High-sensitive troponin T and N-terminal-brain-natriuretic-peptide predict outcome in symptomatic aortic stenosis

Abstract

Objectives. Aortic stenosis (AS) and atherosclerosis share similarities when it comes to risk factors and disease progression. Like in other heart diseases, we hypothesized that biomarkers like high-sensitive troponin T (hsTnT), N-terminal-pro-brain-natriuretic-peptide (NT-proBNP) and high-sensitive C-reactive protein (hsCRP) could be useful in risk stratification. Design. A total of 136 patients (57% men, mean age 74 years), referred for evaluation of AS (valve area 0.62 cm², left ventricular ejection fraction 64%) were consecutively enrolled in the study. The relationship between hsTnT, hsCRP and NT-proBNP, different echocardiographic parameters of AS and cardiac function were investigated as well as their relation to all-cause mortality. Results. In contrast to hsCRP, hsTnT and NT-proBNP were individually correlated with prognosis. Regression analysis identified diabetes and the combination of hsTnT and NT-proBNP as significant predictors of all-cause mortality. When analyzing patients without surgery separately, only the combination of hsTnT and NT-proBNP were identified as a significant predictor of all-cause mortality in multivariable analysis. Conclusion. The combination of NT-proBNP and hsTnT came out as the strongest predictor of outcome irrespective of surgical treatment or not and could be of particular interest in risk-stratification in AS-patients. The results should be confirmed in prospective studies both in symptomatic and asymptomatic patients.

Key words::

• aortic stenosis
• B-type natriuretic peptide
• C-reactive protein
• troponin
• prognosis

Introduction

Aortic stenosis (AS) and atherosclerosis share similarities when it comes to risk factors and disease progression. Degenerative aortic valve diseases are important causes of cardiovascular mortality and morbidity. AS is the most prevalent of all valvular diseases and the prevalence increases with age. In patients with degenerative AS, the aortic valve morphology progresses from normal leaflets to aortic sclerosis and eventually to different degrees of stenosis. In one large study, 20% of patients aged 65–75 years were found to have aortic sclerosis and 1.3% had AS. In the age group over 85 years, the respective percentages were 48 and 4 (1). While previously thought to be a degenerative disorder, recent studies have revealed that the development of AS shares similarities with atherogenesis in the field of inflammation and calcification (2–4).

Echocardiography is today the cornerstone for diagnosis and risk stratification in patients with AS. Both disease severity (i.e., valvular narrowing) as well as myocardial function is important prognostic variables in these patients, but better risk predictors are desired. Troponins, reflecting myocardial injury, brain natriuretic peptides (BNP/N-terminal [NT]-proBNP) reflecting myocardial filling pressure, and C-reactive protein (CRP), being a reliable marker of inflammation, have all been useful in the diagnosis and prognostic stratification of patients with various forms of cardiovascular disorders including stable and unstable atherosclerotic disorders and heart failure (5–7). It appears that the combined use of these biomarkers gives additional information as compared with the use of one of them alone (8).

With this background, we hypothesized that the combined use of troponin, NT-proBNP, and CRP could be useful in risk stratification in patients with advanced AS. There are some reports of elevated CRP and BNP in patients with AS (9,10), and especially BNP may serve as an important prognostic marker. However, there are few reports on the value of troponin as prognostic marker in AS. Also, studies on the additional value to clinical and echocardiographic variables of the combined use of CRP, troponins, and BNP are scarce among AS patients. To test our hypothesis we analyzed plasma levels of high-sensitive troponin T (hsTnT), NT-proBNP and high sensitive CRP (hsCRP) in patients with symptomatic AS. The results were related to echocardiographic parameters as well as to the association of the plasma markers alone or in combination, with long-term mortality.

Material and methods

Patients

Patients referred for evaluation of AS at a tertiary center (Department of Cardiology, Oslo University Hospital Rikshospitalet, Oslo, Norway), between May 2005 and January 2007, were consecutively enrolled in this prospectively design study. Only patients with confirmed AS were included. Of patients asked to participate, none refused. All together 154 patients with suspected aortic stenosis (AS) were scheduled for the study. Of these, 4 did not have AS and 14 had inadequate blood sampling or inadequate echocardiographic data. Thus, 136 patients were evaluated.

