Citations

AbstractWe report a case of alcohol ablation into a vein of Marshall for recurrent dormant conduction into the pulmonary veins with adenosine testing in a patient where two prior ablation attempts failed to isolate the left vein.

Background: Artificial intelligence (AI)-based analysis of the electrocardiogram (ECG) can estimate the probability of having atrial fibrillation (AF) while in sinus rhythm. We evaluated the association between the probability of AF using AI-ECG and incident ischemic stroke (I-Stroke) and cardiovascular (CV) mortality. Methods: We evaluated a community-based cohort of consecutive patients that sought primary care in Olmsted County, MN, from the years 1998 to 2000 followed-up through March 2016. Inclusion criteria were ages 40-79, an electrocardiogram within 2 years and complete CHA2DS2-VASc data. We excluded those with known atherosclerotic CV disease or AF. The AI network was developed in 180,000 patients (649,931 ECG). The primary endpoint was incident I-Stroke; secondary endpoint was I-Stroke or CV mortality; validated in duplicate. Multivariate cox models adjusted for age, sex, history of hypertension, diabetes, heart failure, and in CHA2DS2-VASc Score subgroups (categorized as low=0, moderate=1, and high risk ≥2). Results: We included 14,601 patients, mean age 53.2±13.08 (51% women, 95% whites), CHA2DS2-VASc score 1.3±1.2, median follow-up of 16.3 years, IQR 14.5-17.5, 727 (4.9%) had an I-Stroke and 1309 (8.9%) had I-Stroke or died from CV causes. When comparing the 5 th vs the 1 st quintile, those with high AI-ECG AF probability had increased risk for I-Stroke (HR 3.25, 95%CI 2.55-4.14, P-for trend <.0001 Figure-A ) and ischemic stroke or CV mortality (HR 5.73, 95%CI 4.69-6.99, P-for trend <.0001 Figure-B ). This remained significant after adjustments. Furthermore, AI-ECG AF probability was associated with I-Stroke across CHA2DS2-VASc risk levels (HR 2.43 for high, 2.33 for moderate, 1.98 for low CHA2DS2-VASc risk, all P<0.01). Conclusion: The AI-ECG AF algorithm predicts long-term I-Stroke and CV mortality and may refine CHA2DS2-VASc. These results highlight the utility of the AI enabled ECG when estimating I-Stroke or CV mortality risk.

Introduction: Cardiac Sarcoidosis (CS) is a non-ischemic cardiomyopathy (NICM) characterized by infiltration of non-caseating granulomas involving in the heart with highly variable clinical manifestations. Cardiac resynchronization therapy (CRT) has shown significant promise in NICM, though little is known about its effectiveness in patients with CS. Hypothesis: We sought to determine if CRT improved cardiac remodeling and reduced hospitalizations in patients with CS. Methods: We retrospectively reviewed all patients with a clinical or histological diagnosis of CS who underwent CRT implantation at a Mayo Clinic site from 2000-2021. Baseline characteristics, echocardiographic parameters, heart failure hospitalization, and major adverse cardiac events (MACE) were assessed. Results: Our cohort was comprised of 55 patients with 61.8% male and a mean age of 58.7 ± 10.9 years. At baseline, 38 (69.1%) patients had isolated CS, while 17 (30.9%) had evidence of CS with extra-cardiac sarcoidosis. The overwhelming majority underwent CRT-D implantation (n=52, 94.5%) with 67.3% of implanted devices upgrades from prior pacemaker or implantable cardioverter defibrillator. At 6 months post-implantation there was no significant different in ejection fraction (34.8 ± 10.9 % vs. 37.7 ± 14.2 %, p = 0.237), left ventricular end systolic diameter (49.1 ± 9.9 mm vs. 45.7 ± 9.9 mm, p = 0.077) or left ventricular end-diastolic diameter (58.5 ± 10.2 mm vs. 57.5 ± 8.1 mm, p = 0.574). Within the first 6 months post-implantation, 5 (9.1%) patients sustained a heart failure hospitalization. At a mean follow up of 4.1 ± 3.7 years, 14 (25.5%) patients experienced a heart failure hospitalization, 11 (20.0%) underwent cardiac transplantation, 1 (1.8%) underwent LVAD implantation and 7 (12.7%) patients died. Conclusions: Our findings suggest a poor response to CRT in patients with CS with no significant evidence of reverse remodeling within 6 months and a substantial proportion of patients progressing to advanced heart failure therapies.

