Abstract
Background
Bicuspid aortic valve (BAV) is associated with a faster progression of aortic stenosis (AS). Whether the determinants of AS progression are the same or different in patients with BAV vs tricuspid aortic valve (TAV) is unknown. The aim of this study was to identify the factors associated with the progression of AS in patients with BAV vs patients with TAV.
Methods
Patients with AS were prospectively recruited in the Metabolic Determinants of the Progression of Aortic Stenosis (PROGRESSA) study (ClinicalTrials.gov Identifier: NCT01679431). The haemodynamic progression rate of AS was assessed by the annualized progression rate of peak aortic jet velocity (Vpeak). Univariable and multivariable linear regression analyses were used to identify the factors associated with a faster progression of AS in patients with BAV vs patients with TAV.
Results
There were 79 patients with BAV and 208 patients with TAV. The baseline severity of AS was similar between the 2 groups of patients as well as the annualized progression rate of AS. In patients with BAV, obesity (β = 0.25, P = 0.04), diabetes (β = 0.26, P = 0.02), and BAV with right-noncoronary cusp fusion (β = 0.29, P = 0.01) were found to be independently associated with a faster progression of AS, whereas in patients with TAV, AS baseline severity (baseline Vpeak, β = 0.14, P = 0.04) and chronic kidney disease (β = 0.16, P = 0.02) were significantly associated with AS progression.
Conclusion
Factors associated with progression rate of AS are different in BAV and TAV. The main factors associated with a faster progression of AS appear to be obesity, diabetes, right-noncoronary cusp fusion in patients with BAV vs chronic kidney disease in patients with TAV.
Résumé
Contexte
La bicuspidie valvulaire aortique (BVA) est associée à une progression plus rapide de la sténose aortique (SA). On ignore toutefois si les facteurs en cause dans la progression de la SA sont les mêmes chez les patients qui présentent une BVA et chez ceux qui présentent une valve aortique tricuspide. Le but de cette étude était de déterminer les facteurs associés à la progression de la SA chez les patients présentant une BVA par rapport à ceux ayant une valve aortique tricuspide.
Méthodologie
Des patients présentant une SA ont été recrutés dans l’étude PROGRESSA (Metabolic Determinants of the Progression of Aortic Stenosis), une étude prospective sur les déterminants métaboliques de la progression de la SA (ClinicalTrials.gov : NCT01679431). Pour calculer le taux de progression hémodynamique de la SA, on a utilisé les mesures annualisées de la vélocité maximale du jet transaortique (Vmax). Des analyses de régression linéaire univariées et multivariées ont permis de mettre en évidence les facteurs associés à une progression plus rapide de la SA en présence d’une BVA par rapport à une valve aortique tricuspide.
Résultats
Parmi les patients évalués, 79 présentaient une BVA et 208, une valve aortique tricuspide. La gravité de la SA au départ était comparable entre les deux groupes de patients, tout comme le taux de progression annualisé de la SA. Chez les patients avec BVA, l’obésité (β = 0,25, P = 0,04), le diabète (β = 0,26, P = 0,02) et la BVA avec fusion des feuillets coronaire droit et non coronaire (β = 0,29, P = 0,01) ont été associés de manière indépendante à une progression plus rapide de la SA, tandis que chez les patients ayant une valve tricuspide, la gravité de la SA au départ (Vmax initiale, β = 0,14, P = 0,04) et la présence d’une néphropathie chronique (β = 0,16, P = 0,02) ont été significativement associées à une progression de la SA.
Conclusion
Les facteurs associés au taux de progression de la SA sont différents selon qu’il y a ou non présence d’une BVA. Les principaux facteurs associés à une progression plus rapide de la SA semblent être l’obésité, le diabète et la fusion des feuillets coronaire droit et non coronaire pour la BVA, tandis que la néphropathie chronique serait le facteur aggravant chez les patients présentant une valve aortique tricuspide.
Calcific aortic stenosis (AS) is the third most common cardiovascular disease in the high-income countries.1 The 2 main etiologies are a calcifying disease on a tricuspid aortic valve (TAV) and the presence of a congenitally abnormal bicuspid aortic valve (BAV). BAV is the most common congenital heart anomaly with a prevalence of 1%-2% in the general population.2,3 Subjects with a BAV have a higher risk of developing AS, and they develop AS earlier in life (ie, 10-20 years earlier). Furthermore, for a given age and sex, the progression of AS is faster in patients with BAV vs those with TAV.3, 4, 5
Several cardiovascular risk factors have been found to be associated with a faster progression of AS in previous studies, including older age, baseline AS severity, hypertension, dyslipidaemia, metabolic syndrome, diabetes, apolipoprotein B/apolipoprotein A1 (apoB/apoA1) ratio, lipoprotein (a) levels, oxidized phospholipids levels, and chronic kidney disease.6, 7, 8, 9, 10, 11, 12 However, these previous studies pooled together patients with BAV and those with TAV and did not perform separate analyses in BAV and TAV. It is thus unknown whether the determinants of AS progression are similar or different in BAV vs TAV. The objective of this study was thus to identify the factors associated with the progression of AS in patients with a BAV vs those with a TAV.