Echocardiographic parameters and blood samples were obtained from each patient. Coronary angiography was performed in all patients to identify any concomitant coronary artery disease (CAD; at least 1 vessel disease with >50% narrowing of luminal diameter). Exclusion criteria were severe (grade III) aortic or mitral regurgitation or serum creatinine >150 μmol/L. Baseline characteristics are shown in Table I. All investigations were obtained within a period of 3 days. Informed consent was obtained from each study subject. The regional committee for ethics in medicine approved the study protocol.

Table I. Baseline characteristics.

	Total population (n =136)	Survivors (n =107)	Non-survivors (n =29)	p-Value
Age (years)	74±9	73±10	79±5	<0.001
Male (%)	57	55	65	0.320
BMI (kg/m^2)	26.3±4.2	26.5±4.4	25.7±4.0	0.390
NYHA functional class I/II/III/IV (%)	3/33/63/1	4/36/60/0	0/26/70/4	0.190
CAD (%)	47	44	59	0.200
Smokers (%)	13	15	7	0.087
T2DM (%)	10	7	24	0.007
Hypertension (%)	27	24	35	0.200
Atrial fibrillation (%)	34	30	48	0.048
Biochemistry
Creatinine (µmolL^-1)	89±35	85±27	104±53	0.010
eGFR (ml/min/1.73 m^2)	73±33	76±34	60±24	0.015
hsCRP (mg/L)*	1.8 (0.9,4.4)	1.7 (0.8,3.9)	2.6(1.3,11.7)	0.256
hsTnT (ng/L)*	14.1 8.2,25.1)	12.7(7.8,18.7)	32.3(12.1,57,9)	<0.001
NT-proBNP (pmol/L)*	98 (42,279)	74(37,150)	291(151,853)	<0.001
Hemodynamics
LVEF (%)	62±32	63±11	56±15	0.005
CO (l/min)	5.0±1.1	5.1±1.2	4.5±1.0	0.031
Aortic valve area (cm^2)	0.62±0.2	0.70±0.22	0.60±0.17	0.035
Mean aortic gradient (mmHg)	54±19	55±20	53±16	0.990
Medication (%)
ACE inhibitors	13	12	17	0.800
ARB	21	21	21	0.970
Beta-blocker	48	42	69	0.020
Statins	50	49	55	0.510
Warfarin	20	17	31	0.130
Aspirin	48	51	38	0.480

Values given as percentage, mean ± SD. BMI, body mass index; CAD, coronary artery disease; T2DM, diabetes mellitus type 2; LVEF, left ventricular ejection fraction; hsTnT, high-sensitive troponin T; NT-proBNP, N-terminal pro-brain natriuretic peptide; CO, cardiac output; hsCRP, high sensitive C-reactive protein; ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.

*Median and interquartile range.

Echocardiography

Conventional echocardiographic imaging of the heart was performed from parasternal and apical views by use of a GE Vivid 7 ultrasonic digital scanner (GE Vingmed, Horten, Norway). Continuous wave Doppler from multiple positions was used to obtain the maximum aortic annular blood flow velocities, and used to calculate aortic valve area by use of the continuity equation (11). Doppler echocardiographic calculations of stroke volume and cardiac output were performed on the basis of the aortic annular cross-sectional and flow velocity profile. Calculation of left ventricular ejection fraction (LVEF) was obtained by the biplane Simpson method (12). Dimensional and velocity parameters were averaged from at least 3 (at least 5 in atrial fibrillation) cardiac cycles. Observers were blinded to the clinical patient status and the standard echo findings.

Biochemistry and blood sampling

Peripheral venous blood was drawn into pyrogen-free tubes with EDTA as anticoagulant. The tubes were immediately immersed in melting ice and centrifuged within 30 minutes at 2000g for 20 minutes to obtain platelet-poor plasma. All samples were stored at − 80°C until analysis.

NT-proBNP concentrations in plasma were determined with an electrochemiluminescence immunoassay on a Modular platform (Roche Diagnostica, Basel, Switzerland). The coefficient of variation (CV) was <4%. The lower detection limit was 0.6 pmol/L. The normal range was <35 pmol/L and <60 pmol/L for men aged 50–69 years and >70 years, respectively, and <30 pmol/L and <90 pmol/L for women in these age groups.

Levels of CRP were determined using a particle-enhanced, high-sensitive immunoturbidimetric assay (hsCRP, Tina-Quant CRP Gen.3). This assay has a minimal detectable concentration of 0.6 mg/L, and a total imprecision of ≤7.5% for CRP <5 mg/L. The normal range is <4 mg/L.

