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.
Cardiac implantable electronic devices and outcomes in heart failure patients with syncope
Abstract Funding Acknowledgements Type of funding sources: Private hospital(s). Main funding source(s): Mayo Clinic Background/Introduction Syncope is a common presentation in heart failure (HF) patients. However, the associations between syncope and prognosis in HF patients with the cardiac implantable electronic device (CIED) have not been demonstrated. It is unclear whether syncope increases all-cause mortality in HF patients with CIED. Purpose We aimed to examine the association between syncope and all-cause mortality in the largest cohort of HF with reduced ejection fraction (HFrEF), mid-ranged ejection fraction (HFmEF), and preserved ejection fraction (HFpEF) patients with and without CIED. Methods A retrospective cohort of patients with HF and syncope at our hospital between 2010 and 2015 were identified, and 1:1 propensity was matched with a control group of HF patients without syncope. A chart review was conducted. The multivariate Cox regression model was applied to estimate the association between syncope and the all-cause mortality endpoint. Results 3,449 HF patients were diagnosed with syncope (mean age, 72.8±14.5 years; 41.5% women), and the propensity-matched control HF patients without syncope (n=3,449) aged 72.8±14.3 years, and 42.5% women were selected. Cardiac implantable electronic devices were implanted more in HF patients with syncope (32.5% versus 13.7%, p<0.001). Implantable cardioverter defibrillators were implanted more in HF patients with syncope (15.6% versus 8.3%, p<0.001) as well as pacemakers (16.9% versus 7.5%, p<0.001) and cardiac resynchronization therapy devices (6.9% versus 4.8%, p=0.015). Among HF patients with CIED, syncope significantly increased the risk of all-cause mortality in HFrEF patients (hazard ratio [HR]=1.479, 95% confidence interval [CI]: 1.197-1.828, p<0.001) but not in HFpEF (HR=0.980, 95%CI: 0.793-1.210, p=0.849)(Figure 1). Syncope also tended to increase the risk of all-cause mortality in HFmEF patients with CIED but was not significant (HR=1.193, 95%CI: 0.762-1.865, p=0.762)(Figure 1). Among HF patients without CIED, syncope did not increase the risk of all-cause mortality in HFrEF (HR=0.923, 95%CI: 0.806-1.057, p=0.247), HFmEF (HR=1.074, 95%CI: 0.848-1.360, p=0.554), or HFpEF (HR=0.964, 95%CI: 0.883-1.052, p=0.406). Conclusions Syncope significantly increased the risk of all-cause mortality in HFrEF patients but not in HFmEF or HFpEF patients with CIED. The association of syncope and increased mortality in HFrEF patients with CIED suggests that syncope may be a marker and a factor of mortality and warrants further investigation.
Transcatheter Aortic Valve Replacement Prognostication with Augmented Mean Arterial Pressure
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.
Surgical versus catheter ablation in atrial fibrillation: A systematic review and meta‐analysis of randomized controlled trials
AbstractIntroductionAtrial fibrillation (AF) is the most common cardiac arrhythmia with a high stroke and mortality rate. The video‐assisted thoracoscopic radiofrequency pulmonary vein ablation is a treatment option for patients who fail catheter ablation. Randomized data comparing surgical versus catheter ablation are limited. We performed a meta‐analysis of randomized control trials to explore the outcome efficacy between surgical and catheter radiofrequency pulmonary vein ablation in patients with AF.MethodsWe comprehensively searched the databases of MEDLINE and EMBASE from inception to December 2020. Included studies were published randomized control trials that compared video‐assisted thoracoscopic and catheter radiofrequency pulmonary vein ablation. Data from each study were combined using the fixed‐effects, generic inverse variance method of DerSimonian, and Laird to calculate odds ratios and 95% confidence intervals.ResultsSix studies from November 2013 to 2020 were included in this meta‐analysis involving 511 AF patients (79% paroxysmal) with 263 catheter ablation (mean age 56 ± 3 years) and 248 surgical ablations (mean age 52 ± 4 years). Catheter ablation was associated with increased atrial arrhythmias recurrence when compared to surgical ablation (pooled relative risk = 1.85, 95% confidence interval: 1.44−2.39, p < .001, I2 = 0.0%) but associated with less total major adverse events (pooled relative risk = 0.29, 95% confidence interval: 0.16−0.53, p < .001, I2 = 0.0%). In subgroup analysis, catheter ablation was associated with increased AF recurrence in refractory paroxysmal AF when compared to surgical ablation (pooled relative risk = 2.47, 95% confidence interval: 1.31−4.65, p = .005, I2 = 0.0%) but not in persistent AF (relative risk = 1.09, 95% confidence interval: 0.60−2.0, p = .773).ConclusionCatheter ablation was associated with higher atrial arrhythmia recurrence when compared with surgical ablation. However, our study suggests that the benefit of surgical ablation in patients with persistent AF is unclear. More studies and alternative ablation strategies investigation in persistent AF are warranted.
