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Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Introduction: Cardiac amyloidosis (CA) has been suggested to be common (up to 16%) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). CA has poorer outcomes and its assessment in all TAVR patients may be costly and challenging. Hypothesis: CA may be screened for with an artificial intelligence (AI) clinical predictive model applied to pre-TAVR ECGs, and high probability (>50%) for CA may be associated with worse clinical outcomes. Methods: In this retrospective analysis of the Mayo institutional National Cardiovascular Disease Registry (NCDR)-TAVR, patients undergoing a TAVR between Jan-2012 and Dec-2017 were included. Pre-TAVR ECGs were analyzed by the AI predictive model for CA embedded in the EMR. EMRs were reviewed to assess for a clinical diagnosis of CA in those identified as high probability (>50%) by the AI tool. Clinical outcomes on 1 year follow-up were extracted from the NCDR-TAVR database and Kaplan-Meier curves were created to compare patients with high CA probability (≥50%) versus those with low probability (<50%). Results: Of 1070 patients who underwent TAVR (mean age 81.1± 8.5 years, 58.2% male), 263 (24.6%) had ≥50% probability for CA on pre-procedure ECG. Only 18 (1.7%) of these had clinical diagnosis of CA. In the survival analysis, high probability of CA by AI tool was associated with higher all-cause mortality (HR 1.60, 95%CI 1.09-2.34, p=0.01) and greater HF admissions (HR 1.59, 95%CI 1.08-2.35, p<0.01). Neither TIA/stroke nor myocardial infarction were statistically significant. MACE (TIA/stroke, myocardial infarction, heart failure admissions) was higher in the ≥50% CA probability group (HR 1.68, 95%CI 1.17-2.40, p<0.01), (Figure) . Conclusion: CA is clinically underdiagnosed in patients undergoing TAVR. AI applied to pre-TAVR ECGs suggesting higher probability for CA identifies a subgroup at higher risk of clinical events, who may benefit from further diagnostic evaluation for CA.

Introduction: Doppler mean gradient (MG) can underestimate the severity of aortic stenosis (AS) in patients with atrial fibrillation (AF) compared to patients in sinus rhythm (SR). Patients with AF and severe AS may experience delayed diagnosis and more advanced disease at time of referral for transcatheter aortic valve replacement (TAVR). Methods: Patients who underwent TAVR from 2013 to 2017 for native valve severe AS were identified from an institutional database. MG and aortic valve calcium score (AVCS) at time of referral were compared in patients in AF and SR. Retrospective theoretical AVCS in AF patients were derived assuming an average progression of 152 AU/year (published data). Results: There were 820 patients included; mean age was 81.3+/- 8.2 years and 41.6% were female. AF was present in 356 patients at time of referral. Patients in AF were older (82.2 vs. 80.5, p = 0.003), had lower MG compared to SR patients (42.0 vs. 44.9, p = 0.002) and a lower peak velocity (4.1 vs. 4.2, p = 0.010) with a similar indexed aortic valve area (0.4 vs. 0.4, p = 0.17). Stratified by sex, the median calcium score for AF patients was higher (by around 300 AU) among both males (AF 2850.0 vs. SR 2561.0, p = 0.044) and females (AF 1942.0 vs. 1610.5, p = 0.025) ( figure 1 ). A density plot of retrospective theoretical AVCS in AF patients (projected assuming referral to TAVR approximately two years prior) resulted in nearly identical median AVCS between the two cohorts ( figure 2 ). Conclusions: Older age and higher AVCS in patients with AF compared to SR suggests that AS was both underestimated and more advanced at time of referral to TAVR. Patients in AF may have severe AS as early as 2 years prior to TAVR referral.