Material and Methods
Study population
Patients were prospectively recruited in the Metabolic Determinants of the Progression of Aortic Stenosis (PROGRESSA) study (ClinicalTrials.gov Identifier: NCT01679431). Patients were included if they had: (1) age >18 years old, (2) an AS defined by a peak aortic jet velocity (Vpeak) ≥2 m/s, and (3) a preserved left ventricular ejection fraction (LVEF, ≥50%). The exclusion criteria were: (1) an aortic or mitral regurgitation > mild, (2) a concomitant mitral stenosis, (3) a previous intervention on the aortic or mitral valve, and (4) patients with a history of rheumatic disease, endocarditis, or chest radiotherapy. In this subanalysis of the PROGRESSA study, patients were included if they had at least the 1-year echocardiography follow-up.
Data collection
Clinical data included anthropometric measurements (body surface area [BSA], body mass index, and obesity [body mass index >30 kg/m2]) and cardiovascular risk factors/comorbidities (history of smoking, history of chronic kidney disease [creatinine clearance <60 mL/min], hypertension, dyslipidaemia, metabolic syndrome, diabetes, and coronary artery disease) retrieved from patients’ medical records. We also measured several metabolic markers (levels of fasting glucose, apoB, apoA1, calcium, and phosphate) at the baseline visit. Furthermore, the apoA1/apoB ratio and calcium/phosphate ratio were calculated.
Doppler echocardiography
All patients had comprehensive Doppler echocardiography examinations performed on commercially available ultrasound machines (Philips iE33 or EPIQ7, Philips Healthcare, Best, The Netherlands) according to the current recommendations of the American Society of Echocardiography and analysed by the same laboratory.2,13 Aortic valve morphology was assessed carefully on a short-axis view, the left ventricular outflow tract (LVOT) diameter was measured at the insertion of the aortic valve leaflets in a parasternal long-axis zoom view, and stroke volume (SV) was calculated by multiplying the LVOT area by the velocity time integral obtained by pulsed wave Doppler in the LVOT. SV was then indexed by BSA to obtain the SV index. The Doppler echocardiography haemodynamic parameters used to assess AS severity were Vpeak measured by continuous wave Doppler, mean transvalvular gradient (MG) derived from the modified Bernoulli equation, and aortic valve area (AVA) calculated by the standard continuity equation and indexed by BSA to obtain the indexed AVA. LVEF was assessed by the biplane Simpson method. Finally, the annualized progression rate of AS was calculated by dividing the difference between the last follow-up and baseline values by the follow-up time of the patients ([follow-up – baseline]/follow-up time).
Statistical analyses
Continuous variables were expressed as mean ± standard deviation or median (25th-75th percentiles), and categorical variables as numbers (%). Continuous variables were tested for normality using the Shapiro-Wilk test, and then comparisons between patients with BAV and those with TAV were made using Student’s t-test or Wilcoxon’s test as appropriate. Categorical data were compared using the χ2 test or the Fisher exact test as appropriate. Univariable linear regression analyses were used to identify variables associated with AS progression rate, and multivariable linear regression analyses were conducted to identify the independent determinants of faster haemodynamic progression in BAV and TAV subcohorts. The different assumptions underlying linear regressions have been assessed: (1) the linear relationship between the dependent and independent variables was evaluated using a scatterplot, (2) the absence of multicollinearity was tested using the variance inflation factor, and (3) the normality of the regression residuals was evaluated using a histogram, and homoscedasticity was assessed using a scatterplot. Multivariable models included prespecified variables that have been previously reported to be associated with AS progression (baseline severity of AS, age, sex, obesity, hypertension, dyslipidaemia, diabetes, and coronary artery disease) as well as other variables that had a P value of <0.1 in the univariable analyses of association with AS progression in each aortic valve subcohort (BAV and TAV). Values of biological variables were normalized by a logarithmic transformation before being entered into linear regression analyses. Results were reported as standardized coefficients (β coefficients) with their respective 95% confidence intervals (95% CI). Standardized coefficients present the advantage of being unitless, which allows us to compare the different predictors and the importance of the effect of each predictor on the dependent variable (ie, AS progression rate).
Finally, analyses were performed to assess the interaction between valve morphology and factors associated with progression to confirm a differential impact of these factors according to valve morphology. Statistical analyses were performed with JMP and SPSS statistical software, and a 2-tailed P value of <0.05 was considered statistically significant.
Results
Study population
Baseline characteristics of the patients are presented in Table 1. The study population consisted of 287 patients, with 79 (28%) having BAV and 208 (72%) having TAV. Patients were followed for a median time of 3.5 years (2.0-5.1 years), with no difference between BAV and TAV patients: 3.2 (2.0-5.8) vs 3.9 (2.0-5.0) years, P = 0.47. Patients with BAV were younger (49 [39-59] vs 71 [66-75] years old, P < 0.0001), less often men (57% vs 77%, P = 0.0008), and had less comorbidities and cardiovascular risk factors (including obesity, hypertension, dyslipidaemia, metabolic syndrome, diabetes, coronary artery disease, and history of smoking, all P < 0.05). There was no significant difference between BAV and TAV with regard to echocardiographic parameters of baseline AS severity (Vpeak: 2.7 [2.4-3.0] vs 2.6 [2.4-3.0] m/s, P = 0.98; MG: 17 [13-22] vs 15 [13-20] mm Hg, P = 0.24; AVA: 1.21 [1.07-1.44] vs 1.21 [1.03-1.44] cm2, P = 0.53; and aortic valve area index: 0.67 [0.59-0.78] vs 0.64 [0.55-0.74] cm2/m2, P = 0.09). Patients with BAV had larger LVOT diameters (23.0 [20.9-24.4] vs 21.9 [20.7-23.0] mm, P = 0.003), but SV, SV index, and LVEF were similar between patients with BAV and those with TAV (all, P ≥ 0.18). At baseline, there were respectively 58 (73%), 20 (25%), and 1 (2%) patients with mild (Vpeak: 2.0-2.9 m/s), moderate (Vpeak: 3.0-3.9 m/s), and severe AS (Vpeak: ≥4.0 m/s) in patients with BAV, whereas there were 158 (76%), 44 (21%) and 6 (3%) patients with mild, moderate, and severe AS in patients with TAV (P = 0.57) (Supplemental Fig. S1A). Plasma levels of apoB, apoA1, apoB/apoA1 ratio, calcium, phosphate and calcium/phosphate ratio, and C-reactive protein were similar in BAV vs TAV (all, P ≥ 0.19 except for apoB where there was a trend for a higher level of apoB in patients with BAV: 0.83 [0.72-1.06] vs 0.80 [0.69-0.98] g/L, P = 0.08). Patients with TAV had a higher fasting glucose level at baseline compared with patients with BAV (5.6 [5.0-6.3] vs 5.2 [4.8-5.4] mmol/L, P < 0.0001).
