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Introduction: Diabetes mellitus and insulin resistance are associated with accelerated vascular injury and progression of coronary atherosclerosis. CD34 + progenitor cells are mobilized and recruited to repair the endothelial and vascular damage. Hypothesis: We hypothesized that the interaction of insulin levels and retention of CD34+ progenitors in the coronary arteries will be different between patients with and without insulin resistance. Methods: In patients with no obstructive coronary artery disease (NOCAD: <40% angiographic stenosis), blood samples were collected concurrently from the proximal aorta and the coronary sinus, and CD34+ cells counted using flow cytometry. CD34+ cells gradient was calculated by subtracting aortic from coronary sinus cell counts, with a higher gradient reflecting lower retention. Patients on antidiabetic medications were excluded. Insulin resistance (IR) was estimated as HOMA-IR index ([insulin]*[glucose]/405)) ≥2. Results: Of 128 patients (mean age 51±11 years, 77% females), 60 (47%) had IR (mean age 51±10 years, 73% females) and 68 (53%) did not (mean age 50±13 years, 79% females). The groups did not differ in age, sex or LDL cholesterol. The IR group had higher BMI and triglyceride levels and lower HDL cholesterol. CD34 + cell gradient correlated directly significantly with insulin levels in patients without IR (r=0.25, p=0.04) (Fig1A) , but inversely in those with IR (r=-0.39, p=0.01) (Fig1B) . Both associations remained significant after adjustment for age, sex, and BMI (IR: r=-0.39, p=0.02; no IR: r=29, p=0.04). Conclusions: In NOCAD patients with IR, higher levels of serum insulin were associated with increased retention of CD34 + cells in the coronary arteries. The current study supports a potential role for CD34 + cells for vascular repair in patients with IR.

Background Recent studies have indicated high rates of future major adverse cardiovascular events in patients with Takotsubo cardiomyopathy (TC), but there is no well‐established tool for risk stratification. This study sought to evaluate the prognostic value of several artificial intelligence‐augmented ECG (AI‐ECG) algorithms in patients with TC. Methods and Results This study examined consecutive patients in the prospective and observational Mayo Clinic Takotsubo syndrome registry. Several previously validated AI‐ECG algorithms were used for the estimation of ECG‐ age, probability of low ejection fraction, and probability of atrial fibrillation. Multivariable models were constructed to evaluate the association of AI‐ECG and other clinical characteristics with major adverse cardiac events, defined as cardiovascular death, recurrence of TC, nonfatal myocardial infarction, hospitalization for congestive heart failure, and stroke. In the final analysis, 305 patients with TC were studied over a median follow‐up of 4.8 years. Patients with future major adverse cardiac events were more likely to be older, have a history of hypertension, congestive heart failure, worse renal function, as well as high‐risk AI‐ECG findings compared with those without. Multivariable Cox proportional hazards analysis indicated that the presence of 2 or 3 high‐risk findings detected by AI‐ECG remained a significant predictor of major adverse cardiac events in patients with TC after adjustment by conventional risk factors (hazard ratio, 4.419 [95% CI, 1.833–10.66], P =0.001). Conclusions The combined use of AI‐ECG algorithms derived from a single 12‐lead ECG might detect subtle underlying patterns associated with worse outcomes in patients with TC. This approach might be beneficial for stratifying high‐risk patients with TC.

BACKGROUND: The financial burden linked to the diagnosis and treatment of patients with chest pain on the health care system is considerable. Angina and nonobstructive coronary artery disease (ANOCA) is common, associated with adverse cardiovascular events, and may lead to repeat testing or hospitalizations. Diagnostic certainty can be achieved in patients with ANOCA using coronary reactivity testing (CRT); however, its financial effect on the patient has not been studied. Our goal was to assess the effect of CRT on health care–related cost in patients with ANOCA. METHODS: Patients with ANOCA who underwent diagnostic coronary angiography (CAG) and CRT (CRT group) were matched to controls who had similar presentation but only underwent a CAG without CRT (CAG group). Standardized inflation-adjusted costs were collected and compared between the 2 groups on an annual basis for 2 years post the index date (CRT or CAG). RESULTS: Two hundred seven CRT and 207 CAG patients were included in the study with an average age of 52.3±11.5 years and 76% females. The total cost was significantly higher in the CAG group as compared with the CRT group ($37 804 [$26 933–$48 674] versus $13 679 [$9447–$17 910]; P <0.001). When costs are itemized and divided based on the Berenson-Eggers Type of Service categorization, the largest cost difference occurred in imaging (any type, including CAG; P <0.001), procedures (eg, percutaneous coronary intervention/coronary artery bypass grafting/thrombectomy) ( P =0.001), and test (eg, blood tests, EKG; P <0.001). CONCLUSIONS: In this retrospective observational study, assessment of CRT in patients with ANOCA was associated with significantly reduced annual total costs and health care utilization. Therefore, the study may support the integration of CRT into clinical practice.

