Malebranche, Daniel; Bartkowiak, Joanna; Ryffel, Christoph; Bernhard, Benedikt; Elsmaan, Mamdouh; Nozica, Nikolas; Okuno, Taishi; Lanz, Jonas; Praz, Fabien; Stortecky, Stefan; Räber, Lorenz; Heg, Dik; Roten, Laurent; Windecker, Stephan; Pilgrim, Thomas; Reichlin, Tobias (2021). Validation of the 2019 Expert Consensus Algorithm for the Management of Conduction Disturbances After TAVR. JACC. Cardiovascular Interventions, 14(9), pp. 981-991. Elsevier 10.1016/j.jcin.2021.03.010
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OBJECTIVES
The aim of this study was to validate the 2019 consensus algorithm in a large cohort of contemporary transcatheter aortic valve replacement (TAVR) patients.
BACKGROUND
The optimal management of patients with atrioventricular conduction disturbances after TAVR is unknown. Guidance was consolidated in an expert consensus algorithm in 2019.
METHODS
In a retrospective analysis of a prospective registry, patients were classified according to the 2019 consensus algorithm as eligible for early discharge (day 1 or 2 after TAVR), higher risk for high-degree atrioventricular block (HAVB) or complete heart block (CHB) or in need for a permanent pacemaker (PPM). The primary endpoint was the incidence of PPM implantation for HAVB or CHB within 30 days after TAVR. Patients with prior PPM or implantable cardioverter-defibrillator implantation, valve-in-valve procedures, or incomplete electrocardiographic data were excluded.
RESULTS
Among 1,439 patients undergoing TAVR between January 2014 and December 2019, the 2019 consensus algorithm classified 73% as eligible for early discharge, 21% as at higher risk for HAVB or CHB, and 6% as in need of PPM. PPM implantation for HAVB or CHB occurred in 234 patients (16%) within 30 days after TAVR. The incidence of PPM implantation was 2.7% in the early discharge group, 41% in the group with higher risk for HAVB or CHB, and 100% in the PPM group.
CONCLUSIONS
The 2019 consensus algorithm safely identifies patients with no need for PPM implantation. This strategy allows more uniform management of TAVR patients and facilitates early discharge of low-risk patients without prolonged monitoring in 3 of 4 patients. However, the algorithm is less precise in the identification of high-risk patients.
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