Clinical Research Directory

CMR-Based Prognostic Study in Patients With Cardiac Implantable Electronic Devices

Cardiac implantable electronic devices (CIEDs) are widely used to treat patients with heart failure, malignant arrhythmias, and other conditions. However, accurately identifying suitable candidates for CIED implantation remains a clinical challenge. Cardiovascular magnetic resonance imaging (CMR) provides a comprehensive assessment of cardiac structure, function, and tissue characteristics, facilitating evaluation of the myocardial substrate for arrhythmias. This study aims to evaluate the prognostic value of multiparametric CMR-derived imaging markers in CIED patients through preoperative CMR examinations. Imaging parameters of interest include structural-functional indices, myocardial strain, late gadolinium enhancement, entropy, and T1 and T2 mapping. Long-term clinical outcomes will be obtained from existing medical records and follow-up. The primary endpoint is sudden cardiac death (SCD) or SCD-equivalent events, defined as SCD, resuscitated cardiac arrest, sustained ventricular tachycardia or ventricular fibrillation, or appropriate ICD therapy. Secondary endpoints include all-cause mortality or heart failure rehospitalization. This study aims to elucidate the role of CMR in assessing CIED treatment indications and long-term risk stratification, thereby helping to optimize CIED implantation decisions.

Human/Machine Interface: What the HeartMate 3 ® Device Tells Us About the Future

Durable left ventricular assist devices (dLVAD) have been increasingly utilized since the mid to late 1990s, with an uptick of utility starting in 2010 following expanded indications for therapy to not only include a bridge to transplantation strategy, but also for those individuals who suffer from advanced heart failure (HF) and do not qualify for cardiac transplantation. Despite the decreasing size of the newest generation devices leading to a lessened occurrence of adverse events, bleeding and infection still remain a concern for clinicians, as well as a general lack of predictability towards adverse events in individuals with a dLVAD in place. There is a lack of description in the literature currently, regarding the interface between what the pump data provides and what is seen in clinical practice. There also is little known about the effects of what is provided in the pump data, in correlation to quality-of-life following dLVAD implantation. Therefore, the purpose of this study is to prospectively analyze normal and abnormal pump data through pump operations such as suction events, low flow alarms as well as other adventitious alarms, PI events and power cable disconnects greater than 20 seconds, from the HeartMate 3 ® dLVAD in order to clinically correlate this data to quality of life, frailty and other various medical conditions and adverse events as defined by the Interagency Registry for Mechanically Assisted Circulatory Support (Intermacs). This will be achieved through two aims: 1) Evaluate the effectiveness of dLVAD pump operations data on clinical practice application (quality of life, frailty and various medical conditions, and adverse events such as GIB, RHF, infection, hypertension, arrhythmias and stroke); and 2) Evaluate correlations and relationships of longitudinal normal and abnormal dLVAD pump operations data, to demographic and clinical variables. This study is the first study to evaluate HeartMate 3 ® dLVAD pump operations data over time for effectiveness in the clinical practice.

Evaluation of a Single-lead ECG Patch-based Telemetry System for In-hospital Monitoring

"This investigator-initiated, prospective, single-center clinical study evaluates the performance and clinical utility of a single-lead electrocardiogram (ECG) patch-based telemetry system for hospitalized patients who require in-hospital telemetry ECG monitoring. The system integrates real-time centralized surveillance (MEMO-Cue) with post-hoc analytic review (MEMO-Care) using ECG signals recorded by the MEMO Patch M, aiming to enable timely recognition of clinically important arrhythmias and to inform treatment decisions under routine inpatient conditions. Adults (≥19 years) indicated for continuous ECG monitoring during admission are enrolled after written informed consent, with a planned sample size of 100 to yield approximately 90 evaluable participants (10% anticipated dropout). The design does not include randomization or blinding. Study procedures include a screening visit (eligibility and baseline data), an inpatient monitoring period of at least 12 hours and up to 8 days with simultaneous MEMO-Cue monitoring and MEMO Patch M recording, and an end-of-visit assessment when MEMO-Care analytic results become available. Concomitant therapies deemed clinically necessary are permitted and documented, and adverse events are prospectively assessed. Clinical utility endpoints quantify care impact and timeliness: (1) rate of treatment plan changes (e.g., initiation or modification of anticoagulants or antiarrhythmic drugs, cardioversion scheduling, device implantation, or other actions); (2) time to recognition (days) of major arrhythmias-atrial fibrillation (AF), ventricular tachycardia (VT), pause, ventricular premature complex (VPC), and supraventricular tachycardia (SVT)-based on MEMO-Cue alarms or MEMO-Care results with objective confirmation; (3) reduction ratio in recognition time when identified earlier by MEMO-Cue versus MEMO-Care; and (4) proportion of participants with shortened recognition time by MEMO-Cue. Clinical performance endpoints assess detection characteristics and agreement between MEMO-Cue alarms and MEMO-Care findings: (1) clinical sensitivity (true positive / \[true positive + false negative\]); (2) precision, i.e., positive predictive value (true positive / \[true positive + false positive\]); and (3) positive concordance rate (proportion of MEMO-Care-detected arrhythmias alerted by MEMO-Cue). Safety is captured as treatment-emergent adverse events after device application, including device-related skin reactions, detachment, or signal dropouts, with severity graded per NCI-CTCAE v5.0 and relationship to device recorded. By characterizing real-time patch-based telemetry alongside analytic review and its influence on diagnostic timing and management, the study aims to generate practical evidence supporting feasibility, reliability, and workflow compatibility of single-lead patch telemetry for in-hospital ECG monitoring.

Changes in Electrocardiographic (ECG) Ventricular Repolarization and Transthoracic Impedance Cardiography (ICG) Parameters in Patients with COVID-19 and After the Disease: Persistence and Prognostic Significance of These Changes

The aim of this study is to determine the relationship between changes in resting electrocardiography (ECG) ventricular repolarization parameters, transthoracic impedance cardiography (ICG) parameters, and COVID-19, to assess the relationship between ECG changes after COVID-19 and heart rhythm disorders (arrhythmias), cardiovascular events (the onset and exacerbation of cardiovascular diseases), the persistence of changes two years after the illness, and to identify prognostic ventricular repolarization parameters in patients with and after COVID-19. It is expected that the results obtained during the study will help predict long-term cardiovascular complications in these patients, aiming to prevent them by providing recommendations for the long-term monitoring of individuals who have recovered from COVID-19. Additionally, the investigators hope to propose a new ECG ventricular repolarization parameter that could be used in the future for prognostic assessment in patients with other diseases as well.

a Foundational Model for Cardiovascular Disease Diagnosis and Prediction

The goal of this observational study is to develop and evaluate the efficacy of a foundational model that integrates multimodal medical data to improve the diagnosis and prediction of cardiovascular diseases in patients aged 18 and older, including those with various heart conditions such as coronary artery disease, heart failure, and arrhythmias. The main questions it aims to answer are: Can a multimodal data-based diagnostic model match or exceed the accuracy of traditional gold-standard methods like coronary angiography, MRI, and echocardiography? Does integrating different types of data (ECG, imaging, biochemical tests) improve diagnostic accuracy and prediction of cardiovascular disease outcomes? Researchers will compare the foundational model with traditional diagnostic methods to see if the model offers better sensitivity, specificity, and prediction accuracy across different heart disease types. Participants will: Provide data from past medical records, including ECG, echocardiography, cardiac MRI, and biochemical tests. Undergo further data collection if necessary, in line with standard clinical procedures for cardiovascular disease management.