Citations

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.

Background: Histological changes induced by gluten in the duodenal mucosa of patients with non-coeliac gluten sensitivity (NCGS) are poorly defined. Objectives: To evaluate the structural and inflammatory features of NCGS compared to controls and coeliac disease (CeD) with milder enteropathy (Marsh I-II). Methods: Well-oriented biopsies of 262 control cases with normal gastroscopy and histologic findings, 261 CeD, and 175 NCGS biopsies from 9 contributing countries were examined. Villus height (VH, in μm), crypt depth (CrD, in μm), villus-to-crypt ratios (VCR), IELs (intraepithelial lymphocytes/100 enterocytes), and other relevant histological, serologic, and demographic parameters were quantified. Results: The median VH in NCGS was significantly shorter (600, IQR: 400–705) than controls (900, IQR: 667–1112) (p < 0.001). NCGS patients with Marsh I-II had similar VH and VCR to CeD [465 µm (IQR: 390–620) vs. 427 µm (IQR: 348–569, p = 0·176)]. The VCR in NCGS with Marsh 0 was lower than controls (p < 0.001). The median IEL in NCGS with Marsh 0 was higher than controls (23.0 vs. 13.7, p < 0.001). To distinguish Marsh 0 NCGS from controls, an IEL cut-off of 14 showed 79% sensitivity and 55% specificity. IEL densities in Marsh I-II NCGS and CeD groups were similar. Conclusion: NCGS duodenal mucosa exhibits distinctive changes consistent with an intestinal response to luminal antigens, even at the Marsh 0 stage of villus architecture.

Abstract Background: Colorectal cancer has a strong epigenetic component that is accompanied by frequent DNA methylation (DNAm) alterations in addition to heritable genetic risk. It is of interest to understand the interrelationship of germline genetics, DNAm, and colorectal cancer risk. Methods: We performed a genome-wide methylation quantitative trait locus (meQTL) analysis in 1,355 people, assessing the pairwise associations between genetic variants and lymphocytes methylation data. In addition, we used penalized regression with cis-genetic variants ± 1 Mb of methylation to identify genome-wide heritable DNAm. We evaluated the association of genetically predicted methylation with colorectal cancer risk based on genome-wide association studies (GWAS) of over 125,000 cases and controls using the multivariate sMiST as well as univariately via examination of marginal association with colorectal cancer risk. Results: Of the 142 known colorectal cancer GWAS loci, 47 were identified as meQTLs. We identified four novel colorectal cancer–associated loci (NID2, ATXN10, KLHDC10, and CEP41) that reside over 1 Mb outside of known colorectal cancer loci and 10 secondary signals within 1 Mb of known loci. Conclusions: Leveraging information of DNAm regulation into genetic association of colorectal cancer risk reveals novel pathways in colorectal cancer tumorigenesis. Our summary statistics-based framework sMiST provides a powerful approach by combining information from the effect through methylation and residual direct effects of the meQTLs on disease risk. Further validation and functional follow-up of these novel pathways are needed. Impact: Using genotype, DNAm, and GWAS, we identified four new colorectal cancer risk loci. We studied the landscape of genetic regulation of DNAm via single-SNP and multi-SNP meQTL analyses.

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: 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.

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.