Table 1.
Baseline characteristics of the study population
| Whole cohort (n = 287) | BAV (n = 79, 28%) | TAV (n = 208, 72%) | P value | |
|---|---|---|---|---|
| Clinical data | ||||
| Follow-up (y) | 3.5 (2.0-5.1) | 3.2 (2.0-5.8) | 3.9 (2.0-5.0) | 0.47 |
| Age (y) | 68 (58-74) | 49 (39-59) | 71 (66-75) | <0.0001 |
| Male sex, n (%) | 205 (71) | 45 (57) | 160 (77) | 0.0008 |
| BSA (m2) | 1.89 ± 0.20 | 1.86 ± 0.22 | 1.90 ± 0.19 | 0.11 |
| BMI (kg/m2) | 28 (26-31) | 26 (24-30) | 29 (26-32) | <0.0001 |
| Obesity, n (%) | 105 (37) | 19 (24) | 86 (41) | 0.007 |
| Hypertension, n (%) | 200 (70) | 27 (34) | 173 (84) | <0.0001 |
| Dyslipidaemia, n (%) | 187 (65) | 30 (38) | 157 (76) | <0.0001 |
| Metabolic syndrome, n (%) | 50 (17) | 8 (10) | 42 (20) | 0.04 |
| Diabetes, n (%) | 67 (23) | 4 (5) | 63 (30) | <0.0001 |
| Coronary artery disease, n (%) | 95 (33) | 5 (6) | 90 (43) | <0.0001 |
| History of smoking, n (%) | 173 (60) | 34 (43) | 139 (67) | 0.0002 |
| Chronic kidney disease, n (%) | 15 (5) | 2 (3) | 13 (6) | 0.25 |
| Echocardiographic data | ||||
| LVOT diameter (mm) | 22.0 (20.8-23.3) | 23.0 (20.9-24.4) | 21.9 (20.7-23.0) | 0.003 |
| Vpeak (m/s) | 2.6 (2.4-3.0) | 2.7 (2.4-3.0) | 2.6 (2.4-3.0) | 0.98 |
| MG (mm Hg) | 15 (13-21) | 17 (13-22) | 15 (13-20) | 0.24 |
| AVA (cm2) | 1.21 (1.04-1.44) | 1.21 (1.07-1.44) | 1.21 (1.03-1.44) | 0.53 |
| AVAi (cm2/m2) | 0.65 (0.57-0.75) | 0.67 (0.59-0.78) | 0.64 (0.55-0.74) | 0.09 |
| Stroke volume (SV) (mL) | 77 (69-86) | 77 (68-86) | 77 (69-85) | 0.92 |
| SV index (mL/m2) | 41 (37-45) | 43 (38-46) | 41 (36-45) | 0.18 |
| LVEF (%) | 65 (62-70) | 65 (60-68) | 65 (63-70) | 0.30 |
| Blood biomarker data | ||||
| Fasting glucose (mmol/L) | 5.3 (5.0-6.0) | 5.2 (4.8-5.4) | 5.6 (5.0-6.3) | <0.0001 |
| apoB (g/L) | 0.80 (0.70-0.99) | 0.83 (0.72-1.06) | 0.80 (0.69-0.98) | 0.08 |
| apoA1 (g/L) | 1.47 (1.32-1.69) | 1.55 (1.34-1.73) | 1.47 (1.30-1.68) | 0.19 |
| apoB/apoA1 ratio | 0.54 (0.46-0.67) | 0.55 (0.44-0.74) | 0.54 (0.46-0.66) | 0.49 |
| Calcium (mmol/L) | 2.41 (2.35-2.47) | 2.42 (2.36-2.47) | 2.40 (2.35-2.47) | 0.53 |
| Phosphate (mmol/L) | 1.03 (0.93-1.13) | 1.03 (0.80-1.14) | 1.02 (0.92-1.12) | 0.56 |
| Calcium/phosphate ratio | 2.34 (2.13-2.59) | 2.30 (2.12-2.59) | 2.35 (2.14-2.60) | 0.56 |
| C-reactive protein (mg/L) | 1.50 (0.70-3.38) | 1.35 (0.60-3.15) | 1.56 (0.77-3.47) | 0.31 |
Statistically significant P values are in bold (P < 0.05).
apoA1, apolipoprotein A1; apoB, apolipoprotein B; AVA, aortic valve area; AVAi, aortic valve area indexed by body surface area; BAV, bicuspid aortic valve; BMI, body mass index; BSA, body surface area; LVEF, left ventricular ejection fraction; LVOT, left ventricular outflow tract; MG, mean transvalvular gradient; TAV, tricuspid aortic valve; Vpeak, peak aortic jet velocity.
