Citations

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.

AbstractBackgroundElevated transmitral gradient post transcatheter mitral valve edge‐to‐edge repair (TEER) has been associated with worse outcomes. Whether an elevated baseline transmitral diastolic mean gradient (MG) ≥5 mmHg is associated with hemodynamic outcomes after TEER is unknown.MethodsA total of 164 consecutive patients undergoing TEER at Mayo Clinic between June 2014 and May 2018 were analyzed in this retrospective study. Baseline demographics, as well as clinical, echocardiographic, and procedural data were obtained. Data on direct left atrial pressure (LAP) before and after TEER were recorded. Logistic regression models were constructed to evaluate the association between preprocedure transmitral diastolic mean gradient (pre‐MG) and (1) improvement in LAP following TEER, (2) postprocedure transmitral diastolic mean gradient (post‐MG). A decrease in LAP post TEER was considered an improvement in hemodynamic response. Pre‐MG was categorized as: ≥5 and <5 mmHg.ResultsMedian age of the cohort was 81.5 years (Q1: 76.3, Q3: 87) and 34% were female. At baseline, median transmitral diastolic MG was 4 mmHg (Q1: 3, Q3: 5) and median LAP was 19 mmHg (Q1:16, Q3: 23.5). In a multivariable model, adjusted for age and sex, patients with pre‐MG ≥ 5 mmHg were less likely to see an improvement in LAP post TEER (adjusted odds ratio [aOR]: 0.22, 95% confidence interval [CI]: 0.09, 0.55; p = 0.001) and more likely to have elevated post‐MG (aOR; 7.08, 95% CI: 2.93, 17.13; p < 0.001).ConclusionHigher pre‐MG (≥5 mmHg) was associated with a lower reduction in LAP and higher residual transmitral gradient following TEER suggesting other potential contributors to increased LAP besides mitral regurgitation as a cause of elevated baseline MG.

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.

Background The aim of this study was to establish prognostic hemodynamic parameters in patients with mitral stenosis secondary to mitral annular calcification. Methods and Results A retrospective cohort of 105 patients undergoing transseptal catheterization for hemodynamic evaluation of mitral annular calcification–related mitral stenosis between 2004 and 2020 was studied. Mitral valve gradient (MVG) and mitral valve area (MVA; calculated by the Gorlin formula) were measured using direct left atrial and left ventricular pressures. The median age of the patients was 70.3 years (58.4–76.7 years), and 53.3% were women. The median MVA was 1.7 cm 2 (1.3–2.3 cm 2 ) and MVG was 7.3 mm Hg (5.3–10.3 mm Hg); left ventricular end‐diastolic pressure was 17.6±28.3 mm Hg. During a median of 2.1 years (0.7–4.5 years), there were 63 deaths; 1‐ and 5‐year survival were 76% and 40%, respectively. There was no association between left ventricular end‐diastolic pressure and survival. After adjusting for age and comorbidities, both MVA (hazard ratio [HR], 0.50 per cm 2 ; 95% CI, 0.34–0.73) and MVG (HR, 1.1 per mm Hg; 95% CI, 1.05–1.20) were independent predictors of death. Atrial fibrillation was also independently associated with mortality. When added to a combined model, MVA remained associated with death (HR, 0.51 per cm 2 ; 95% CI, 0.33–0.79) while MVG was not. Conclusions In patients with mitral annular calcification–related mitral stenosis, survival was poor. MVA and MVG were independently associated with death, but MVA was a better predictor of outcomes.

AbstractBackgroundMitral transcatheter edge‐to‐edge repair (MTEER) is an established therapeutic approach for mitral regurgitation (MR). Functional mitral regurgitation originating from atrial myopathy (A‐FMR) has been described.ObjectivesWe sought to assess the clinical, echocardiographic and hemodynamic considerations in A‐FMR patients undergoing MTEER.MethodsFrom 2014 to 2020, patients undergoing MTEER for degenerative MR (DMR), functional MR (FMR), and mixed MR were assessed. A‐FMR was defined by the presence of MR > moderate in severity; left ventricular (LV) ejection fraction (LVEF) ≥ 50%; and severe left atrial (LA) enlargement in the absence of LV dysfunction, leaflet pathology, or LV tethering. The diagnosis of A‐FMR (vs. ventricular‐FMR [V‐FMR]) was confirmed by three independent echocardiographers. Baseline characteristics, procedural outcomes as well as clinical and echocardiographic follow‐up are reported. Device success was defined as final MR grade ≤ moderate; MR reduction ≥1 grade; and final transmitral gradient <5 mmHg.Results306 patients underwent MTEER, including DMR (62%), FMR (19%), and mixed MR (19%). FMR cases included 37 (63.8%) V‐FMR and 21 (36.2%) A‐FMR. Tricuspid regurgitation (≥ moderate) was higher in A‐FMR (80.1%) compared to V‐FMR (54%) and DMR (42%). Device success did not significantly differ between A‐FMR and V‐FMR (57% vs. 73%, p = 0.34) or DMR (57% vs. 64%, p = 1.0). The A‐FMR cohort was less likely to achieve ≥3 grades of MR reduction compared to V‐FMR (19% vs. 54%, p = 0.01) and DMR (19% vs. 49.7%, p = 0.01). Patients with V‐FMR and DMR demonstrated significant reductions in mean left atrial pressure (LAP) and peak LA V‐wave, though A‐FMR did not (LAP −0.24 ± 4.9, p = 0.83; peak V‐wave −1.76 ± 9.1, p = 0.39). In follow‐up, echocardiographic and clinical outcomes were similar.ConclusionsIn patients undergoing MTEER, A‐FMR represents one‐third of FMR cases. A‐FMR demonstrates similar procedural success but blunted acute hemodynamic responses compared with DMR and V‐FMR following MTEER. Dedicated studies specifically considering A‐FMR are needed to discern the optimal therapeutic approaches.

