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ObjectiveIn heart failure populations without aortic stenosis (AS), the prognostic utility of multiple biomarkers in addition to clinical factors has been demonstrated. We aimed to determine whether multiple biomarkers of cardiovascular stress are associated with mortality in patients with AS undergoing aortic valve replacement (AVR) independent of clinical factors.MethodsFrom a prospective registry of patients with AS, 345 participants who were referred for and treated with AVR (transcatheter (n=183) or surgical (n=162)) were included. Eight biomarkers were measured on blood samples obtained prior to AVR: growth differentiation factor 15 (GDF15), soluble ST2 (sST2), amino-terminal pro-B-type natriuretic peptide (NTproBNP), galectin-3, high-sensitivity cardiac troponin T, myeloperoxidase, high-sensitivity C reactive protein and monocyte chemotactic protein-1. Biomarkers were evaluated based on median value (high vs low) in a Cox proportional hazards model for all-cause mortality and a parsimonious group of biomarkers selected. Mean follow-up was 1.9±1.2 years; 91 patients died.ResultsThree biomarkers (GDF15, sST2 and NTproBNP) were retained in the model. One-year mortality was 5%, 12%, 18% and 33% for patients with 0 (n=79), 1 (n=96), 2 (n=87) and 3 (n=83) biomarkers elevated, respectively (p<0.001). After adjustment for the Society of Thoracic Surgeons (STS) risk score, a greater number of elevated biomarkers was associated with increased mortality (referent: 0 elevated): 1 elevated (HR 1.47, 95% CI 0.60 to 3.63, p=0.40), 2 elevated (HR 2.89, 95% CI 1.24 to 6.74, p=0.014) and 3 elevated (HR 4.59, 95% CI 1.97 to 10.71, p<0.001). Among patients at intermediate or high surgical risk (STS score ≥4), 1-year and 2-year mortality rates were 34% and 43% for patients with three biomarkers elevated versus 4% and 4% for patients with 0 biomarkers elevated. When added to the STS score, the number of biomarkers elevated provided a category-free net reclassification improvement of 64% at 1 year (p<0.001). The association between a greater number of elevated biomarkers and increased mortality after valve replacement was similar in the transcatheter and surgical AVR populations.ConclusionsThese findings demonstrate the potential utility of multiple biomarkers to aid in risk stratification of patients with AS. Further studies are needed to evaluate their utility in clinical decision-making in specific AS populations.

Objective An inflammatory response after cardiac surgery is associated with worse clinical outcomes, but recent trials to attenuate it have been neutral. We evaluated the association between systemic inflammatory response syndrome (SIRS) and mortality after transcatheter (TAVR) and surgical aortic valve replacement (SAVR) for aortic stenosis (AS) and evaluated whether diabetes influenced this relationship. Methods Patients (n=747) with severe AS treated with TAVR (n=264) or SAVR (n=483) between January 2008 and December 2013 were included and 37% had diabetes mellitus. SIRS was defined by four criteria 12–48 h after aortic valve replacement (AVR): (1) white blood cell count <4 or >12; (2) heart rate >90; (3) temperature <36 or >38°C; or (4) respiratory rate >20. Severe SIRS was defined as meeting all four criteria. The primary endpoint was 6-month all-cause mortality (60 deaths occurred by 6 months). Inverse probability weighting (IPW) was performed on 44 baseline and procedural variables to minimise confounding. Results Severe SIRS developed in 6% of TAVR patients and 11% of SAVR patients (p=0.02). Six-month mortality tended to be higher in those with severe SIRS (15.5%) versus those without (7.4%) (p=0.07). After adjustment, severe SIRS was associated with higher 6-month mortality (IPW adjusted HR 2.77, 95% CI 2.04 to 3.76, p<0.001). Moreover, severe SIRS was more strongly associated with increased mortality in diabetic (IPW adjusted HR 4.12, 95% CI 2.69 to 6.31, p<0.001) than non-diabetic patients (IPW adjusted HR 1.74, 95% CI 1.10 to 2.73, p=0.02) (interaction p=0.007). The adverse effect of severe SIRS on mortality was similar after TAVR and SAVR. Conclusions Severe SIRS was associated with a higher mortality after SAVR or TAVR. It occurred more commonly after SAVR and had a greater effect on mortality in diabetic patients. These findings may have implications for treatment decisions in patients with AS, may help explain differences in outcomes between different AVR approaches and identify diabetic patients as a high-risk subgroup to target in clinical trials with therapies to attenuate SIRS.

Pressure overload initiates a series of alterations in the human heart that predate macroscopic organ-level remodeling and downstream heart failure. We study aortic stenosis through integrated proteomic, tissue transcriptomic, and genetic methods to prioritize targets causal in human heart failure. First, we identify the circulating proteome of cardiac remodeling in aortic stenosis, specifying known and previously-unknown mediators of fibrosis, hypertrophy, and oxidative stress, several associated with interstitial fibrosis in a separate cohort ( N  = 145). These signatures are strongly related to clinical outcomes in aortic stenosis ( N  = 802) and in broader at-risk populations in the UK Biobank ( N  = 36,668). We next map this remodeling proteome to myocardial transcription in patients with and without aortic stenosis through single-nuclear transcriptomics, observing broad differential expression of genes encoding this remodeling proteome, featuring fibrosis pathways and metabolic-inflammatory signaling. Finally, integrating our circulating and tissue-specific results with modern genetic approaches, we implicate several targets as causal in heart failure. Pressure overload in the heart, such as from aortic stenosis, triggers early molecular changes before visible damage occurs. Here, the authors show that combining proteomics, transcriptomics, and genetic data reveals key drivers of heart failure, highlighting potential targets for treatment.

Acute kidney injury after transcatheter aortic valve implantation (TAVI) has been associated with adverse outcomes; however, data are limited on the subacute changes in renal function that occur after discharge and their impact on clinical outcomes. This study investigates the relation between subacute changes in kidney function at 30 days after TAVI and survival. Patients from 2 centers who underwent TAVI and survived beyond 30 days with baseline, in-hospital, and 30-day measures of renal function were retrospectively analyzed. Patients were stratified based on change in estimated glomerular filtration rate (eGFR) from baseline to 30 days as follows: improved (≥15% higher than baseline), worsened (≤15% lower), or unchanged (values in between). Univariable and multivariable models were constructed to identify predictors of subacute changes in renal function and of 2-year mortality. Of the 492 patients who met inclusion criteria, eGFR worsened in 102 (22%), improved in 110 (22%), and was unchanged in 280 (56%). AKI occurred in 90 patients (18%) and in only 27% of patients with worsened eGFR at 30 days. After statistical adjustment, worsened eGFR at 30 days (hazard ratio vs unchanged eGFR 2.09, 95% CI 1.37 to 3.19, p <0.001) was associated with worse survival, whereas improvement in renal function was not associated with survival (hazard ratio vs unchanged eGFR 1.30, 95% CI 0.79 to 2.11, p = 0.30). Worsened renal function at 30 days after TAVI is associated with increased mortality after TAVI. In conclusion, monitoring renal function after discharge may identify patients at high risk of adverse outcomes.