Citations

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.

Clinicians caring for neonates with congenital heart disease encounter challenges in clinical care as these infants await surgery or are evaluated for further potential interventions. The newborn with heart disease can present with significant pathophysiologic heterogeneity and therefore requires a personalized therapeutic management plan. However, this complex field of neonatal–cardiac hemodynamics can be simplified. We explore some of these clinical quandaries and include specific sections reviewing the anatomic challenges in these patients. We propose this to serve as a primer focusing on the hemodynamics and therapeutic strategies for the preoperative neonate with systolic dysfunction, diastolic dysfunction, excessive pulmonary blood flow, obstructed pulmonary blood flow, obstructed systemic blood flow, transposition physiology, and single ventricle physiology.

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 > 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 TAILOR‐PCI (Tailored Antiplatelet Initiation to Lessen Outcomes due to decreased Clopidogrel Response After Percutaneous Coronary Intervention) studied genotype‐guided selection of antiplatelet therapy after percutaneous coronary intervention versus conventional therapy with clopidogrel. The presence of CYP2C19 loss‐of‐function alleles in patients treated with clopidogrel may be associated with increased risk for ischemic events. We report a prespecified sex‐specific analysis of genotyping and associated cardiovascular outcomes from this study. Methods and Results Associations between sex and major adverse cardiac events (MACE: cardiovascular death, myocardial infarction, stroke, stent thrombosis, and severe recurrent ischemia) and Bleeding Academic Research Consortium (BARC) bleeding at 12 months were analyzed using Cox proportional‐hazards models. Among 5276 randomized patients, loss‐of‐function carriers were observed in ≈36% of both sexes, and >80% of carriers were heterozygotes. At 12 months, after adjustment for baseline differences, risks of MACE (HR , 1.28 [0.97 to 1.68]; P =0.088) and BARC bleeding (hazard ratio [HR], 1.36 [0.91 to 2.05]; P =0.14) were comparable among women and men. There were no significant interactions between sex and treatment strategy for MACE interaction P value ( P int =0.59) or BARC bleeding ( P int =0.47) nor for sex and genotype (MACE P int =0.15, and BARC bleeding P int =0.60). Conclusions CYP2C19 loss‐of‐function alleles were present in ≈1 in 3 women and men. Women had similar adjusted risks of MACE and bleeding as men following percutaneous coronary intervention. Genotype‐guided therapy did not significantly reduce the risk of MACE or bleeding relative to conventional therapy for both sexes. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01742117.

Purpose of review To summarize the role of chemotherapy and offer some guidance regarding the selection of chemotherapy in mPC. Recent findings Patients with mHSPC have varied prognoses with testosterone suppression alone (androgen deprivation therapy, ADT) and differential responses to docetaxel with ADT. Patients with de novo and metachronous high-volume disease have a robust survival benefit with the addition of docetaxel to hormonal therapies. Patients with synchronous low-volume disease have a more modest survival benefit from docetaxel and there is no evidence of survival benefit with docetaxel in patients with metachronous low-volume disease. Integration of biomarkers may refine treatment selection regardless of volume of disease. Docetaxel and cabazitaxel also impart an OS benefit in patients with metastatic castration-resistant prostate cancer (mCRPC). The choice of chemotherapy in mCRPC depends on treatment received in mHSPC setting. Docetaxel remains the first line chemotherapy in castration-resistant patients who have not received it in mHSPC followed by cabazitaxel, otherwise cabazitaxel can be deployed without docetaxel retreatment. Summary Chemotherapy is a key class of therapy for selected patients with mHSPC and mCRPC.

AbstractBackgroundE3805 (CHAARTED) is a phase 3 trial demonstrating improved survival for men with metastatic hormone‐sensitive prostate cancer (mHSPC) randomized to treatment with docetaxel (D) and androgen‐deprivation therapy (ADT) versus ADT alone. We assessed the association of baseline body mass index (BMI) and metformin exposure with quality of life (QOL) and prostate cancer outcomes including survival in patients enrolled in the CHAARTED study.MethodsWe performed a posthoc exploratory analysis of the CHAARTED trial of men with mHSPC randomized to treatment with ADT with or without D between 2006 and 2012. Cox proportional hazards models and Kruskal–Wallis test were used to evaluate the association between BMI with QOL and prostate cancer outcomes and between metformin exposure and survival.ResultsIn 788 of 790 enrolled patients with prospectively recorded baseline BMI and metformin exposure status, lower BMI was not associated with survival, but was associated with high volume disease (p < 0.0001) and poorer baseline QOL on functional assessment of cancer therapy–prostate (p = 0.008). Only 68 patients had prevalent metformin exposure at baseline in the CHAARTED trial. Four groups were identified: ADT + D + metformin (n = 39); ADT + D (n = 357); ADT + metformin (n = 29); and ADT alone (n = 363). Baseline clinicopathologic characteristics were similar between groups. In this small exploratory multivariable analysis, metformin exposure was not associated with survival (hazard ratio: 1.15; 95% confidence interval: 0.81–1.63, p = 0.44).ConclusionsThere was no link between baseline BMI and survival, but lower baseline BMI was associated with features of greater cancer burden and poorer QOL.

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: Unsupervised machine learning (ML) can provide insight into a dataset without significant expert time for annotation and labeling, but was never used to assess the heterogeneous MitraClip population. Hypothesis: We hypothesized that unsupervised k-means ML could identify prognostically-distinct phenogroups in MitraClip patients without a priori knowledge of the dataset. Methods: Patients who underwent MitraClip (June 2014-September 2020) at Mayo Clinic sites were identified from the Mayo institutional NCDR database for baseline and follow-up data. Variables with ≥ 50% missing data were excluded. A k-means algorithm was used for clustering analysis. Input variables were grouped according to 4 distinct k-means determined clusters. Kaplan-Meier survival analysis was used to assess the survival of each cluster. Results: A total of 389 consecutive patients were included in the final analysis, and 95 unique variables were used. The mean age was 80.3±8.7 years; 256 (65.8%) were male. The mean STS MV Replace score was 9.1±5.7. Fifty-five (14.5%) patients died during the mean follow duration (185 days). Kaplan-Meier analysis showed significant survival differences among clusters (Figure 1). The cluster (cluster 2, n=120) with best survival performance (all-cause mortality 3.3%) had features of non-calcified mitral leaflets, nonischemic cardiomyopathy, and less than moderate tricuspid regurgitation. Cluster 3 (n=66) had the worst survival performance (all-cause mortality 27.3%) and opposite features than cluster 2. Conclusions: Unsupervised ML can identify distinct phenotype clusters with prognostic significance in MitraClip patients. Patients with non-calcified mitral leaflets, nonischemic cardiomyopathy, and less than moderate tricuspid regurgitation are intrinsically different from other MitraClip patients and should be considered the potential optimal candidates.