Abstract Introduction Lipoprotein(a) [Lp(a)] is associated with an increased incidence of aortic stenosis. Bioprosthetic aortic valve degeneration and native aortic stenosis share similar pathological mechanisms. Evidence regarding the role of serum Lp(a) concentrations in bioprosthetic aortic valve degeneration is lacking. Purpose To evaluate the association between serum Lp(a) concentrations and bioprosthetic aortic valve degeneration. Methods In this retrospective multicenter study, consecutive patients who underwent a bioprosthetic aortic valve replacement between Jan-2010 and Dec-2020 and had a preoperatory serum Lp(a) measurement were included. A baseline transthoracic echocardiography (TTE) was performed following the aortic valve replacement and a follow-up TTE was performed at least 24 months after the baseline study to determine the presence of bioprosthetic valve degeneration. Significant degeneration was defined as: (a) an increase &gt;10 mmHg in mean bioprosthetic aortic valve gradient from baseline status + a decrease in effective orifice area + a decrease in Doppler velocity index + exclusion of clinically thrombotic leaflet thickening, OR (b) new moderate or severe prosthetic aortic regurgitation (if the main component was periprosthetic, then it was not considered). Lp(a) concentrations were compared between patients with and without degeneration and regression analysis was conducted to investigate the association between bioprosthetic valve degeneration and Lp(a) levels. Results In total, 211 cases were included (mean age 74.1 ±9.4 years, 72.0% males, 29.9% transcatheter aortic valve replacements) (Figure 1). Median time between baseline and follow-up TTE was 5.0 (IQR 3.7) years. Bioprostheses degeneration was observed in 33 (15.6%) patients at follow-up. Median serum levels of Lp(a) were significantly higher in the patients affected by degeneration versus non-affected cases (50.0 vs 15.7 mg/dl, p=0.003). In the regression analysis, high Lp(a) levels (≥30 mg/dl) were associated with degeneration both in a univariate analysis (OR 4.8, 95%CI 2.2-10.9, p&lt;0.001) and multivariate analysis adjusted by other risk factors for bioprostheses degeneration (age, sex, hypertension, smoking, patient prosthesis mismatch, creatinine levels, and body surface area) (OR 5.2, 95%CI 2.1-12.8, p&lt;0.001). Conclusion Serum Lp(a) concentrations seem to be a risk factor for bioprosthetic aortic valve degeneration (Figure 2). There is an increasing need to accurately predict bioprosthetic aortic valve degeneration and to develop novel methods and treatments to increase their durability. Prospective studies are needed to confirm these findings and to investigate whether lowering Lp(a) could slow bioprostheses degradation.Population characteristicsLp(a) and bioprostheses degeneration

Objectives Lipoprotein(a) (Lp(a)) is associated with an increased incidence of native aortic stenosis, which shares similar pathological mechanisms with bioprosthetic aortic valve (bAV) degeneration. However, evidence regarding the role of Lp(a) concentrations in bAV degeneration is lacking. This study aims to evaluate the association between Lp(a) concentrations and bAV degeneration. Methods In this retrospective multicentre study, patients who underwent a bAV replacement between 1 January 2010 and 31 December 2020 and had a Lp(a) measurement were included. Echocardiography follow-up was performed to determine the presence of bioprosthetic valve degeneration, which was defined as an increase >10 mm Hg in mean gradient from baseline with concomitant decrease in effective orifice area and Doppler Velocity Index, or new moderate/severe prosthetic regurgitation. Levels of Lp(a) were compared between patients with and without degeneration and Cox regression analysis was performed to investigate the association between Lp(a) levels and bioprosthetic valve degeneration. Results In total, 210 cases were included (mean age 74.1±9.4 years, 72.4% males). Median time between baseline and follow-up echocardiography was 4.4 (IQR 3.7) years. Bioprostheses degeneration was observed in 33 (15.7%) patients at follow-up. Median serum levels of Lp(a) were significantly higher in patients affected by degeneration versus non-affected cases: 50.0 (IQR 72.0) vs 15.6 (IQR 48.6) mg/dL, p=0.002. In the regression analysis, high Lp(a) levels (≥30 mg/dL) were associated with degeneration both in a univariable analysis (HR 3.6, 95% CI 1.7 to 7.6, p=0.001) and multivariable analysis adjusted by other risk factors for bioprostheses degeneration (HR 4.4, 95% CI 1.9 to 10.4, p=0.001). Conclusions High serum Lp(a) is associated with bAV degeneration. Prospective studies are needed to confirm these findings and to investigate whether lowering Lp(a) levels could slow bioprostheses degradation.