Introduction: The mechanistic link between early coronary artery disease (CAD) and atrial fibrillation (AF) continues to be explored. Clonal hematopoiesis of indeterminate potential (CHIP) is increasingly recognized as a risk factor for cardiovascular disease. We hypothesize CHIP further increases the risk for AF in early CAD. Methods: 184 participants underwent invasive coronary angiogram with endothelial function testing. Buffy coat was used for whole exosome sequencing to identify CHIP (variant allele frequency > 2% and minor allele frequency ≤ 0.1%). Early CAD was defined by the presence of coronary endothelial dysfunction (CED) in the absence of obstructive CAD. Invasive coronary angiography with endothelial function testing characterized CED as ≥ 20% increase in coronary artery diameter or ≤ 50% increase in coronary blood flow in response to acetylcholine. AF was identified by ICD-10 code or patient survey and confirmed by an independent investigator by chart review. Cox proportional hazard regression was adjusted for age, sex, and conventional cardiovascular comorbidities (hypertension, diabetes, and total cholesterol). Results: Of the 184 participants, we identified 23 cases with both early CAD and CHIP and 62 normal controls without CHIP or CAD. Case patients were significantly older (mean 60 ±9 vs 52 ±10 years, p = 0.004 years) and predominantly female (74% vs 81%, p = 0.506). AF was more likely among case participants when compared to normal controls (29% vs 10%, p = 0.036). Mean time to AF or last follow-up was 11 ±7 years. Case patients with both early CAD and CHIP were nearly 10 times more likely to develop AF when compared to normal controls in a Cox regression model adjusted for age, sex, and conventional cardiovascular comorbidities (HR 9.52, 95% CI 1.93 - 47.02, p = 0.006). The risk for AF was not significant if we defined cases by only the presence of CHIP (n = 30) or early CAD (n = 122). Conclusions: Patients with both CHIP and early CAD may have greater risk for developing AF beyond the presence of CHIP or CAD alone. Our findings suggest an added mechanistic role of CHIP that further increases the risk for AF in early CAD.

Introduction: Recent studies have indicated high rates of future major adverse cardiovascular events in patients with Takotsubo cardiomyopathy (TTC). This study sought to evaluate the prognostic value of our institutional artificial intelligence-augmented electrocardiography (AI-ECG) algorithms in patients with TTC. Methods: This study enrolled consecutive patients in the prospective and observational Mayo Clinic Takotsubo syndrome registry. TTC was diagnosed according to the Mayo Clinic diagnostic. Our clinic’s previously developed and validated AI-ECG algorithms were used for detection of ECG-Age, probability of low ejection fraction, and probability of atrial fibrillation.Multivariable models were constructed to evaluate the association of AI-ECG and other clinical characteristics with major adverse cardiac events (MACE), defined as cardiac death, recurrence of TTC, nonfatal myocardial infarction, hospitalization for congestive heart failure, and stroke. Results: In the final analysis, 305 patients were studied over a median follow-up of 4.8 years. Patients with MACE were more likely to be older, have history of hypertension and chronic heart failure (CHF), worse renal function as well as having high-risk AI-ECG findings compared to those without. In the multivariate Cox proportional hazard analysis, the presence of 3 or 4 high-risk findings detected by AI-ECG, remained a significant predictor of MACE in the patients with TTC after adjusted by conventional risk factors (hazard ratio (HR) 2.17, 95% CI [1.33, 3.53], P=0.002; HR 2.44, 95% CI [1.38, 4.29], P=0.002, respectively). Conclusions: The combined use of developed AI-ECG algorithms derived from a single 12-lead ECG might identify ECG correlates of underlying non-transient myocardial dysfunction and detect subtle underlying patterns associated with worse outcomes in patients with TTC. This approach might be beneficial for stratifying high-risk patients with TTC.