TnT was measured by electrochemiluminescence immunoassay (hsTnT, Elecsys Troponin T high sensitive, Roche Diagnostics). In the TnT assay, the limit of blank was 3 ng/L and the lowest concentration with a CV ≤10% was 13 ng/L. Values in the range 12–14 ng/L are within the 99 percentile in a healthy control cohort (Roche Diagnostic).

Follow-up

Survival data were obtained from the Norwegian Population Register and computerized medical records. Mode of death data was collected from ‘Statistics Norway, Causes of death’. Surgical status was extracted from hospital registries and case records.

Statistics

Variables not normally distributed as evaluated by the Kolmogorov–Smirnov test were log transformed for the statistics but may be presented as non-transformed data. Differences between groups were analyzed with the Student t-test or Mann Whitney U test as appropriate. The importance of hsTnT, NT-proBNP, and hsCRP as a risk factor for all-cause mortality was investigated in multi-variable regression analyses including variables significantly associated with mortality as shown in Table I. Continuous variables were included as log 10 transformed values when appropriate. Cox proportional hazard analysis was performed to estimate hazard ratios (HR) using forward stepwise conditional method. The following variables were entered: age, diabetes mellitus, atrial fibrillation, eGFR, LVEF, aortic valve area, hsTnT, NT-proBNP, CRP as well as interaction terms between the biochemical variables (i.e., hsTnT*NT-proBNP, hsTnT*CRP, NT-proBNP*CRP). Follow-up time for all-cause mortality was calculated from time of inclusion to death from any cause. Harrell's C-index was calculated to evaluate the accuracy for prediction of all-cause mortality. Receiver-operating characteristics (ROC) curves were generated to evaluate the accuracy for prediction of all-cause mortality. Kaplan–Meier analysis with log-rank test was performed to compare the number of events in different groups (comparisons pooled over strata). P values are two-sided and considered significant when <0.05.

Results

Of all 136 patients, 103 were scheduled for aortic valve replacement (AVR) while surgical intervention was declined in 33 (comorbidity/high risk for operation [n =20], unwilling to undergo operation [n =4], uncertain clinical benefit because of less severe symptoms [n =8], other reasons [n =1]). One patient accepted for valve surgery died pending surgery, while 102 patients underwent surgical intervention.

hsCRP, hsTnT, and NT-proBNP in relation to echocardiographic characteristics

Correlations between echocardiographic parameters and biomarkers are shown in Table II. While hsCRP and hsTnT showed no correlation with aortic pressure gradient and aortic valve area, NT-proBNP was positively correlated with aortic pressure gradient and inversely correlated with aortic valve area. Not surprisingly, hsTnT and in particular NT-proBNP were significantly correlated with several parameters of myocardial function, while hsCRP was significantly associated only with ejection fraction, left atrial diameter and mitral deceleration time (Table II).

Table II. Relation between biomarkers and echocardiography.

	Mean ± SD	hsTnT*	NT-proBNP*	hsCRP*
Mean aortic gradient (mmHg)	54±19	0.15 (0.085)	0.21 (0.020)	− 0.06 (0.540)
Aortic valve area (cm^2)	0.62±0.22	− 0.16 (0.082)	− 0.34 (<0.001)	0.05 (0.618)
Interventricular septal diameter (cm)	1.26±0.2	0.21 (0.013)	0.25 (0.003)	0.11 (0.198)
Left atrium diameter (cm)	4.1±0.7	0.24 (0.007)	0.46 (<0.001)	0.23 (0.012)
Deceleration time (ms)	272±91	0.03 (0.742)	− 0.23 (0.025)	− 0.27 (0.008)
CI (l/min/m^2)	2.75±0.6	− 0.26 (0.005)	− 0.29 (0.002)	0.00 (0.988)
EF (%)	63±11	− 0.21 (0.015)	− 0.41 (<0.001)	− 0.22 (0.009)
EDV (ml)	85±32	0.22 (0.009)	0.16 (0.059)	0.07 (0.419)
ESV (ml)	33±20	0.25 (0.003)	0.31 (<0.001)	0.16 (0.064)
Tricuspid regurgitation (cm/s)	30±8	0.18 (0.058)	0.35 (<0.001)	0.14 (0.139)

Variables were log-transformed. Values given as mean ± SD. CI, cardiac index; EF, ejection fraction; EDV, end diastolic volume; ESV end systolic volume.

*Correlation coefficient with p-values in parentheses.