Abstract 11454: Unsupervised Machine Learning Identified High-Risk Phenotype in Heart Failure Patients with Syncope
Introduction: Syncope was reported to be associated with sudden cardiac death in heart failure patients regardless of the etiology of syncope. We attempted to use unsupervised machine learning to identify the prognostically distinct phenotypes in a large population of heart failure patients presenting with syncope. Hypothesis: Unsupervised machine learning can identify prognostically distinct phenotypes in a large population of heart failure patients presenting with syncope. Methods: Patients with a diagnosis of systolic or diastolic heart failure and syncope at Mayo Clinic sites were identified for baseline and follow-up data. Variables with ≥ 20% missing data were excluded; a total of 57 variables were used for k-means clustering analysis. Patients were grouped according to 4 distinct k-means determined clusters for statistical analysis. Results: A total of 3,557 patients with proper follow-up and echocardiography data were included in the final analysis. The median follow-up duration was 36.3 months, and 2908 (81.7%) patients died. Cluster 2 (n= 680) was identified as the cluster with the highest mortality (92%), which contained patients with high proportions of cardiovascular comorbidities, especially chronic kidney disease. The Kaplan-Meier survival curves are shown in Figure 1. In multivariate Cox regression analysis, the presence of CKD independently predicts mortality (HR 1.62, 95%CI 1.50-1.76, p <0.0001) after adjusting for age and sex. Conclusions: Unsupervised machine learning identified patients with CKD, CAD and DM are high-risk phenotypes in heart failure patients with syncope, and can be used to guide future studies in this highly heterogeneous, unexplored population.
Abstract 10680: Unsupervised Machine Learning Clustering Identifies Phenotypes of Optimal Candidates in Mitraclip Patients
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.
Does the Age of Sudden Cardiac Death in Family Members Matter in Brugada Syndrome?
Background Brugada syndrome is an inherited cardiac channelopathy associated with major arrhythmic events (MAEs). The presence of a positive family history of sudden cardiac death (SCD) as a risk predictor of MAE remains controversial. We aimed to examine the association between family history of SCD and MAEs stratified by age of SCD with a systematic review and meta‐analysis. Methods and Results We searched the databases of MEDLINE and EMBASE from January 1992 to January 2020. Data from each study were combined using the random‐effects model. Fitted metaregression was performed to evaluate the association between the age of SCD in families and the risk of MAE. Twenty‐two studies from 2004 to 2019 were included in this meta‐analysis involving 3386 patients with Brugada syndrome. The overall family history of SCD was not associated with increased risk of MAE in Brugada syndrome (pooled odds ratio [OR], 1.11; 95% CI, 0.82–1.51; P =0.489, I 2 =45.0%). However, a history of SCD in family members of age younger than 40 years of age did increase the risk of MAE by ≈2‐fold (pooled OR, 2.03; 95% CI, 1.11–3.73; P =0.022, I 2 =0.0%). When stratified by the age of cut point at 50, 45, 40, and 35 years old, a history of SCD in younger family member was significantly associated with a higher risk of MAE (pooled OR, 0.49, 1.30, 1.51, and 2.97, respectively; P =0.046). Conclusions A history of SCD among family members of age younger than 40 years was associated with a higher risk of MAE.