Computed tomography derived FFR and plaque features in prognosis of aortic stenosis combined with coronary artery disease after TAVR

To assess the value of computed tomography angiography (CTA)-derived fractional flow reserve (CT-FFR) and high-risk plaque characteristics (HRPC) in the prediction of prognosis in patients with concomitant aortic stenosis (AS) and coronary artery disease (CAD) after transcatheter aortic valve replacement (TAVR). The study was a post hoc analysis from a multicenter TAVR registry. Patients with AS and obstructive CAD who underwent successful TAVR treatment were enrolled. The CT-FFR and HRPC were measured in coronary vessels with ≥ 50% stenosis lesions. The patients were then grouped according to CT-FFR (≤ 0.8 vs. >0.8) and HRPC (Yes vs. No) criteria. The primary outcome was major adverse cardiovascular events (MACE), a composite of cardiac death, nonfatal myocardial infarction, and ischemia-driven revascularization. The multivariable Cox proportional regression was used to identify independent predictors of MACE. To assess the combined prognostic value of CT-FFR and HRPC to OPT-CAD risk, receiver operating characteristic curves were used and the area under the curve (AUC) was determined. A total of 213 patients were enrolled. The mean age was 74.34 years and 125 (58.4%) were male. The patients with lower CT-FFR (≤ 0.8) had a higher rate of MACE compared with those with CT-FFR > 0.8 (11.9% vs. 2.3%, P = 0.011). However, there was no significant difference in MACE incidence (9.0% vs. 5.3%, P = 0.38) between patients with and without HRPC, respectively. The Cox regression model revealed that advanced age (hazard ratio [HR] 1.07, 95% confidence interval [CI] 1.003-1.15, P = 0.04), elevated NT-proBNP levels (HR 1.004, 95% CI 1.00-1.01, P = 0.046), and higher CT-FFR (HR 0.78, 95% CI 0.62-0.97, P = 0.03) were independent predictors of MACE. The optimal threshold value for predicting MACE using CT-FFR was determined to be 0.79. The performance in predicting MACE using the OPT-CAD score model was enhanced when both CT-FFR and HRPC were incorporated into the model [AUC 0.63 (0.49-0.76) vs. 0.74 (0.63-0.84), P = 0.04]. Pre-procedure CT-FFR was an independent predictor of MACE in patients with concomitant AS and CAD after TAVR.

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Journal
Scientific Reports
Published
2025-09-01
DOI
https://doi.org/10.1038/s41598-025-17951-w
Primary Topic
Cardiac Valve Diseases and Treatments
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article
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article

Computed tomography derived FFR and plaque features in prognosis of aortic stenosis combined with coronary artery disease after TAVR

Qian Tong, Yingxian Sun, Wenyue Pang, Bo Yu et al.
Scientific Reports
Cardiac Valve Diseases and Treatments
article

Computed tomography derived FFR and plaque features in prognosis of aortic stenosis combined with coronary artery disease after TAVR

Qian Tong, Yingxian Sun, Wenyue Pang, Bo Yu, Miaohan Qiu, Bin Wang, Yaling Han, Bin Liu, Bo Luan, Yu Sun, Yang Li, Jihong Liu, Kai Xu, Geng Wang, Ran Guo, Yi Fang, Zhenyang Liang
article en

Abstract

To assess the value of computed tomography angiography (CTA)-derived fractional flow reserve (CT-FFR) and high-risk plaque characteristics (HRPC) in the prediction of prognosis in patients with concomitant aortic stenosis (AS) and coronary artery disease (CAD) after transcatheter aortic valve replacement (TAVR). The study was a post hoc analysis from a multicenter TAVR registry. Patients with AS and obstructive CAD who underwent successful TAVR treatment were enrolled. The CT-FFR and HRPC were measured in coronary vessels with ≥ 50% stenosis lesions. The patients were then grouped according to CT-FFR (≤ 0.8 vs. >0.8) and HRPC (Yes vs. No) criteria. The primary outcome was major adverse cardiovascular events (MACE), a composite of cardiac death, nonfatal myocardial infarction, and ischemia-driven revascularization. The multivariable Cox proportional regression was used to identify independent predictors of MACE. To assess the combined prognostic value of CT-FFR and HRPC to OPT-CAD risk, receiver operating characteristic curves were used and the area under the curve (AUC) was determined. A total of 213 patients were enrolled. The mean age was 74.34 years and 125 (58.4%) were male. The patients with lower CT-FFR (≤ 0.8) had a higher rate of MACE compared with those with CT-FFR > 0.8 (11.9% vs. 2.3%, P = 0.011). However, there was no significant difference in MACE incidence (9.0% vs. 5.3%, P = 0.38) between patients with and without HRPC, respectively. The Cox regression model revealed that advanced age (hazard ratio [HR] 1.07, 95% confidence interval [CI] 1.003-1.15, P = 0.04), elevated NT-proBNP levels (HR 1.004, 95% CI 1.00-1.01, P = 0.046), and higher CT-FFR (HR 0.78, 95% CI 0.62-0.97, P = 0.03) were independent predictors of MACE. The optimal threshold value for predicting MACE using CT-FFR was determined to be 0.79. The performance in predicting MACE using the OPT-CAD score model was enhanced when both CT-FFR and HRPC were incorporated into the model [AUC 0.63 (0.49-0.76) vs. 0.74 (0.63-0.84), P = 0.04]. Pre-procedure CT-FFR was an independent predictor of MACE in patients with concomitant AS and CAD after TAVR.

Scientific ReportsVol. 15(1)
Harbin Medical University (CN), Dalian Medical University (CN), Jilin University (CN), Liaoning Provincial People's Hospital (CN), First Hospital of Jilin University (CN), General Hospital of Shenyang Military Region (CN), Second Affiliated Hospital of Harbin Medical University (CN), First Hospital of China Medical University (CN), First Affiliated Hospital of Dalian Medical University (CN), Second Affiliated Hospital of Jilin University (CN), Affiliated Zhongshan Hospital of Dalian University (CN), China Medical University (CN)
Openalex Percentile: Top 64%
Cardiac Valve Diseases and Treatments
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