Introduction: Post-transcatheter aortic valve replacement (TAVR) outcome of patients is an important research topic. To accurately assess post-TAVR mortality, we examined a family of new echo-parameters (augmented systolic blood pressure (AugSBP) and arterial mean pressure parameters (AugMAP)) derived from blood pressure and aortic valve gradient ( Figure 1 ). Methods: Patients in the Mayo Clinic National Cardiovascular Diseases Registry-TAVR database who underwent TAVR between January 1, 2012, and June 30, 2017, were identified to retrieve baseline clinical, echocardiographic, and mortality data. The median of AugSBP and AugMAP were used to stratify patients in Kaplan-Meier analysis. Results: The final cohort contained 974 patients with a mean age of 81.4±8.3 years old, and 56.6% were male. The mean Society of Thoracic Surgeons risk score was 8.2±5.2. The median follow-up duration was 354 days, and the one-year all-cause mortality rate was 14.2%. Detailed characteristics are summarized in Table 1. AugMAP1 < 102.5 mmHg (median) was associated with a 3-fold risk of all-cause mortality post-TAVR at 1 year (hazard ratio 3.0, 95%confidence interval 2.0-4.5, p<0.0001)( Figure 1 ). Conclusions: Augmented mean arterial pressure provides clinicians with a simple but effective approach to quickly identify patients at risk and potentially improve post-TAVR prognosis.

Background: Post-transcatheter aortic valve replacement (TAVR) patient outcome is an important research topic. To accurately assess post-TAVR mortality, we examined a family of new echo parameters (augmented systolic blood pressure (AugSBP) and arterial mean pressure (AugMAP)) derived from blood pressure and aortic valve gradients. Methods: Patients in the Mayo Clinic National Cardiovascular Diseases Registry-TAVR database who underwent TAVR between 1 January 2012 and 30 June 2017 were identified to retrieve baseline clinical, echocardiographic and mortality data. AugSBP, AugMAP and valvulo-arterial impedance (Zva) (Zva) were evaluated using Cox regression. Receiver operating characteristic curve analysis and the c-index were used to assess the model performance against the Society of Thoracic Surgeons (STS) risk score. Results: The final cohort contained 974 patients with a mean age of 81.4 ± 8.3 years old, and 56.6% were male. The mean STS risk score was 8.2 ± 5.2. The median follow-up duration was 354 days, and the one-year all-cause mortality rate was 14.2%. Both univariate and multivariate Cox regression showed that AugSBP and AugMAP parameters were independent predictors for intermediate-term post-TAVR mortality (all p < 0.0001). AugMAP1 < 102.5 mmHg was associated with a 3-fold-increased risk of all-cause mortality 1-year post-TAVR (hazard ratio 3.0, 95%confidence interval 2.0–4.5, p < 0.0001). A univariate model of AugMAP1 surpassed the STS score model in predicting intermediate-term post-TAVR mortality (area under the curve: 0.700 vs. 0.587, p = 0.005; c-index: 0.681 vs. 0.585, p = 0.001). Conclusions: Augmented mean arterial pressure provides clinicians with a simple but effective approach to quickly identify patients at risk and potentially improve post-TAVR prognosis.

Background: Prior studies have reported conflicting results of persistent iatrogenic atrial septal defect (iASD) and its impact following a transcatheter edge-to-edge repair (TEER) procedure. This study aims to evaluate the incidence of iASD and its clinical and hemodynamic impact after a TEER. Methods: Consecutive patients who underwent a TEER procedure from June 2014 to September 2020 at the Mayo Clinic were identified. The presence of iASD was retrospectively identified on post-procedure transthoracic echocardiography (TTE) to group patients into an iASD+ group and an iASD− group for comparison of prognosis and cardiac function. Results: A total of 316 patients were included; the mean age was 79.1 ± 9.1 years, and 67.7% were male. Persistent iASD was diagnosed in 108 (34.2%) patients. There was no difference concerning all-cause mortality, heart failure hospitalization, and stroke/TIA between groups at follow-up (median follow-up of 9 months). Post-procedure TTE demonstrated no differences regarding right ventricle (RV) and left ventricle (LV) dimensions and function, including TAPSE (15.2 ± 4.6 vs. 15.4 ± 5.5 mm, p = 0.875), and LV ejection fraction (51.1 ± 14.0% vs. 51.3 ± 13.9%, p = 0.933). However, patients with iASD had higher RV systolic pressure (48.7 ± 14.4 vs. 45.5 ± 14.5 mmHg, p = 0.042) compared with patients without iASD. Conclusion: Notwithstanding higher RV pressures, patients with persistent iASD had no hemodynamic compromise and an equal prognosis compared with those without a residual atrial defect after a TEER procedure. These findings support the mid-term safety of procedures in which an interatrial defect needs to be created and would argue against the need for interventional closure.

