (non-ITI alert group). There were 35 and 14 patients in the ITI and non-ITI alert groups, respectively. A total of 96 ITI alerts were observed. ITI alerts associated with HF development were observed in 21% (20/96); whereas, ITI alerts not associated with HF development were observed in 79% (76/96). Accurate device-measured PA was confirmed in 76 ITI alerts, which consisted of 30 alerts with lower PA and 46 alerts without lower PA. ITI alerts associated with HF development were observed in 30% (9/30) of the alerts with lower PA, whereas observed only in 6.5% (3/46) of the alerts without lower PA. In conclusion, the CorVue ITI alerts indicated a high false-positive rate. However, device-measured PA may be useful to determine whether ITI alerts are associated with HF development or not, which was attributed to the high negative predictive value.

Early Detection of Fluid Retention in Patients with Advanced Heart Failure: A Review of a Novel Multisensory Algorithm, HeartLogicTM

Heart failure (HF) hospitalisations due to decompensation are associated with shorter life expectancy and lower quality of life. These hospitalisations pose a significant burden on the patients, doctors and healthcare resources. Early detection of an upcoming episode of decompensation may facilitate timely optimisation of the ambulatory medical treatment and thereby prevent heart-failure-related hospitalisations. The HeartLogic^TM algorithm combines data from five sensors of cardiac implantable electronic devices into a cumulative index value. It has been developed for early detection of fluid retention in heart failure patients. This review aims to provide an overview of the current literature and experience with the HeartLogic^TM algorithm, illustrate how the index can be implemented in daily clinical practice and discuss ongoing studies and potential future developments of interest.

A Steep Increase in the HeartLogic Index Predicts COVID-19 Disease in an Advanced Heart Failure Patient

We present a patient with severe nonischemic cardiomyopathy in whom the HeartLogic algorithm was activated on her Boston Scientific cardioverter defibrillator. She had an out-of-alert state for several months and had clinically “stable” heart failure with no hospitalizations in the last 6 months. A sudden and fast increase of the HeartLogic index preceded her presentation in the emergency ward by several days. The detailed readout of HeartLogic however had some atypical features for heart failure decompensation. The patient presented at the emergency department with an increased dyspnea and a dry cough. Clinical exam showed desaturation and was suggestive for an acute respiratory infection. Subsequent imaging with CT thorax and nasopharyngeal real-time polymerase chain reaction (RT-PCR) confirmed SARS-CoV-2 viral pneumonia (COVID-19). This case illustrates that a timely and detailed analysis of HeartLogic alerts could help in the early differentiation of disease in patients with severe heart failure.