Bridging The Ep & Hf Gap: A Dual Aprn Model Can Optimize Post-crt Management.

Abstract

<h3>Introduction</h3> Subspecialty management of heart failure (HF) patients after cardiac resynchronization therapy (CRT) is often inharmonious, leading to limited medical and device therapy optimization. <h3>Hypothesis</h3> We hypothesized that a novel, dual advanced practice registered nurse (APRN) subspecialty care model would allow for device optimization, medical therapy titration, and identification of end-stage heart failure patients. <h3>Methods</h3> We designed a multidisciplinary clinic to assess patients six months post CRT implantation. That team consisted of an APRN from our heart failure team, an APRN from our electrophysiology team, and a HF nurse. Patients underwent device interrogation, 12-lead electrocardiogram, transthoracic echocardiogram, six-minute walk test, and completed a Minnesota Living with Heart Failure Questionnaire. Both APRNs simultaneously evaluated the patient and developed a unified plan of care which included device reprogramming to achieve greater than 98% CRT pacing, medical therapy titration, and referral to the advanced heart failure program. Pre and post device implantation characteristics were summarized with descriptive statistics. A CRT responder was defined as a 5% or greater improvement in ejection fraction with 10% or greater decrease in left ventricular end-systolic volume. <h3>Results</h3> Thirty-three consecutive patients were seen in the clinic from September 2020 to April 2021. Three were excluded from this analysis due to missing data. Mean age was 68 years; 23 (77%) were male; 26 (87%) were Caucasian and 4 (13%) were African American. Sixteen (53%) had ischemic cardiomyopathy. Twelve patients (40%) were CRT responders at six months. Nine patients (30%) underwent device programming modifications and 11 (37%) had medications titrated on this visit. One patient (3%) was referred for advanced therapies. <h3>Conclusions</h3> A dual APRN model of post-CRT HF patients can be an effective clinical workflow to optimize medical and device-based therapies.