Haemodynamic progression rate of AS in BAV vs TAV
The annualized progression rate of Vpeak and MG are presented in Figure 1. The progression rate of Vpeak was similar between patients with BAV and those with TAV: 0.11 [0.03-0.25] and 0.12 [0.04-0.21] m/s/y (P = 0.96) (Fig. 1A). Similar results were obtained with the progression rate of MG (1.2 [0.4-4.7] and 1.9 [0.6-3.6] mm Hg/y, P = 0.50, respectively) (Fig. 1B). However, after adjusting for age, sex, AS baseline severity, hypertension, diabetes, metabolic syndrome, and chronic kidney disease, BAV was independently associated with a faster progression rate of AS (β = 0.21, 95% CI [0.04; 0.37], P = 0.02), which confirms what we previously reported.4
Figure 1.
Haemodynamic progression rate of AS according to valve morphology. Annualized progression rate of AS based on Vpeak (A) and MG (B). The red boxplots represent patients with BAV, and the blue boxplots represent patients with TAV. The box shows 25th and 75th percentiles, the median line shows the median value, the error bars show the 10th and 90th percentiles, the circles are outliers, and the asterisks are extremes. The numbers at the top of the graph are medians (25th-75th percentiles). P values are from Wilcoxon’s tests. AS, aortic stenosis; BAV, bicuspid aortic valve; MG, mean transvalvular gradient; TAV, tricuspid aortic valve; Vpeak, peak aortic jet velocity.
After a median follow-up time of 3.5 years, there were respectively 35 (44%), 29 (37%), and 15 (19%) patients with mild, moderate, and severe AS in patients with BAV and 91 (44%), 89 (43%), and 28 (13%) patients with mild, moderate, and severe AS in patients with TAV (P = 0.43) (Supplemental Fig. S1B). The proportion of patients progressing to a higher grade of severity was also similar between the 2 groups (43% in patients with BAV vs 41% in patients with TAV, P = 0.80) (Supplemental Fig. S1C).
Factors associated with faster AS progression in BAV vs TAV
In patients with BAV, higher baseline Vpeak, older age, obesity, dyslipidaemia, diabetes, and coronary artery disease were associated with the haemodynamic progression of AS (ie, annualized progression rate of Vpeak) in univariable analyses (Supplemental Table S1). When analysing the phenotypes of BAV (type 0 [no raphe] vs type I [raphe] with left coronary cusp-right coronary cusp (RCC) fusion, RCC-noncoronary cusp (NCC) fusion, or left coronary cusp-NCC fusion), only the RCC-NCC fusion subtype was associated with a faster progression of AS compared with other subtypes (Fig. 2, Table 2, Supplemental Table S1). In multivariable analysis, obesity (β = 0.25, 95% CI [0.02; 0.49], P = 0.04), diabetes (β = 0.26, 95% CI [0.04; 0.55], P = 0.02), and RCC-NCC fusion (β = 0.29, 95% CI [0.08; 0.52], P = 0.01) were independently associated with a faster progression of AS in patients with BAV. There were also trends for a significant association with higher baseline Vpeak (β = 0.16, 95% CI [−0.05; 0.40], P = 0.13) and older age (β = 0.26, 95% CI [−0.01; 0.58], P = 0.06) (Table 2). The overall regression was statistically significant (R2 = 0.37, P < 0.001).
Figure 2.
Annualized progression rate of AS in patients with BAV according to BAV phenotypes (A) and to right and noncoronary cusp fusion vs all other phenotypes of BAV (B). The box shows 25th and 75th percentiles, the median line shows the median value, the error bars show the 10th and 90th percentiles, the circles are outliers, and the asterisks are extremes. The numbers at the top of the graph are medians (25th-75th percentiles). P values are from Wilcoxon’s tests. AP, BAV type 0 with anterior-posterior orientation; AS, aortic stenosis; BAV, bicuspid aortic valve; LAT, BAV type 0 with left-right orientation; LCC-NCC, BAV type I with left and noncoronary cusp fusion; LCC-RCC, BAV type I with left and right coronary cusp fusion; RCC-NCC, BAV type I with right and noncoronary cusp fusion; Vpeak, peak aortic jet velocity.
Table 2.
Univariable and multivariable linear regression analyses for the progression of Vpeak in patients with BAV (n = 79)
| Univariable |
Multivariable |
|||
|---|---|---|---|---|
| Standardized beta (β) (95% CI) |
P value | Standardized beta (β) (95% CI) |
P value | |
| Baseline Vpeak | β = 0.22 (−0.002; 0.44) | 0.051 | β = 0.16 (−0.05; 0.40) | 0.13 |
| Age | β = 0.35 (0.14; 0.56) | 0.002 | β = 0.26 (−0.01; 0.58) | 0.06 |
| Male sex | β = 0.15 (−0.07; 0.37) | 0.19 | β = −0.001 (−0.22; 0.22) | 0.99 |
| Obesity | β = 0.27 (0.05; 0.49) | 0.02 | β = 0.25 (0.02; 0.49) | 0.04 |
| Hypertension | β = 0.21 (−0.02; 0.43) | 0.07 | β = −0.06 (−0.32; 0.19) | 0.61 |
| Dyslipidaemia | β = 0.28 (0.06; 0.50) | 0.01 | β = −0.05 (−0.32; 0.22) | 0.72 |
| Diabetes | β = 0.27 (0.05; 0.49) | 0.02 | β = 0.26 (0.04; 0.55) | 0.02 |
| Coronary artery disease | β = 0.25 (0.03; 0.47) | 0.03 | β = 0.15 (−0.07; 0.40) | 0.17 |
| BAV with RCC-NCC fusion | β = 0.32 (0.09; 0.56) | 0.007 | β = 0.29 (0.08; 0.52) | 0.01 |
Statistically significant P values are in bold (P < 0.05).