Differences in patient characteristics between survivors and non-survivors

During a mean follow-up of 37 months (range 1–54 months), 29 patients died; 12 in the non-surgical group (9 for cardiovascular and 3 of non-cardiovascular reasons [i.e., cancer and chronic obstructive pulmonary disease]) and 17 (i.e., 4 of cardiovascular reason, 6 of sudden death and 7 of non-cardiovascular reason) in the group who underwent surgery. There was a significantly higher mortality rate in patients who were not operated (HR 2.93 [1.41 − 6.10], p =0.004). When evaluating the association between mortality and demographic data, echocardiographic parameters and biochemical characteristics of the AS patients, several significant findings were revealed (Table I). First, non-survivors were older, and more often had diabetes mellitus type 2 (T2DM), atrial fibrillation, or renal impairment. They further were characterized by markedly increased hsTnT and NT-proBNP levels as well as increased hsCRP (Figure 1). Finally, non-survivors had lower effective aortic valve area, had lower LVEF and cardiac output and were more likely to use beta-blockers. With respect to other baseline characteristics, there were no significant differences between survivors and non-survivors.

Figure 1. Plasma levels of hsTnT, NT-proBNP and hsCRP in 136 patients with symptomatic aortic stenosis (AS) according to survival during long-term follow-up. Data are shown as median and interquartile range. *p <0.05, **p <0.001 versus survivors.

Univariate predictors of all-cause mortality

Figure 2 demonstrates a strong association between the concentrations of hsCRP, NT-proBNP and particularly hsTnT, and all-cause mortality. The unadjusted HR when comparing quartile 4 with quartile 1–3 was 6.44 (2.17–19.09, p <0.001) for NT-proBNP and 9.89 (2.90–33.75, p <0.001) for hsTnT, while hsCRP failed to reach significance.

Figure 2. Association between hsTnT, NT-proBNP, hsCRP, and all-cause mortality in 136 patients with symptomatic AS. Kaplan–Meier curves showing the cumulative incidence of all-cause mortality (n =29) during the entire study (mean follow-up 37 months, range 1–54), according to quartiles at enrollment.

Unadjusted Cox regressions variables are shown in Table III left column, showing significant hazard ratios for hsTnT, NT-proBNP, and hsCRP as well as for the combination of hsTnT and NT-proBNP (as continuous variables). ROC curves comparing the predictive value of hsTnT, NT-proBNP, and hsCRP are given in Figure 3. The ROC analyses of death showed C-index for NT-proBNP of 0.76 (95%CI 0.66–0.86, p <0.001), of hsTnT 0.71 (95% CI 0.59–0.82, p <0.001) and of hsCRP 0.64 (95% CI 0.53–0.75, p =0.012) (Figure 3). The optimal cut-off point for NT-proBNP was 142 pmol/L and for hsTnT 32 ng/l.

Table III. Multi-variable analyses of predictors of all-cause mortality in 136 patients with symptomatic AS.

	Unadjusted		Multivariable echo* (Stepwise)		Multivariable (Stepwise)
Variable	HR (95%CI)	p	HR (95%CI)	p	HR (95%CI)	p
Age	1.10 (1.04–1.16)	<0.001
Diabetes Mellitus	3.11 (1.39–6.98)	0.006			2.63 (1.09–6.32)	0.031
Atrial fibrillation	2.01 (1.00–4.07)	0.052
[Loge] eGFR	0.05 (0.01–0.29)	0.001
[Loge] hsTnT	11.03 (1.49–5.66)	0.003
[Loge] hsCRP	2.90 (1.49–5.66)	0.002
[Loge] NT-proBNP	8.54 (4.01–18.17)	<0.001
[Loge] Ejection fraction	0.19 (0.00–0.46)	0.002	0.74 (0.15–3.74)	0.712
[Loge] Aortic valve area	0.58 (0.36–0.92)	0.022	0.81 (0.50–1.32)	0.403
[Loge] HsTnT*[Loge] NT-proBNP	1.96 (1.62–2.38)	<0.001	1.89 (1.36–2.61)	<0.001	2.16 (1.65–2.81)	<0.001
[Loge] HsCRP*[Loge] NT-proBNP	1.68 (1.38–2.05)	<0.001	1.28 (1.03–1.60)	0.025

hsCRP, high sensitive C-reactive protein; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal pro-brain natriuretic peptide; hsTnT, high sensitive Troponin T.

*Force adjusted with ejection fraction and aortic valve area.

Figure 3. ROC curve analysis for the predictive value of hsTnT, NT-proBNP, and hsCRP for all-cause mortality. C-index and 95% CI are given.

