Prognostic utility of biomarkers in predicting of one-year outcomes in patients with aortic stenosis treated with transcatheter or surgical aortic valve implantation

• Published in: PloS one Vol. 7; no. 12; p. e48851
• Main Authors: Parenica, Jiri, Nemec, Petr, Tomandl, Josef, Ondrasek, Jiri, Pavkova-Goldbergova, Monika, Tretina, Martin, Jarkovsky, Jiri, Littnerova, Simona, Poloczek, Martin, Pokorny, Petr, Spinar, Jindrich, Cermakova, Zdenka, Miklik, Roman, Malik, Petr, Pes, Ondrej, Lipkova, Jolana, Tomandlova, Marie, Kala, Petr
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14.12.2012; Public Library of Science (PLoS)
• Subjects: Aged; Aged, 80 and over; Algorithms; Analysis; Aorta; Aortic stenosis; Aortic valve; Aortic valve stenosis; Aortic Valve Stenosis - surgery; Aortic Valve Stenosis - therapy; Biochemistry; Biological markers; Biology; Biomarkers; Biomarkers - metabolism; Cardiac Catheterization - adverse effects; Cardiac Catheterization - methods; Cardiovascular disease; Chemistry; Consortia; Cystatin C; Cysteine; Deoxyguanosine; Extracellular matrix; Extracellular Matrix - metabolism; Female; Ferritin; Gelatinase B; Glutathione; Heart attacks; Heart failure; Heart surgery; Heart Valve Prosthesis Implantation - adverse effects; Heart Valve Prosthesis Implantation - methods; Homocysteine; Hospitals; Humans; Implantation; Kidney - metabolism; Male; Malondialdehyde; Malondialdehyde - metabolism; Mathematical models; Matrix metalloproteinase; Medical prognosis; Medical research; Medicine; Metabolism; Metalloproteinase; Middle Aged; Mortality; Multivariate analysis; Nitric Oxide - metabolism; Oxidative Stress; Patient outcomes; Patients; Peptides; Physiology; Prediction models; Prognosis; Prospective Studies; Reclassification; Recovery (Medical); Risk; Risk Assessment; Risk groups; ROC Curve; Safety; Stenosis; Surgery; Surgical implants; Tissue inhibitor of metalloproteinase 1; Treatment Outcome; Czech Republic
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0048851

The aim of the work was to find biomarkers identifying patients at high risk of adverse clinical outcomes after TAVI and SAVR in addition to currently used predictive model (EuroSCORE). There is limited data about the role of biomarkers in predicting prognosis, especially when TAVI is available. The multi-biomarker sub-study included 42 consecutive high-risk patients (average age 82.0 years; logistic EuroSCORE 21.0%) allocated to TAVI transfemoral and transapical using the Edwards-Sapien valve (n = 29), or SAVR with the Edwards Perimount bioprosthesis (n = 13). Standardized endpoints were prospectively followed during the 12-month follow-up. The clinical outcomes after both TAVI and SAVR were comparable. Malondialdehyde served as the best predictor of a combined endpoint at 1 year with AUC (ROC analysis) = 0.872 for TAVI group, resp. 0.765 (p<0.05) for both TAVI and SAVR groups. Increased levels of MDA, matrix metalloproteinase 2, tissue inhibitor of metalloproteinase (TIMP1), ferritin-reducing ability of plasma, homocysteine, cysteine and 8-hydroxy-2-deoxyguanosine were all predictors of the occurrence of combined safety endpoints at 30 days (AUC 0.750-0.948; p<0.05 for all). The addition of MDA to a currently used clinical model (EuroSCORE) significantly improved prediction of a combined safety endpoint at 30 days and a combined endpoint (0-365 days) by the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) (p<0.05). Cystatin C, glutathione, cysteinylglycine, asymmetric dimethylarginine, nitrite/nitrate and MMP9 did not prove to be significant. Total of 14.3% died during 1-year follow-up. We identified malondialdehyde, a marker of oxidative stress, as the most promising predictor of adverse outcomes during the 30-day and 1-year follow-up in high-risk patients with symptomatic, severe aortic stenosis treated with TAVI. The development of a clinical "TAVIscore" would be highly appreciated. Such dedicated scoring system would enable further testing of adjunctive value of various biomarkers.