AbstractAimsThe MicraTM transcatheter pacing system (TPS) (Medtronic) is the only leadless pacemaker that promotes atrioventricular (AV) synchrony via accelerometer‐based atrial sensing. Data regarding the real‐world experience with this novel system are scarce. We sought to characterize patients undergoing MicraTM‐AV implants, describe percentage AV synchrony achieved, and analyze the causes for suboptimal AV synchrony.MethodsIn this retrospective cohort study, electronic medical records from 56 consecutive patients undergoing MicraTM‐AV implants at the Mayo Clinic sites in Minnesota, Florida, and Arizona with a minimum follow‐up of 3 months were reviewed. Demographic data, comorbidities, echocardiographic data, and clinical outcomes were compared among patients with and without atrial synchronous ventricular pacing (AsVP) ≥ 70%.ResultsSixty‐five percent of patients achieved AsVP ≥ 70%. Patients with adequate AsVP had smaller body mass indices, a lower proportion of congestive heart failure, and prior cardiac surgery. Echocardiographic parameters and procedural characteristics were similar across the two groups. Active device troubleshooting was associated with higher AsVP. The likely reasons for low AsVP were small A4‐wave amplitude, high ventricular pacing burden, and inadequate device reprogramming. Importantly, in patients with low AsVP, subjective clinical worsening was not noted during follow‐up.ConclusionWith the increasing popularity of leadless pacemakers, it is paramount for device implanting teams to be familiar with common predictors of AV synchrony and troubleshooting with MicraTM‐AV devices.

AbstractBackgroundThe incidence of colorectal cancer (CRC) among individuals aged younger than 50 years has been increasing. As screening guidelines lower the recommended age of screening initiation, concerns including the burden on screening capacity and costs have been recognized, suggesting that an individualized approach may be warranted. We developed risk prediction models for early-onset CRC that incorporate an environmental risk score (ERS), including 16 lifestyle and environmental factors, and a polygenic risk score (PRS) of 141 variants.MethodsRelying on risk score weights for ERS and PRS derived from studies of CRC at all ages, we evaluated risks for early-onset CRC in 3486 cases and 3890 controls aged younger than 50 years. Relative and absolute risks for early-onset CRC were assessed according to values of the ERS and PRS. The discriminatory performance of these scores was estimated using the covariate-adjusted area under the receiver operating characteristic curve.ResultsIncreasing values of ERS and PRS were associated with increasing relative risks for early-onset CRC (odds ratio per SD of ERS = 1.14, 95% confidence interval [CI] = 1.08 to 1.20; odds ratio per SD of PRS = 1.59, 95% CI = 1.51 to 1.68), both contributing to case-control discrimination (area under the curve = 0.631, 95% CI = 0.615 to 0.647). Based on absolute risks, we can expect 26 excess cases per 10 000 men and 21 per 10 000 women among those scoring at the 90th percentile for both risk scores.ConclusionsPersonal risk scores have the potential to identify individuals at differential relative and absolute risk for early-onset CRC. Improved discrimination may aid in targeted CRC screening of younger, high-risk individuals, potentially improving outcomes.

Aims: The MicraTM transcatheter pacing system (TPS) (Medtronic) is the only leadless pacemaker that promotes atrioventricular (AV) synchrony via accelerometer-based atrial sensing. Data regarding the real-world experience with this novel system are currently lacking. We sought to characterize patients undergoing MicraTM -AV implants, describe percentage AV synchrony achieved, and analyze the causes for suboptimal AV synchrony. Methods: In this retrospective cohort study, electronic medical records from 56 consecutive patients undergoing MicraTM -AV implants at the Mayo Clinic sites in Minnesota, Florida, and Arizona with a minimum follow-up of 3 months were reviewed. Demographic data, comorbidities, echocardiographic data, and clinical outcomes were compared among patients with and without atrial synchronous-ventricular pacing (AsVP) ≥70%. Results: Fifty-six percent of patients achieved AsVP ≥70%. Patients with adequate AsVP had smaller body mass indices, a lower proportion of congestive heart failure and pulmonary hypertension. Echocardiographic parameters and procedural characteristics were similar across the two groups. Active device troubleshooting was associated with higher AsVP. The likely reasons for low AsVP were persistent atrial arrhythmias, small A4-wave amplitude, and inadequate device reprogramming. Importantly, in patients with low AsVP, subjective clinical worsening was not noted during follow-up. Conclusion: With the increasing popularity of leadless PM, it is paramount for device implanting teams to be familiar with common predictors of AV synchrony and troubleshooting with MicraTM -AV devices.