To test if any additional predictive value could be gained, we tested combinations of hsTnT, NT-proBNP, and CRP (data not shown) quartiles in the prediction of all-cause mortality. As shown in Figure 4, combing the fourth quartiles of hsTnT and NT-proBNP revealed a strong association.

Figure 4. Risk prediction for all-cause mortality in symptomatic AS using combinations of quartiles of hsTnT and NT-proBNP on all-cause mortality.

Multivariable predictors of all-cause mortality

To further test which predictor, or which combination of predictors, were most strongly associated with all-cause mortality; the unadjusted variables in Table III were included in a multivariable stepwise Cox regression. This analysis identified diabetes and the combination of hsTnT and NT-proBNP (for variables entered see statistics section) as significant predictors of all-cause mortality (Table III right column). Of the variables in Table I, associations with the presence of diabetes were observed for (using logistic regression): BMI B =0.17±0.07, p =0.014, eGFR B =1.60±0.71, p =0.024, CRP B =1.44±0.53, p =0.006. A stepwise logistic regression including these variables and operation status shows that CRP (B =1.46±0.56, p =0.009) and eGFR (B =1.52±0.73, p =0.038) were predictors for diabetes, underscoring a link between diabetes and inflammation and impaired kidney function, potentially contributing to the predictive power of diabetes. When analyzing patients who were operated with AVR separately (Table IV), the same predictors were identified in multivariable stepwise regression, although the association was weaker. In unoperated patients only the combination of hsTnT and NT-proBNP was identified as a significant predictor of all-cause mortality in multivariable analysis (HR =2.87 [1.70–4.84], p <0.001).

Table IV. Multi-variable analyses of predictors of all-cause mortality in 102 patients with symptomatic AS who underwent AVR.

	Unadjusted				Multivariable (Stepwise)
Variable	HR (95%CI)	p	Multivariable echo* (Stepwise)		HR (95%CI)	p
Age	1.09 (1.02–1.18)	0.019
Diabetes Mellitus	3.69 (1.19–11.47)	0.024			5.65 (1.71–18.50)	0.004
Atrial fibrillation	2.14 (0.80–5.74)	0.130
[Loge] eGFR	0.06 (0.00–0.98)	0.048
[Loge] hsTnT	5.42 (1.46–20.04)	0.011
[Loge] hsCRP	1.86 (0.63–5.50)	0.260
[Loge] NT-proBNP	3.65 (1.41–9.46)	0.008
[Loge] Ejection fraction	0.11 (0.02–0.72)	0.021	0.22 (0.03–1.88)	0.44
[Loge] Aortic valve area	0.69 (0.37–1.29)	0.230	0.74 (0.38–1.42)	0.74
[Loge] hsTnT*[Loge] NT-proBNP	1.69 (1.21–2.36)	0.004			1.89 (1.28–2.78)	0.001
[Loge] HsCRP*[Loge] NT-proBNP	1.66 (1.15–2.41)	0.007	1.61 (1.08–2.38)

hsCRP, high sensitive C-reactive protein; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal pro-brain natriuretic peptide; hsTnT, high sensitive Troponin T. *Force adjusted with ejection fraction and aortic valve area.

Discussion

Clinical symptoms in conjunction with echocardiographic quantification form the basis of prognostic evaluation in patients with aortic stenosis. In the present study, we show that the ‘standard’ biomarkers hsTnT and NT-proBNP may give additional prognostic information in addition to established echocardiographic parameters. hsCRP seems to be of limited value. Our study confirms that traditional markers such as age, diabetes mellitus, and renal function serve as prognostic markers in addition to stenosis severity and depressed myocardial function. However, when the biomarkers were included in the model, all the traditional markers fell out as independent prognostic variables, except for diabetes mellitus. In fact hsTnT was the strongest prognostic marker, and especially the combination of hsTnT and NT-proBNP appears to be of particular prognostic value in these patients with symptomatic AS.

Diabetes mellitus was a predictor for mortality in the operated group, probably due to a reduced eGFR as shown in multivariate analysis. In general terms, patients with diabetes have more frequent comorbidities like peripheral artery disease and renal failure and in the present study, the presence of diabetes was significantly associated with decreased eGFR. Diabetes has also been reported to be associated with the presence of additional coronary artery disease in patients with AS (13). In the unoperated group, diabetes did not predict mortality, but caution is needed in the interpretation because of the low number of patients declined surgery. In fact hsTnT was the strongest prognostic marker, and especially the combination of hsTnT and NT-proBNP appears to be of particular prognostic value in these patients with symptomatic AS.

