Structural and Functional Correlates of Gradient-Area Patterns in Severe Aortic Stenosis and Normal Ejection Fraction

Prognostic Implications of Discordant Low-Gradient Severe Aortic Stenosis: Comprehensive Analysis of a Large Multicenter Registry

Background

Up to 30% of patients with severe aortic stenosis (SAS) (indexed aortic valve area [AVAi] <0.6 cm2/m2) exhibit low-transvalvular gradient despite normal ejection fraction. There is intense debate regarding the prognostic significance of this entity.

Objectives

The purpose of this study was to compare the outcome of patients with discordant low-gradient SAS (DLG-SAS) vs moderate aortic stenosis (MAS) and high-gradient SAS (HG-SAS).

Methods

We used the BEL-F-ASt (Belgium-France-Aortic Stenosis) registry including consecutive patients with AS. Survival was compared overall and after matching (inverse probability weighting and propensity-score matching) for clinical and imaging variables. The analysis was first performed in the overall population (n = 2,582) and then in the population of unoperated patients (n = 1,812).

Results

After-inverse probability weighting-matching, the 3 groups were balanced. Five-year survival was better in MAS than in DLG-SAS and HG-SAS-patients (58.9% vs 47% vs 41.2%, P < 0.001). Similar results were obtained in unoperated patients (54.1% vs 37.9% vs 28.1%, P < 0.001). To explore the impact of MG (≤40 vs >40 mmHg) and AVAi (<0.6 vs ≥0.6 cm2/m2) on outcomes, survival of propensity score-matched cohorts of HG-vs DLG-SAS and MAS vs DLG-SAS were compared. After matching for MG, survival was better in MAS than in DLG-SAS (52% vs 40%, P < 0.001). After matching for AVAi, survival was better in DLG-SAS than in HG-SAS patients (45% vs 33%, P < 0.001).

Conclusions

Survival of DLG-SAS is better than that of HG-SAS and worse than that of MAS patients. At comparable MG, the lower the AVAi, the worse the prognosis, whereas at comparable AVAi, the higher the MG, the worse the prognosis. These data argue that DLG-SAS is an intermediate form in the disease continuum.

Impaired Left Ventricular Circumferential Midwall Systolic Performance Appears Linked to Depressed Preload, but Not Intrinsic Contractile Dysfunction or Excessive Afterload, in Paradoxical Low-Flow/Low-Gradient Severe Aortic Stenosis

Paradoxical low-flow/low-gradient aortic stenosis (P-LFLG-AS) occurs in about one-third of patients with severe AS and preserved left ventricular (LV) ejection fraction (EF). Our aim was to differentiate between altered LV loading conditions and contractility as determinants of subtle LV systolic dysfunction in P-LFLG-AS. We retrospectively analyzed medical records of patients with isolated severe degenerative AS and preserved EF (30 subjects with P-LFLG-AS and 30 patients with normal-flow/high-gradient severe AS (NFHG-AS)), without relevant coexistent diseases (e.g., diabetes, coronary artery disease and chronic kidney disease) or any abnormalities which could account for a low-flow state. Patients with P-LFLG-AS and NFHG-AS did not differ in aortic valve area index and most clinical characteristics. Compared to NFHG-AS, subjects with P-LFLG-AS exhibited smaller LV end-diastolic diameter (LVd) (44 ± 5 vs. 54 ± 5 mm, p < 0.001) (consistent with lower LV preload) with pronounced concentric remodeling, higher valvulo-arterial impedance (3.8 ± 1.1 vs. 2.2 ± 0.5 mmHg per mL/m2, p < 0.001) and diminished systemic arterial compliance (0.45 ± 0.11 vs. 0.76 ± 0.23 mL/m2 per mmHg, p < 0.001), while circumferential end-systolic LV midwall stress (cESS), an estimate of afterload at the LV level, was similar in P-LFLG-AS and NFHG-AS (175 ± 83 vs. 198 ± 69 hPa, p = 0.3). LV midwall fractional shortening (mwFS) was depressed in P-LFLG-AS vs. NFHG-AS (12.3 ± 3.5 vs. 14.7 ± 2.9%, p = 0.006) despite similar EF (61 ± 6 vs. 59 ± 8%, p = 0.4). By multiple regression, the presence of P-LFLG-AS remained a significant predictor of lower mwFS compared to NFHG-AS upon adjustment for cESS (β ± SEM: −2.35 ± 0.67, p < 0.001); however, the significance was lost after further correction for LVd (β = −1.10 ± 0.85, p = 0.21). In conclusion, the association of P-LFLG-AS with a lower cESS-adjusted mwFS, an index of afterload-corrected LV circumferential systolic function at the midwall level, appears secondary to a smaller LV end-diastolic cavity size according to the Frank−Starling law. Thus, low LV preload, not intrinsic contractile dysfunction or excessive afterload, may account for impaired LV circumferential midwall systolic performance in P-LFLG-AS.

Harnessing feature extraction capacities from a pre-trained convolutional neural network (VGG-16) for the unsupervised distinction of aortic outflow velocity profiles in patients with severe aortic stenosis

Aims

Hypothesizing that aortic outflow velocity profiles contain more valuable information about aortic valve obstruction and left ventricular contractility than can be captured by the human eye, features of the complex geometry of Doppler tracings from patients with severe aortic stenosis (AS) were extracted by a convolutional neural network (CNN).

Methods and results

After pre-training a CNN (VGG-16) on a large data set (ImageNet data set; 14 million images belonging to 1000 classes), the convolutional part was employed to transform Doppler tracings to 1D arrays. Among 366 eligible patients [age: 79.8 ± 6.77 years; 146 (39.9%) women] with pre-procedural echocardiography and right heart catheterization prior to transcatheter aortic valve replacement (TAVR), good quality Doppler tracings from 101 patients were analysed. The convolutional part of the pre-trained VGG-16 model in conjunction with principal component analysis and k-means clustering distinguished two shapes of aortic outflow velocity profiles. Kaplan-Meier analysis revealed that mortality in patients from Cluster 2 (n = 40, 39.6%) was significantly increased [hazard ratio (HR) for 2-year mortality: 3; 95% confidence interval (CI): 1-8.9]. Apart from reduced cardiac output and mean aortic valve gradient, patients from Cluster 2 were also characterized by signs of pulmonary hypertension, impaired right ventricular function, and right atrial enlargement. After training an extreme gradient boosting algorithm on these 101 patients, validation on the remaining 265 patients confirmed that patients assigned to Cluster 2 show increased mortality (HR for 2-year mortality: 2.6; 95% CI: 1.4-5.1, P-value: 0.004).

Conclusion

Transfer learning enables sophisticated pattern recognition even in clinical data sets of limited size. Importantly, it is the left ventricular compensation capacity in the face of increased afterload, and not so much the actual obstruction of the aortic valve, that determines fate after TAVR.