Pacemaker and ICD Programming Adherence With Evidence-Based Recommendations.

INTRODUCTION

Despite data-driven 2015 expert consensus statement (consensus) guidelines on recommended PPM and ICD parameters, patients often fall short of optimal device programing. The purpose of this retrospective, observational, single-center study is to review device implant registry data both before and after the consensus update to determine whether there is an improvement in adherence to consensus-recommended device programming over time.

METHODS

McKesson software was used to identify all patients pre- (1/1/2012-12/31/2013) and post- (1/1/2020-12/31/2022) consensus who underwent a single, dual, or BiV device implant and had at least one follow-up appointment in the electronic medical record. Groups were evaluated for adherence to consensus recommendations based on the type of device. BiV devices were evaluated based on the percent of total pacing, with > 98% pacing being considered compliant with the consensus. Single and dual-chamber ICDs were evaluated based on bradycardia and tachyarrhythmia programming parameters as outlined in the 2015 consensus document and the 2019 manufacturer-specific update. Due to significant implantation rates at our institution, and to maintain consistency, only Medtronic devices were evaluated in this study.

RESULTS

In the BiV group, before the consensus, 41 (85.4%) patients were > 98% paced, compared with only 69 (58.0%) patients post-consensus. Forty-five (93.7%) patients were at least 90% paced in the pre-consensus group, compared with 109 (91.6%) in the post-consensus group. In the ICD group, bradycardia-pacing settings were similar in both groups (34/89.5% vs. 73/90.1%, p = 0.91). There was a trend toward improved adherence to tachyarrhythmia therapies post-consensus (15/39.5% vs. 37/45.7%, p = 0.52). Nonadherence was driven by 1:1 SVT logic initiation. If this parameter was excluded, both groups increased significantly (37/97.4% vs. 78/96.3%, p = 0.76).

CONCLUSIONS

This study adds to the growing body of literature showing a persistent disconnect between data-driven recommendations and real-world clinical practice. Larger studies are needed to better understand physician barriers to these guideline-driven recommendations.