Introduction: Multiple supervised machine learning (ML) models have been used to assess the outcomes in patients who underwent transcatheter aortic valve replacement (TAVR) procedure, however, supervised ML requires significant expert time for annotation and labeling. Unsupervised ML can provide insight into the dataset without this process. Hypothesis: We hypothesized that unsupervised k-means ML can identify distinct phenogroups in TAVR patients that can predict prognosis without a priori knowledge. Methods: A retrospective study of patients who underwent TAVR (Jan 2012-Dec 2017) at Mayo Clinic sites was performed. Baseline demographics, EKG, cardiac computed tomography, and echocardiographic data were abstracted. Variables with ≥ 20% missing data were excluded. Prior to the k-means clustering algorithm, principal component analysis was used for dimensionality reduction. Input variables were analyzed according to k-means determined clusters. Kaplan-Meier survival analysis was used to assess the survival of each cluster. Results: A total of 1071 consecutive patients were included in the final analysis. A total of 141 unique variables were used. The mean age was 80.7±8.6 years, 58.2% were male. Patients were divided into 2 distinct phenogroups. In the two phenogroups, cluster 0 (n=639) has significantly better survival than cluster 1 (n= 432) (log-rank p=0.0002) (Figure 1). Cluster 1 has features of low flow-low gradient (LFLG) hemodynamic profile, including lower systolic blood pressure, mean aortic valve gradient, peak aortic valve velocity, and worse LV ejection fraction. Conclusions: Unsupervised ML can identify distinct phenotype features with prognostic significance in TAVR patients. Our results suggest that patients with LFLG hemodynamic features are intrinsically different from other TAVR patients and require more attention to avoid adverse outcomes.

Introduction: Conduction disturbance after transcatheter aortic valve replacement (TAVR) remains a common complication. Predictive tools to identify conduction disturbance requiring pacing are limited. Our main objective was to develop a deep learning model to predict the need for a permanent pacemaker. Hypothesis: An electrocardiogram (ECG) based deep learning algorithm can predict the need for permanent pacemaker post TAVR. Methods: We evaluated patients who had TAVR at Mayo Clinic between June 2010 and May 2021. Digital ECGs done on the TAVR date or within 24 hours post procedure were partitioned into training, validation, and testing datasets. We trained a deep learning algorithm on the training data and optimized hyperparameters against the validation data. All model performance metrics are based on the reserved test data that were estimated once model architecture was optimized. Need for permanent pacemaker, defined as pacemaker placement due to development of conduction disturbance post TAVR and at least 1% ventricular pacing on device interrogation done at least 2 weeks post pacemaker implantation, was the training target. Results: A total of 3021 patients were evaluated for inclusion and 2,407 cases were available for modeling (exclusions: prior pacemaker (n=419), unsuccessful TAVR (n=27) and no ECG within the pre-specified period (n=168)). Overall, the median age was 82 (Q1: 76, Q3: 86) and 41% were female. In the withheld test data, 15% had a permanent pacemaker with at least 1% ventricular pacing. The algorithm detected the need for pacemaker in the test set with an AUC of 0.83 (95% CI: 0.73 to 0.92). Accuracy, sensitivity, specificity, positive and negative predictive were 80%, 72%, 81%, 41% and 94%, respectively. Conclusions: This study demonstrates the ability of a deep learning model based on ECG data to assist in making the decision to implant a pacemaker following TAVR with a high negative predictive value. Larger validation studies are warranted.

Background: Transcatheter aortic valve replacement (TAVR) is an approved alternative to surgical aortic valve replacement. However, as the clinical indication and adoption of TAVR expands, it remains important to identify predictors of mortality after TAVR. We aimed to study the impact of aortic valve calcium score on long term mortality following TAVR in a large patient population. Methods: We included consecutive patients who successfully underwent TAVR from June 2010 – June 2019 across all Mayo Clinic sites. Patients were followed through February 2021. Aortic valve calcium scores were obtained from preoperative computed tomography angiography of the chest. Additional data was abstracted from medical records. Cox-proportional hazard regression models were employed to evaluate the independent effect of aortic valve calcium score on mortality. Results: A total of 1988 patients were evaluated in the final analysis. Forty-two percent were women, median age was 83 years (Q1: 77, Q3: 87), 16% received a permanent pacemaker following TAVR and 83% received an Edwards Sapien valve. We demonstrate an incremental increase in mortality risk as aortic valve calcium score values increased after adjusting for age, gender, pacemaker implantation, left bundle branch block, and Charlson Comorbidity Index. Selected calcium score cut-points with adjusted hazard ratios (aHR) are displayed: 1200 AU (aHR: 1.13, 95% CI 1.06, 1.20); 2000 AU (aHR: 1.22, 95% CI 1.09, 1.35); 3000 AU (aHR: 1.34, 95% CI: 1.14, 1.58). Conclusion: This study demonstrates an association between aortic valve calcium score and long-term mortality in a large patient population. This highlights the potential predictive value of the calcium score in preoperative planning and may provide clinicians with an additional measure for risk stratification prior to TAVR.