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Angiographic phenotypes predict FFR/iFR discordance in severe aortic stenosis: A cluster analysis
Artur Dziewierz1, Barbara Zdzierak1, Łukasz Rzeszutko1
12(nd) Department of Cardiology, Institute of Cardiology, Jagiellonian University Medical College, Krakow, Poland; Clinical Department of Cardiology and Cardiovascular Interventions, University Hospital, Krakow, Poland.
Insights
In severe aortic stenosis, high percent diameter stenosis lesions predict FFR/iFR discordance. Unsupervised clustering identified "High %DS / Intermediate Length" lesions as the primary drivers of physiological discordance.
Area of Science:
- Cardiology
- Interventional Cardiology
- Medical Imaging
Background:
- Assessing coronary artery disease in severe aortic stenosis (AS) is challenging due to altered hemodynamics.
- Discordance between fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) is common in AS.
- The role of angiographic lesion characteristics in predicting this discordance is not well understood.
Purpose of the Study:
- To identify angiographic predictors of FFR/iFR discordance in severe AS.
- To define distinct angiographic lesion phenotypes using unsupervised machine learning.
- To understand the impact of lesion characteristics on physiological measurements in AS.
Main Methods:
- Prospective registry of 221 patients with severe AS and 401 intermediate coronary lesions.
- Quantitative coronary angiography to measure percent diameter stenosis (%DS) and lesion length (LL).
- FFR and iFR measurements were performed; K-means clustering analyzed %DS and LL to identify phenotypes.
Main Results:
- FFR/iFR discordance occurred in 7.5% of lesions, exclusively as FFR-negative/iFR-positive.
- Higher %DS was the sole independent angiographic predictor of discordance (OR 1.35).
- Three phenotypes were identified: High %DS/Intermediate LL (16.5% discordance), Low %DS/Short-Intermediate LL (2.7% discordance), and Intermediate %DS/Long LL (9.0% discordance).
Conclusions:
- FFR/iFR discordance in severe AS presents as FFR-negative/iFR-positive.
- "High %DS / Intermediate Length" lesions are the primary drivers of physiological discordance.
- These findings identify cases where iFR may overestimate lesion severity in the context of AS-related hemodynamics.
Background:
Assessing coronary artery disease in severe aortic stenosis (AS) is challenging due to altered hemodynamics, causing discordance between fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR). The role of angiographic lesion characteristics in predicting this discordance remains unclear.
Objectives:
To identify angiographic predictors of FFR/iFR discordance and define distinct angiographic phenotypes using unsupervised machine learning.
Methods:
This prospective, single-center registry evaluated 401 intermediate coronary lesions from 221 patients with severe AS (aortic valve area < 1.0 cm2, mean gradient >40 mmHg) using FFR and iFR. Quantitative coronary angiography measured percent diameter stenosis (%DS), lesion length (LL), and other parameters. The primary outcome was FFR/iFR discordance. Receiver operating characteristic and decision curve analyses evaluated %DS predictive utility. K-means clustering was applied to %DS and LL to identify lesion phenotypes.
Results:
FFR/iFR discordance occurred in 30 lesions (7.5 %), exclusively as FFR-negative/iFR-positive pattern. Higher %DS was the only independent angiographic predictor of discordance (adjusted OR 1.35 per 10 % increase; 95 % CI 1.12-1.64; p = 0.002), with modest discriminative ability (AUC = 0.69). Cluster analysis identified three phenotypes: Cluster 0 (High %DS [median 75.0 %]/Intermediate LL [median 15.0 mm], n = 103); Cluster 1 (Low %DS [median 49.0 %]/Short-Intermediate LL [median 13.6 mm], n = 220); and Cluster 2 (Intermediate %DS [median 63.5 %]/Long LL [median 32.4 mm], n = 78). Discordance incidence was highest in Cluster 0 (16.5 %) versus Clusters 1 (2.7 %) and 2 (9.0 %) (p < 0.001).
Conclusions:
In severe AS, FFR/iFR discordance manifests solely as FFR-negative/iFR-positive pattern. While %DS modestly predicts this mismatch, unsupervised clustering reveals that "High %DS / Intermediate Length" lesions primarily drive physiological discordance, identifying cases where iFR may overestimate severity due to AS-related hemodynamics.
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