BAV, bicuspid aortic valve; CI, confidence interval; RCC-NCC, right and noncoronary cusps; Vpeak, peak aortic jet velocity.
In patients with TAV, higher baseline Vpeak and chronic kidney disease were associated with faster AS progression in univariable analysis (Supplemental Table S1). In multivariable analysis, baseline Vpeak (β = 0.14, 95% CI [0.004; 0.29], P = 0.04) and chronic kidney disease (β = 0.16, 95% CI [0.02; 0.31], P = 0.02) were the 2 sole factors significantly associated with a faster progression of AS in patients with TAV. There were also trends for fasting glucose levels (β = 0.17, 95% CI [−0.002; 0.35], P = 0.053) and for the calcium/phosphate ratio (β = −0.12, 95% CI [−0.27; 0.03], P = 0.10) to be associated with a faster progression of AS in patients with TAV (Table 3). The overall regression was statistically significant (R2 = 0.10, P = 0.04).
Table 3.
Univariable and multivariable linear regression analyses for the progression of Vpeak in patients with TAV (n = 208)
| Univariable |
Multivariable |
|||
|---|---|---|---|---|
| Standardized beta (β) (95% CI) |
P value | Standardized beta (β) (95% CI) |
P value | |
| Baseline Vpeak | β = 0.17 (0.03; 0.30) | 0.02 | β = 0.14 (0.004; 0.29) | 0.04 |
| Age | β = 0.04 (−0.10; 0.17) | 0.61 | β = 0.05 (−0.10; 0.19) | 0.52 |
| Male sex | β = 0.05 (−0.09; 0.19) | 0.45 | β = 0.04 (−0.11; 0.18) | 0.62 |
| Obesity | β = −0.03 (−0.11; 0.16) | 0.72 | β = −0.02 (−0.16; 0.13) | 0.82 |
| Hypertension | β = 0.03 (−0.11; 0.17) | 0.67 | β = 0.01 (−0.15; 0.16) | 0.93 |
| Dyslipidaemia | β = 0.02 (−0.12; 0.16) | 0.79 | β = 0.04 (−0.12; 0.19) | 0.63 |
| Diabetes | β = 0.04 (−0.10; 0.18) | 0.60 | β = −0.12 (−0.30; 0.06) | 0.18 |
| Coronary artery disease | β = 0.08 (−0.06; 0.22) | 0.26 | β = 0.03 (−0.12; 0.18) | 0.68 |
| Chronic kidney disease | β = 0.20 (0.06; 0.33) | 0.005 | β = 0.16 (0.02; 0.31) | 0.02 |
| Fasting glucose | β = 0.13 (−0.006; 0.27) | 0.06 | β = 0.17 (−0.002; 0.35) | 0.053 |
| Calcium/phosphate ratio | β = −0.12 (−0.26; 0.02) | 0.09 | β = −0.12 (−0.27; 0.03) | 0.10 |
Statistically significant P values are in bold (P < 0.05).
CI, confidence interval; TAV, tricuspid aortic valve; Vpeak, peak aortic jet velocity.
Further analyses revealed statistically significant interactions between valve morphology vs obesity (P = 0.02) and diabetes (P = 0.02). Patients with BAV and concomitant obesity had a faster progression rate of AS compared with patients with BAV and no obesity and also to patients with TAV, regardless of the presence/absence of obesity (Fig. 3A). Patients with BAV and diabetes had faster AS progression compared with other groups, but this was not statistically significant (Fig. 3B).
Figure 3.
Annualized progression rate of AS according to valve morphology and obesity (A) or diabetes (B). The red boxplots represent patients with obesity (A) or diabetes (B), and the blue boxplots represent patients without obesity (A) or diabetes (B). The box shows 25th and 75th percentiles, the median line shows the median value, the error bars show the 10th and 90th percentiles, the circles are outliers, and the asterisks are extremes. The numbers at the top of the graph are medians (25th-75th percentiles). P values are from Wilcoxon’s tests. AS, aortic stenosis; BAV, bicuspid aortic valve; TAV, tricuspid aortic valve; Vpeak, peak aortic jet velocity.
Discussion
The main findings of the present study are: (1) factors associated with AS progression may differ in BAV vs TAV; (2) obesity, diabetes, and a BAV with RCC-NCC fusion are independently associated with faster haemodynamic progression of AS in patients with BAV, whereas baseline AS severity and chronic kidney disease are independently associated with AS progression in patients with TAV.