AbstractBackgroundDementia with Lewy bodies (DLB) is a neurodegenerative disorder that presents with a variety of clinical symptoms. Part of the clinical heterogeneity within DLB has been related to the atrophy/sparing of the hippocampus. We extended that previous research by investigating whether different atrophy patterns exist in DLB, beyond and above the atrophy/sparing of the hippocampus, and whether those patterns contribute to the clinical heterogeneity in DLB. We aimed to identify DLB atrophy subtypes using a hypothesis‐free data‐driven clustering approach based on regional gray matter (GM) volumes and characterize the resulting subtypes across key measures.MethodWe included data from three centers of the European DLB consortium. A high‐resolution 3D T1‐weigthed magnetization prepared rapid gradient echo (MPRAGE) sequence was acquired for 97 DLB patients. Eighty‐four cortical regions and 12 subcortical regions from Mayo Clinic Adult Lifespan Template (https://www.nitrc.org/projects/mcalt/) atlases were obtained. Clusters of DLB patients were then determined using the random forest method. Between‐group differences in key demographic, clinical, MRI volumes and cerebrospinal fluid biomarkers (CSF) (amyloid‐beta, phosphorylated‐tau) were performed for clusters characterization.ResultWe identified three subtypes of DLB patients, with distinct patterns of GM volumes and differences in several clinical and demographic measures. Cluster 1 (C1) included 32 DLB patients (33%), cluster 2 (C2) included 29 DLB patients (30%), and cluster 3 (C3) included 36 DLB patients (37%). The clusters differed in age, with C1 being significantly older (72±8.6) than C3 (66±9.5) (F=3.93, p=0.02). C1 was characterized by lower volumes in fronto‐temporal regions and had a higher frequency of visual hallucinations (68%, vs. C2 35%). C2 showed lower volumes in occipital regions. C3 had higher GM volumes overall compared with the other two clusters and presented with a higher frequency of cognitive fluctuations (91%, vs. C1 67%). There were no differences between groups in CSF biomarkers. These results were independent of cluster differences in age and global GM volume.ConclusionThere are distinct patterns of brain atrophy in patients with DLB. These patterns seem to differentially contribute to the frequencies of visual hallucinations and cognitive fluctuations, independently of differences in age and global GM volume across subtypes.

512 Background: The role of immune checkpoint inhibitors (ICIs) in the treatment of extrapulmonary neuroendocrine carcinoma (EP-NEC) has yet to be established. While objective responses have been observed, it is still unknown which patients are likely to derive benefit. We investigated the genomic profiles of patients who did and did not benefit from ICIs. Methods: Previously we reported the objective responses to ICI in a retrospective series of patients with EP-NEC. RECIST 1.1 criteria were used to categorize patients as achieving disease control (DC = CR, PR, or SD) vs progressive disease (PD). The EMR was reviewed to identify patients who had genomic panels performed, and results were extracted for analysis. Results: Of 31 patients eligible for RECIST assessment, 19 had genomic panels available (9 with DC: 4 SD, 5 PR vs 10 with PD). Of those with NEC histology specified, 9 were small cell, 1 combined large and small cell, 3 were large cell. All tumors were microsatellite-stable. All but one (with TMB = 25) of 16 tumors with TMB status available were < 10 m/MB. Of those with disease control, 67% had both TP53 and RB1 alterations, compared with only 10% in those with progressive disease; this was statistically significant ( p = 0.0198, Fisher exact). Of 7 tumors with TP53 + RB1 alterations, 4 were specified as small cell carcinoma. Half of those with PD showed alterations in β-catenin pathway genes CTNNB1 or APC, compared to only one of the DC group, but this did not reach significance ( p = 0.1409, Fisher exact). In an analysis of all Mayo patients (not just those treated with ICI) with NGS data available (Tempus and FoundationOne), concurrent TP53 + RB1 alteration was significantly more common in SCLC than in EP-NEC (Table). Conclusions: In this small series of patients with EP-NEC treated with ICIs, the SCLC-like genomic signature of concurrent TP53 + RB1 alterations was significantly more common in those with disease control than in those with progressive disease. An analysis of all patients with NGS data (not just on ICI) showed that the dual alteration was more common in SCLC, and SCLC also had more TMB-high tumors. This may explain why ICIs are more effective in SCLC than in EP-NEC. Further study is warranted to determine whether TP53 + RB1 mutations predict response to ICI in NEC.[Table: see text]

Abstract Background Glycemic traits—such as hyperinsulinemia, hyperglycemia, and type 2 diabetes—have been associated with higher colorectal cancer risk in observational studies; however, causality of these associations is uncertain. We used Mendelian randomization (MR) to estimate the causal effects of fasting insulin, 2-hour glucose, fasting glucose, glycated hemoglobin (HbA1c), and type 2 diabetes with colorectal cancer. Methods Genome-wide association study summary data were used to identify genetic variants associated with circulating levels of fasting insulin (n = 34), 2-hour glucose (n = 13), fasting glucose (n = 70), HbA1c (n = 221), and type 2 diabetes (n = 268). Using 2-sample MR, we examined these variants in relation to colorectal cancer risk (48 214 case patient and 64 159 control patients). Results In inverse-variance models, higher fasting insulin levels increased colorectal cancer risk (odds ratio [OR] per 1-SD = 1.65, 95% confidence interval [CI] = 1.15 to 2.36). We found no evidence of any effect of 2-hour glucose (OR per 1-SD = 1.02, 95% CI = 0.86 to 1.21) or fasting glucose (OR per 1-SD = 1.04, 95% CI = 0.88 to 1.23) concentrations on colorectal cancer risk. Genetic liability to type 2 diabetes (OR per 1-unit increase in log odds = 1.04, 95% CI = 1.01 to 1.07) and higher HbA1c levels (OR per 1-SD = 1.09, 95% CI = 1.00 to 1.19) increased colorectal cancer risk, although these findings may have been biased by pleiotropy. Higher HbA1c concentrations increased rectal cancer risk in men (OR per 1-SD = 1.21, 95% CI = 1.05 to 1.40), but not in women. Conclusions Our results support a causal effect of higher fasting insulin, but not glucose traits or type 2 diabetes, on increased colorectal cancer risk. This suggests that pharmacological or lifestyle interventions that lower circulating insulin levels may be beneficial in preventing colorectal tumorigenesis.