Histological assessment of cardiac amyloidosis in patients undergoing transcatheter aortic valve replacement

Abstract

Abstract

Aims Studies have reported a strongly varying co‐prevalence of aortic stenosis (AS) and cardiac amyloidosis (CA). We sought to histologically determine the co‐prevalence of AS and CA in patients undergoing transcatheter aortic valve replacement (TAVR). Consequently, we aimed to derive an algorithm to identify cases in which to suspect the co‐prevalence of AS and CA.

Methods and results

In this prospective, monocentric study, endomyocardial biopsies of 162 patients undergoing TAVR between January 2017 and March 2021 at the University Medical Centre Göttingen were analysed by one pathologist blinded to clinical data using haematoxylin–eosin staining, Elastica van Gieson staining, and Congo red staining of endomyocardial biopsies. CA was identified in only eight patients (4.9%). CA patients had significantly higher N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) levels (4356.20 vs. 1938.00 ng/L, P = 0.034), a lower voltage‐to‐mass ratio (0.73 vs. 1.46 × 10 −2 mVm 2 /g, P = 0.022), and lower transaortic gradients (Pmean 17.5 vs. 38.0 mmHg, P = 0.004) than AS patients. Concomitant CA was associated with a higher prevalence of post‐procedural acute kidney injury (50.0% vs. 13.1%, P = 0.018) and sudden cardiac death [SCD; P (log‐rank test) = 0.017]. Following propensity score matching, 184 proteins were analysed to identify serum biomarkers of concomitant CA. CA patients expressed lower levels of chymotrypsin ( P = 0.018) and carboxypeptidase 1 ( P = 0.027). We propose an algorithm using commonly documented parameters—stroke volume index, ejection fraction, NT‐proBNP levels, posterior wall thickness, and QRS voltage‐to‐mass ratio—to screen for CA in AS patients, reaching a sensitivity of 66.6% with a specificity of 98.1%.

Conclusions The co‐prevalence of AS and CA was lower than expected, at 4.9%. Despite excellent 1 year mortality, AS + CA patients died significantly more often from SCD. We propose a multimodal algorithm to facilitate more effective screening for CA containing parameters commonly documented during clinical routine. Proteomic biomarkers may yield additional information in the future.