Patients with BAV are more susceptible to develop AS and generally develop AS at a much younger age than patients with TAV.3,5 This may, at least in part, explain the differences in comorbidities between patients with BAV and those with TAV where the latter are older and have a higher prevalence of cardiovascular risk factors and comorbidities. In a previous study, we reported that BAV is independently associated with a faster progression of anatomic (ie, aortic valve calcification by computed tomography) and haemodynamic (Vpeak) severity of AS, after adjusting for age, sex, baseline AS severity, and other risk factors.4 The present study found consistent findings with the previous one where patients with BAV had a similar rate of AS progression to those with TAV in univariable analysis, but after adjusting for age and other factors, BAV was associated with faster progression. It is thus likely that the abnormal anatomic configuration of the aortic valve in patients with BAV and the ensuing increased leaflet mechanical stress and abnormal transvalvular flow pattern may contribute to the faster progression of AS in these patients.
The main objective of this study was to determine whether the cardiometabolic factors associated with AS progression might differ between BAV vs TAV. Several previous studies have identified risk factors associated with AS progression, but these studies did not perform separate analyses in BAV vs TAV. Several previous studies reported an association between older age and faster progression of AS.9,11,14, 15, 16 In the present study, age was associated with faster AS progression in patients with BAV in univariable analysis, but this association was no longer significant after adjustment for other factors in multivariable analysis. Older patients generally have more frequent cardiometabolic risk factors (ie, obesity, diabetes, dyslipidaemia, hypertension, etc), and the association between age and AS progression may thus be related to these underlying factors. Indeed, a previous study suggested that mechanisms involved in AS development might be different in younger and older patients.17 Baseline AS severity was also frequently associated with AS progression; the more severe is the baseline severity, the faster is the progression rate during follow-up. We also found this association in the patients with TAV.
In the literature, there are very few studies looking at determinants of AS progression in patients with BAV, but several studies including both patients with BAV and those with TAV reported that metabolic syndrome, elevated levels of lipoprotein (a) or oxidized phospholipids, and increased ApoB/apoA1 ratio were significantly associated with faster AS progression, especially in younger patients.7, 8, 9,18,19 Consistent with our results, Yang et al.20 reported that cardiac risk factors are associated with fast progression of AS in patients with BAV but not in those with TAV. Indeed, the associations between these cardiometabolic risk factors were generally strong in younger patients but weak or nonsignificant in older ones. In older patients, factors previously reported to be associated with AS progression were baseline AS severity and phosphocalcic metabolism disorders.21 Hence, it has been postulated that the mechanisms involved in the progression of AS might be different in younger vs older patients. However, previous studies, which included 20%-50% of patients with BAV, analyzed the effect of age but not systematically with valve morphology on AS progression. In light of the results of the present study, it is possible that the differences observed between younger vs older patients with regards to the factors associated with AS progression might, at least in part, be related to the much higher prevalence of BAV in younger patients and TAV in older ones. Our results support the hypothesis that cardiometabolic factors such as obesity, diabetes, and lipid factors may have a more important contribution in the progression of AS in patients with BAV and/or younger age.
In patients with TAV, baseline severity of AS and chronic kidney disease were independently associated with AS progression in the present study. Furthermore, there was also a trend for an independent association between the calcium/phosphate ratio and AS progression, which provides support to the role of phosphocalcic metabolism in TAV/older patients. These factors have also been associated with AS progression in previous studies.10,12,22 AS patients with TAV are generally older and more frequently have risk factors that predispose to ectopic (vascular or valvular) calcification such as chronic kidney disease or osteoporosis.12,23 Hence, age-related processes or factors of phosphocalcic metabolism appear to be the most important determinants of AS progression in patients with TAV.17,21,23, 24, 25
There are several types and phenotypes of BAV. Type I BAV according to the Sievers classification or fused BAV according to recently proposed International Consensus Statement26 is, by far, the most frequent, that is, 90%-95% of all BAV. The RCC-NCC fusion pattern represents 20%-30% of all type I or fused BAV, and this phenotype has been associated with higher risk to develop aortic valve dysfunction in people with BAV.20 However to our knowledge, the present study is the first to report that the RCC-NCC fusion phenotype is also associated with the faster progression rate of the valvular dysfunction among patients with a BAV already having AS.
Clinical implications
These findings provide support for the implementation of an aggressive lifestyle modification programme in obese patients with BAV. Therapeutic management of diabetes and patient’s compliance to treatment must also be optimized. Further studies are needed to determine the mechanisms underlying the association between obesity, diabetes, and chronic kidney disease and AS. Also patients with AS and obesity, diabetes, or chronic kidney disease should be followed more closely as the stenosis may progress rapidly in these patients. If these findings are confirmed, patients with BAV and AS might need serial echocardiography within shorter time intervals, ie, every year for moderate AS and every 2 years for mild AS. Furthermore, an important finding of our study is that patients with RCC-NCC fusion, that is, the second most frequent BAV subtype, are at higher risk of faster AS progression and should also be followed more closely by echocardiography.