Abstract Background Topological data analysis (TDA) is the state-of-the-art unsupervised machine learning framework that can provide insight into the dataset and visualize condensed information via the topological network graph. This robust approach was never used to assess the heterogeneous MitraClip population. Purpose We aim to develop a TDA model that will identify prognostically-distinct phenogroups in MitraClip patients without a priori knowledge of the population and their outcomes. Method Patients who underwent MitraClip (June 2014-September 2020) at Mayo Clinic sites were identified from the institutional database for baseline and follow-up data. Thirteen variables were used for TDA. The topological network graph was created using the Python Scikit-TDA Kepler-Mapper package (v. 2.0.1), and clustering was performed at the graph level with Louvain's modularity method. Kaplan-Meier survival analysis was used to assess the all-cause mortality endpoint of each cluster identified in an unsupervised manner. The dataset with cluster labels was also used to train a Light Gradient Boosted Machine model, and SHapley Additive exPlanations (SHAP) analysis was applied to determine the feature importance. Results A total of 389 consecutive patients were included in the final analysis and two major clusters consisting of 384 patients were identified. The mean age was 80.3±8.7 years; 256 (65.8%) were male. The mean Society of Thoracic Surgeons Mitral Valve Replacement risk score was 9.6±6.9%. Fifty-five (14.5%) patients died during the mean follow duration (185 days). Kaplan-Meier analysis showed significant survival differences among the two clusters (HR: 2.38; 95% CI: 1.39–4.06, p=0.001; Figure 1). Clusters 1 (n=195) was associated with &gt; mild residual mitral regurgitation and worse survival performance and was characterized with worse tricuspid regurgitation severity, a higher proportion of patients with atrial fibrillation/flutter, anterior leaflet prolapse, and mitral annular/leaflet calcification, as summarized in Table 1. Conclusion TDA can identify distinct phenotype clusters with prognostic significance in MitraClip patients based on mitral valve morphology and clinical risk factors. This simple model can facilitate clinical risk stratification for MitraClip patients regarding procedural success and survival performance. Funding Acknowledgement Type of funding sources: None.

Background: Transcatheter aortic valve replacement (TAVR) is now an approved alternative to surgical aortic valve replacement for the treatment of severe aortic stenosis. As the clinical adoption of TAVR expands, it remains important to identify predictors of mortality after TAVR. We aimed to evaluate the impact of sex differences in aortic valve calcium score (AVCS) on long-term mortality following TAVR in a large patient sample. Methods: We included consecutive patients who successfully underwent TAVR for treatment of severe native aortic valve stenosis from June 2010 to May 2021 across all US Mayo Clinic sites with follow-up through July 2021. AVCS values were obtained from preoperative computed tomography of the chest. Additional clinical data were abstracted from medical records. Kaplan-Meier curves and Cox-proportional hazard regression models were employed to evaluate the effect of AVCS on long-term mortality. Results: A total of 2543 patients were evaluated in the final analysis. Forty-one percent were women, median age was 82 years (Q1: 76, Q3: 86), 18.4% received a permanent pacemaker following TAVR, and 88.5% received a balloon expandable valve. We demonstrate an increase in mortality risk with higher AVCS after multivariable adjustment ( P <0.001). When stratified by sex, every 500-unit increase in AVCS was associated with a 7% increase in mortality risk among women (adjusted hazard ratio, 1.07 [95% CI, 1.02–1.12]) but not in men. Conclusions: We demonstrate a notable sex difference in the association between AVCS and long-term mortality in a large TAVR patient sample. This study highlights the potential value of AVCS in preprocedural risk stratification, specifically among women undergoing TAVR. Additional studies are needed to validate this finding.