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Updated: Jun 12, 2026

Full-root Aortic Valve Replacement by Stentless Aortic Xenografts in Patients with Small Aortic Roots
Published on: May 21, 2017
Calcification of surgical aortic bioprostheses and its impact on clinical outcome
Guillaume Guimbretière1,2, Thomas Sénage1,3, Anne-Sophie Boureau1,2
1L'institut du thorax, CHU Nantes, 44093 Nantes, France.
Aims:
Aortic valve calcification (AVC) of surgical valve bioprostheses (BPs) has been poorly explored. We aimed to evaluate in vivo and ex vivo BP AVCs and its prognosis value.
Methods And Results:
Between 2011 and 2019, AVC was assessed using in vivo computed tomography (CT) in 361 patients who had undergone surgical valve replacement 6.4 ± 4.3 years earlier. Ex vivo CT scans were performed for 37 explanted BPs. The in vivo CT scans were interpretable for 342 patients (19 patients [5.2%] were excluded). These patients were 77.2 ± 9.1 years old, and 64.3% were male. Mean in vivo AVC was 307 ± 500 Agatston units (AU). The AVC was 562 ± 570 AU for the 183 (53.5%) patients with structural valve degeneration (SVD) and 13 ± 43 AU for those without SVD (P < 0.0001). In vivo and ex vivo AVCs were strongly correlated (r = 0.88, P < 0.0001). An in vivo AVC > 100 AU (n = 147, 43%) had a specificity of 96% for diagnosing Stage 2-3 SVD (area under the curve = 0.92). Patients with AVC > 100 AU had a worse outcome compared with those with AVC ≤ 100 AU (n = 195). In multivariable analysis, AVC was a predictor of overall mortality (hazard ratio [HR] and 95% confidence interval = 1.16 [1.04-1.29]; P = 0.006), cardiovascular mortality (HR = 1.22 [1.04-1.43]; P = 0.013), cardiovascular events (HR = 1.28 [1.16-1.41]; P < 0.0001), and re-intervention (HR = 1.15 [1.06-1.25]; P < 0.0001). After adjustment for Stage 2-3 SVD diagnosis, AVC remained a predictor of overall mortality (HR = 1.20 [1.04-1.39]; P = 0.015) and cardiovascular events (HR = 1.25 [1.09-1.43]; P = 0.001).
Conclusion:
CT scan is a reliable tool to assess BP leaflet calcification. An AVC > 100 AU is tightly associated with SVD and it is a strong predictor of overall mortality and cardiovascular events.
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