Study limitations
The main limitation of this study is the limited sample size, which resulted in a small number of patients with some risk factors (obesity, diabetes, and chronic kidney disease) of faster AS progression. Hence, the results on the association of these risk factors with AS progression rate are hypothesis-generating and will need to be confirmed in a larger study with age-matched BAV and TAV patients, in order to assess the effect of the different comorbidities and risk factors in patients with similar age and risk profile. The absence of association between chronic kidney disease and AS progression in the patients with BAV may be related to the fact that this risk factor was very rare in this subgroup. This needs to be further investigated and confirmed in other studies with a larger number of patients with BAV presenting with chronic kidney disease. Also, this study included patients with mild or moderate AS, and very few patients had severe AS at baseline. However, there was no difference in the distribution of AS baseline severity between the BAV and TAV subgroups, and we adjusted for baseline severity in the multivariable analyses. For the analyses of the type of BAV, several subgroups included a small number of patients. Finally, our study mainly focused on the cardiometabolic risk factors and BAV phenotypes associated with faster AS progression. Other factors that may have an influence on AS progression, including the occurrence of pregnancy, were not investigated. Clinical data, such as the onset of symptoms, were also missing. Also, we assessed only the predictors for the haemodynamic progression of AS in the current study. It would also be interesting to assess the predictors for the anatomic progression of AS, that is, aortic valve calcification progression, in future studies. All these aforementioned factors need to be investigated in other studies with a larger number of patients with BAV.
Conclusion
The risk factors associated with the progression of AS appear to be different in patients with BAV vs patients with TAV. Indeed, the results obtained in this cohort of patients with mild-to-moderate AS at baseline suggest that patients with BAV may exhibit a faster AS progression in the presence of RCC-NCC fusion, obesity, and diabetes, whereas those with TAV have a faster progression in the presence of chronic kidney disease. Given the limited sample size and small number in some subsets of patients, these results are hypothesis-generating and need to be confirmed in larger cohorts of patients with BAV and TAV.
Acknowledgements
The authors would like to thank Isabelle Fortin, Jocelyn Beauchemin, Céline Boutin, Louise Marois, Virginie Bergeron, Danielle Tardif, Martine Poulin, Caroline Dionne, Martine Fleury, and Martine Parent for their help in data collection and management.
Ethics Statement
The research reported in this study has adhered to clinical research ethical guidelines. This study was approved by the institutional review board (Ethics committee of the Quebec Heart and Lung Institute) and all participants signed a written informed consent at the time of inclusion.
Funding Sources
This work was supported by grants MOP-114997, MOP-2455048, and FDN-143225 from Canadian Institutes of Health Research (CIHR), Ottawa, Ontario, Canada, and a grant from the Foundation of the Québec Heart and Lung Institute. MS is supported by a PhD grant from the Fonds de Recherche Québec-Santé (FRQS), Montréal, Québec, Canada. LT is supported by a PhD grant from the FRQS, Montréal, Québec, Canada. RC is supported by a “Connect Talent” research chair from Region Pays de la Loire and Nantes Metropole. MA holds a new national investigator award from the Canada Heart and Stroke Foundation, Ottawa, Ontario, Canada. PP holds the Canada Research Chair in Valvular Heart Diseases from CIHR, Ottawa, Ontario, Canada.
Disclosures
The authors have no conflicts of interest to disclose.
Footnotes
To access the supplementary material accompanying this article, visit CJC Pediatric and Congenital Heart Disease at https://www.cjcpc.ca/ and at https://doi.org/10.1016/j.cjcpc.2022.06.004
Supplementary Material
References
- 1.Go A.S., Mozaffarian D., Roger V.L., et al. Executive summary: heart disease and stroke statistics—2013 update: a report from the American Heart Association. Circulation. 2013;127:143–152. doi: 10.1161/CIR.0b013e318282ab8f. [DOI] [PubMed] [Google Scholar]
- 2.Baumgartner H., Hung J., Bermejo J., et al. Recommendations on the echocardiographic assessment of aortic valve stenosis: a focused update from the European Association of Cardiovascular Imaging and the American Society of Echocardiography. J Am Soc Echocardiogr. 2017;30:372–392. doi: 10.1016/j.echo.2017.02.009. [DOI] [PubMed] [Google Scholar]
- 3.Fedak P.W., Verma S., David T.E., et al. Clinical and pathophysiological implications of a bicuspid aortic valve. Circulation. 2002;106:900–904. doi: 10.1161/01.cir.0000027905.26586.e8. [DOI] [PubMed] [Google Scholar]
