Management of Postprocedural Conduction Disturbances Using a Prespecified Algorithm in the Optimize PRO Study. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Lack of standardization in posttranscatheter aortic valve replacement (TAVR) conduction disturbance (CD) identification and treatment may affect permanent pacemaker implantation (PPI) rates and clinical outcomes. The safety and efficacy of a standardized TAVR CD algorithm has not been analyzed. This study analyzes the Optimize PRO post-TAVR CD management algorithm with Evolut PRO/PRO+ valves. METHODS: Optimize PRO is a prospective, postmarket study implementing 2 strategies to reduce pacemaker rates: TAVR with cusp overlap technique and a post-TAVR CD algorithm. The 2-hour postprocedural electrocardiogram (ECG) stratified patients to early discharge in the absence of new ECG changes or to CD algorithms for (1) ECG changes with preexisting right or left bundle branch block (LBBB), interventricular conduction delay or first-degree atrioventricular block, (2) new LBBB, or (3) high-degree atrioventricular block (HAVB). RESULTS: The interim analysis of the CD cohort consisted of 125/400 TAVR recipients. In the CD cohort, the 30-day new PPI rate was higher (28.1% vs 1.5%; P <.001), and 60 (48%) patients were discharged with a 30-day continuous ECG monitor. At 30 days, 90% of patients discharged with a monitor did not require PPI. Clinical outcomes, including mortality, stroke, bleeding, and reintervention, were similar in patients with and without CDs. No patient experienced sudden cardiac death. CONCLUSIONS: Effective management of CDs using a standard algorithm following Evolut TAVR provides similar 30-day safety outcomes to patients without CDs who undergo routine next day discharge. The CD algorithm may provide an effective strategy to recognize arrhythmias early, improve PPI utilization, and facilitate safe monitoring of patients after discharge.

publication date

  • November 3, 2023

Identity

PubMed Central ID

  • PMC11307950

Scopus Document Identifier

  • 85177073043

Digital Object Identifier (DOI)

  • 10.1016/j.jscai.2023.101066

PubMed ID

  • 39131970

Additional Document Info

volume

  • 3

issue

  • 1