Mortality in the non-operated group may seem low compared to former studies. Considering that only 33 patients were not found feasible for surgery, caution is needed in the interpretation. Because our hospital is a tertiary referral center, the oldest patients, patients with severe comorbidities and other reasons for poor prognosis may not have been referred. Eight of the patients who were not considered for surgery, had less severe symptoms, which may contribute to a lower mortality.

To date echocardiographic examinations with assessment of the severity of the valvular stenosis and myocardial function together with clinical and hemodynamic parameters have been the cornerstone of prognostication and timing of surgery in AS. Recently, the potential role of BNP/NT-proBNP in prognostication of these patients was reported (14,15), while the value of hsTnT and CRP measurements have been less well studied. All these biomarkers are frequently used in the diagnosis and prognostic stratification of a number of cardiovascular diseases. Cardiac troponins are sensitive and specific markers of myocyte injury and have for a long time been standard in evaluating patients with acute coronary syndromes (5). The use of troponin as a marker of myocardial damage seems to be even more relevant with the use of the new highly sensitive assays for cardiac troponin T. Thus, Latini et al. found that while only 10% of heart failure patients had detectable TnT levels with the traditional assay, 92% of the patients had detectable hsTnT levels, with a strong association between high hsTnT levels and disease severity (16). More recently, Omland et al. showed the ability of hsTnT to predict the incidence of cardiovascular death and development of heart failure in patients with stable CAD (17). In the present study, we extend these findings by showing the ability of hsTnT levels to give independent prognostic information in patients with symptomatic AS. A recent study indicates that hsTnT values are determined by left ventricular mass and may provide prognostic information (18). hsTnT elevation may indicate ongoing myocardial damage in patients with symptomatic AS. Quantification of this process might be of importance in the follow-up of these patients.

The present study confirms previous reports on a correlation between NT-proBNP and disease severity in patients with AS. In one study, Weber et al. found that while NT-proBNP increased in patients treated conservatively, it decreased after valve replacement (14). Pre-operative measurement of BNP has also been found to give independent prognostic information on post-operative mortality and outcome in patients undergoing AVR. A few other studies also conclude that BNP is an independent predictor of outcome, symptom-free survival, and post-operative outcome with regard to survival (19). While the current study confirms that BNP could give prognostic information in patients with symptomatic AS, our main finding was that the combination of NT-proBNP and hsTnT came out as the strongest predictor of outcome irrespective of the patients underwent surgery or not. The combination of biomarkers that at least in part reflects different aspects of the disease process (e.g., myocardial wall stress and cardiomyocyte injury, BNP, and hsTnT, respectively) is an interesting area of cardiovascular research. Our finding suggest that the combination of NT-proBNP and hsTnT could be of particular interest in patients with AS.

In contrast to NT-proBNP and hsTnT, hsCRP did not come out as a significant predictor of mortality. Galante et al. (9) have shown correlation between CRP and aortic stenosis severity. On the other hand, other studies have demonstrated that CRP does not predict disease progression in AS (20), suggesting measurement of CRP to be of limited value in AS. The role of inflammation as an important feature of disease progression in patients with AS, is at present not clear.

There are limitations to this study; the patient sample was relatively small with a limited number of adverse events. Thus, the prognostic value of our results has to be confirmed in prospective studies. Patients with severe aortic regurgitation or severe mitral valve dysfunction were excluded from the study. The exact number of patients excluded for these reasons is not known. Also, patients with severe aortic regurgitation or severe mitral dysfunction were excluded from the study, but unfortunately, the exact number of patients excluded for these reasons is not known. Finally, the patients in our study were symptomatic with severe aortic stenosis and there is a need to perform studies in a wider range of aortic stenosis severity and in non-symptomatic patients.

In conclusion, NT-pro-BNP and hsTnT seem to reflect the hemodynamic burden and degree of myocyte injury, respectively, and may be of value in risk stratification in patients with advanced AS. The combination of NT-proBNP and hsTnT came out as the strongest predictor of outcome irrespective of surgical treatment or not, suggesting that this combination could be of particular interest in risk-stratification in AS. These findings indicate that biomarkers may improve the management of patients with AS. Forthcoming studies should test this hypothesis in larger populations of AS patients, with different degree of disease severity and should also address prognostic consequences of changing surgical techniques.

Acknowledgement

This work was supported by a grant from an anonymous subject.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.