- 4.Shen M., Tastet L., Capoulade R., et al. Effect of bicuspid aortic valve phenotype on progression of aortic stenosis. Eur Heart J Cardiovasc Imaging. 2020;21:727–734. doi: 10.1093/ehjci/jeaa068. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lindman B.R., Clavel M.A., Mathieu P., et al. Calcific aortic stenosis. Nat Rev Dis Primers. 2016;2 doi: 10.1038/nrdp.2016.6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Tastet L., Capoulade R., Clavel M.A., et al. Systolic hypertension and progression of aortic valve calcification in patients with aortic stenosis: results from the PROGRESSA study. Eur Heart J Cardiovasc Imaging. 2017;18:70–78. doi: 10.1093/ehjci/jew013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Tastet L., Capoulade R., Shen M., et al. ApoB/ApoA-I ratio is associated with faster hemodynamic progression of aortic stenosis: results from the PROGRESSA (Metabolic Determinants of the Progression of Aortic Stenosis) study. J Am Heart Assoc. 2018;7 doi: 10.1161/JAHA.117.007980. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Capoulade R., Chan K.L., Yeang C., et al. Oxidized phospholipids, lipoprotein(a), and progression of calcific aortic valve stenosis. J Am Coll Cardiol. 2015;66:1236–1246. doi: 10.1016/j.jacc.2015.07.020. [DOI] [PubMed] [Google Scholar]
- 9.Capoulade R., Clavel M.A., Dumesnil J.G., et al. Impact of metabolic syndrome on progression of aortic stenosis: influence of age and statin therapy. J Am Coll Cardiol. 2012;60:216–223. doi: 10.1016/j.jacc.2012.03.052. [DOI] [PubMed] [Google Scholar]
- 10.Nguyen V., Cimadevilla C., Estellat C., et al. Haemodynamic and anatomic progression of aortic stenosis. Heart. 2015;101:943–947. doi: 10.1136/heartjnl-2014-307154. [DOI] [PubMed] [Google Scholar]
- 11.Kamath A.R., Pai R.G. Risk factors for progression of calcific aortic stenosis and potential therapeutic targets. Int J Angiol. 2008;17:63–70. doi: 10.1055/s-0031-1278283. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kearney L.G., Ord M., Buxton B.F., et al. Progression of aortic stenosis in elderly patients over long-term follow up. Int J Cardiol. 2013;167:1226–1231. doi: 10.1016/j.ijcard.2012.03.139. [DOI] [PubMed] [Google Scholar]
- 13.Baumgartner H., Hung J., Bermejo J., et al. Echocardiographic assessment of valve stenosis: EAE/ASE recommendations for clinical practice. J Am Soc Echocardiogr. 2009;22:1–23. doi: 10.1016/j.echo.2008.11.029. [DOI] [PubMed] [Google Scholar]
- 14.Nassimiha D., Aronow W.S., Ahn C., Goldman M.E. Rate of progression of valvular aortic stenosis in patients ≥ 60 years of age. Am J Cardiol. 2001;87:807–809. doi: 10.1016/s0002-9149(00)01513-7. [DOI] [PubMed] [Google Scholar]
- 15.Peter M., Hoffmann A., Parker C., Luscher T., Burckhardt D. Progression of aortic stenosis. Role of age and concomitant coronary artery disease. Chest. 1993;103:1715–1719. doi: 10.1378/chest.103.6.1715. [DOI] [PubMed] [Google Scholar]
- 16.Yap S.C., Kouwenhoven G.C., Takkenberg J.J., et al. Congenital aortic stenosis in adults: rate of progression and predictors of clinical outcome. Int J Cardiol. 2007;122:224–231. doi: 10.1016/j.ijcard.2006.11.092. [DOI] [PubMed] [Google Scholar]
- 17.Mohty D., Pibarot P., Després J.P., et al. Age-related differences in the pathogenesis of calcific aortic stenosis: the potential role of resistin. Int J Cardiol. 2010;142:126–132. doi: 10.1016/j.ijcard.2008.12.068. [DOI] [PubMed] [Google Scholar]
- 18.Capoulade R., Yeang C., Chan K.L., Pibarot P., Tsimikas S. Association of mild to moderate aortic valve stenosis progression with higher lipoprotein(a) and oxidized phospholipid levels: secondary analysis of a randomized clinical trial. JAMA Cardiol. 2018;3:1212–1217. doi: 10.1001/jamacardio.2018.3798. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Briand M., Lemieux I., Dumesnil J.G., et al. Metabolic syndrome negatively influences disease progression and prognosis in aortic stenosis. J Am Coll Cardiol. 2006;47:2229–2236. doi: 10.1016/j.jacc.2005.12.073. [DOI] [PubMed] [Google Scholar]
- 20.Yang L.T., Boler A., Medina-Inojosa J.R., et al. Aortic stenosis progression, cardiac damage, and survival: comparison between bicuspid and tricuspid aortic valves. JACC Cardiovasc Imaging. 2021;14:1113–1126. doi: 10.1016/j.jcmg.2021.01.017. [DOI] [PubMed] [Google Scholar]
- 21.Hekimian G., Boutten A., Flamant M., et al. Progression of aortic valve stenosis is associated with bone remodelling and secondary hyperparathyroidism in elderly patients—the COFRASA study. Eur Heart J. 2013;34:1915–1922. doi: 10.1093/eurheartj/ehs450. [DOI] [PubMed] [Google Scholar]
- 22.Ternacle J., Cote N., Krapf L., et al. Chronic kidney disease and the pathophysiology of valvular heart disease. Can J Cardiol. 2019;35:1195–1207. doi: 10.1016/j.cjca.2019.05.028. [DOI] [PubMed] [Google Scholar]
- 23.Tastet L., Shen M., Capoulade R., et al. Bone mineral density and progression rate of calcific aortic valve stenosis. J Am Coll Cardiol. 2020;75:1725–1726. doi: 10.1016/j.jacc.2020.01.053. [DOI] [PubMed] [Google Scholar]
- 24.Akat K., Kaden J.J., Schmitz F., et al. Calcium metabolism in adults with severe aortic valve stenosis and preserved renal function. Am J Cardiol. 2010;105:862–864. doi: 10.1016/j.amjcard.2009.10.065. [DOI] [PubMed] [Google Scholar]
- 25.Palta S., Pai A.M., Gill K.S., Pai R.G. New insights into the progression of aortic stenosis: implications for secondary prevention. Circulation. 2000;101:2497–2502. doi: 10.1161/01.cir.101.21.2497. [DOI] [PubMed] [Google Scholar]
- 26.Michelena H.I., Della Corte A., Evangelista A., et al. International consensus statement on nomenclature and classification of the congenital bicuspid aortic valve and its aortopathy, for clinical, surgical, interventional and research purposes. Ann Thorac Surg. 2021;112:e203–e235. doi: 10.1016/j.athoracsur.2020.08.119. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.