Reclassification of moderate aortic stenosis based on data-driven phenotyping of hemodynamic progression

Iksung Cho, William D. Kim, Subin Kim, Kyu Yong Ko, Yeonchan Seong, Dae Young Kim, Jiwon Seo, Chi Young Shim, Jong Won Ha, Makoto Mori, Aakriti Gupta, Seng Chan You, Geu Ru Hong, Harlan M. Krumholz

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2 Citations (Scopus)

Abstract

The management and follow-up of moderate aortic stenosis (AS) lacks consensus as the progression patterns are not well understood. This study aimed to identify the hemodynamic progression of AS, and associated risk factors and outcomes. We included patients with moderate AS with at least three transthoracic echocardiography (TTE) studies performed between 2010 and 2021. Latent class trajectory modeling was used to classify AS groups with distinctive hemodynamic trajectories, which were determined by serial systolic mean pressure gradient (MPG) measurements. Outcomes were defined as all-cause mortality and aortic valve replacement (AVR). A total of 686 patients with 3093 TTE studies were included in the analysis. Latent class model identified two distinct AS trajectory groups based on their MPG: a slow progression group (44.6%) and a rapid progression group (55.4%). Initial MPG was significantly higher in the rapid progression group (28.2 ± 5.6 mmHg vs. 22.9 ± 2.8 mmHg, P < 0.001). The prevalence of atrial fibrillation was higher in the slow progression group; there was no significant between-group difference in the prevalence of other comorbidities. The rapid progression group had a significantly higher AVR rate (HR 3.4 [2.4–4.8], P < 0.001); there was no between-group difference in mortality (HR 0.7 [0.5–1.0]; P = 0.079). Leveraging longitudinal echocardiographic data, we identified two distinct groups of patients with moderate AS: slow and rapid progression. A higher initial MPG (≥ 24 mmHg) was associated with more rapid progression of AS and higher rates of AVR, thus indicating the predictive value of MPG in management of the disease.

Original languageEnglish
Article number6694
JournalScientific reports
Volume13
Issue number1
DOIs
Publication statusPublished - 2023 Dec

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© 2023, The Author(s).

All Science Journal Classification (ASJC) codes

  • General

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