Cardiovascular Implantable Electronic Devices -> Diagnostic Devices & Sensors: -> Device Technology D-AB04 - Innovations, Nuances and Critical Questions in CIED Management Therapies (ID 33) Abstract

D-AB04-05 - First-in-Human Study Of A Novel, Wireless Left Atrial Pressure Monitoring System For Patients With Heart Failure: Interim Results From The Vector-HF Trial (ID 730)

Abstract

Background: Non-invasive monitoring has failed to reduce hospitalizations in patients with heart failure (HF). Increased pulmonary artery pressure occurs weeks before a HF hospitalization.
Objective: To assess feasibility of a wireless left-atrial pressure (LAP) monitoring system in a first-in-human study of patients with chronic HF.
Methods: The V-LAP™ system comprises a wireless sensory implant. A home-based belt powers the implant remotely and receives digital data using radiofrequency. The sensor is implanted using an atrial transseptal approach, under angiographic and echocardiographic guidance (Figure). This multicenter, open-label clinical trial assesses the safety and performance of the V-LAP™ system in 30 patients with HF. We present interim results.
Results: The sensor was successfully implanted (age: 67.0 ± 8.63 years [mean ± SD], all NYHA class III) in 9 patients. There were no procedure or device-related related complications. At implantation (total procedure time: 1.21 ± 0.02 hours; sensor deployment time 6-8 minutes; Fig.1a,b) and 3 months after implantation, V-LAP-derived LAP correlated with pulmonary capillary wedge pressure on right heart catheterization (n=14; r=0.87, p<0.001; mean bias: 0.39 mmHg; 95% limits of agreement -6.36 - 7.14) (Fig.1c). Anecdotal findings from 2 patients include detection of a lower LAP after increasing loop diuretic dose and mitral regurgitation (Fig.d,e).
Conclusion: Interim findings suggest that implantation of V-LAP is feasible. There was a good agreement between V-LAP-derived and right heart catherization-derived LAP. Further evidence is needed to determine whether V-LAP can reliably predict HF hospitalizations.
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