AbstractIntroductionData regarding ventricular tachycardia (VT) or premature ventricular complex (PVC) ablation in patients with aortic valve (AV) intervention (AVI) is limited. Catheter ablation (CA) can be challenging given perivalvular substrate in the setting of prosthetic valves. We sought to investigate the characteristics, safety, and outcomes of CA in patients with prior AVI and ventricular arrhythmias (VA).MethodsWe identified consecutive patients with prior AVI (replacement or repair) who underwent CA for VT or PVC between 2013 and 2018. We investigated the mechanism of arrhythmia, ablation approach, perioperative complications, and outcomes.ResultsWe included 34 patients (88% men, mean age 64 ± 10.4 years, left ventricular (LV) ejection fraction 35.2 ± 15.0%) with prior AVI who underwent CA (22 VT; 12 PVC). LV access was obtained through trans‐septal approach in all patients except one patient who had percutaneous transapical access. One patient had combined retrograde aortic and trans‐septal approach. Scar‐related reentry was the dominant mechanism of induced VTs. Two patients had bundle branch reentry VTs. In the VT group, substrate mapping demonstrated heterogeneous scar that involved the peri‐AV area in 95%. Despite that, the site of successful ablation included the periaortic region only in 6 (27%) patients. In the PVC group, signal abnormalities consistent with scar in the periaortic area were noted in 4 (33%) patients. In 8 (67%) patients, the successful site of ablation was unrelated to the periaortic area. No procedure‐related complications occurred. The survival and recurrence‐free survival rate at 1 year tended to be lower in VT group than in PVC group (p = .06 and p = .05, respectively) with a 1‐year recurrence‐free survival rate of 52.8% and 91.7%, respectively. No arrhythmia‐related death was documented on long‐term follow‐up.ConclusionCA of VAs can be performed safely and effectively in patients with prior AVI.

Background: Clonal hematopoiesis (CH) of indeterminate potential (CHIP) is a risk factor for cardiovascular disease. The relationship between CHIP and coronary microvascular dysfunction (CMD) is unknown. The current study examines the association between CHIP and CH with CMD and the potential relationships in risk for adverse cardiovascular outcomes. Methods: In this retrospective observational study, targeted next-generation sequencing was performed for 177 participants with no coronary artery disease who presented with chest pain and underwent routine coronary functional angiogram. Patients with somatic mutations in leukemia-associated driver genes in hematopoietic stem and progenitor cells were examined; CHIP was considered at a variant allele fraction ≥2%; CH was considered at a variant allele fraction ≥1%. CMD was defined as coronary flow reserve to intracoronary adenosine of ≤2. Major adverse cardiovascular events considered were myocardial infarction, coronary revascularization, or stroke. Results: A total of 177 participants were examined. Mean follow-up was 12±7 years. A total of 17 patients had CHIP and 28 had CH. Cases with CMD (n=19) were compared with controls with no CMD (n=158). Cases were 56±9 years, were 68% women, and had more CHIP (27%; P =0.028) and CH (42%; P =0.001) than controls. CMD was associated with independent risk for major adverse cardiovascular events (hazard ratio, 3.89 [95% CI, 1.21–12.56]; P =0.023), and 32% of this risk was mediated by CH. The risk mediated by CH was ≈0.5× as large as the direct effect of CMD on major adverse cardiovascular events. Conclusions: In humans, we observe patients with CMD are more likely to have CHIP, and nearly one-third of major adverse cardiovascular events in CMD are mediated by CH.

Abstract Primary sclerosing cholangitis (PSC) is a complex bile duct disorder. Its etiology is incompletely understood, but environmental chemicals likely contribute to risk. Patients with PSC have an altered bile metabolome, which may be influenced by environmental chemicals. This novel study utilized state-of-the-art high-resolution mass spectrometry (HRMS) with bile samples to provide the first characterization of environmental chemicals and metabolomics (collectively, the exposome) in PSC patients located in the United States of America (USA) (n = 24) and Norway (n = 30). First, environmental chemical- and metabolome-wide association studies were conducted to assess geographic-based similarities and differences in the bile of PSC patients. Nine environmental chemicals (false discovery rate, FDR &lt; 0.20) and 3143 metabolic features (FDR &lt; 0.05) differed by site. Next, pathway analysis was performed to identify metabolomic pathways that were similarly and differentially enriched by the site. Fifteen pathways were differentially enriched (P &lt; .05) in the categories of amino acid, glycan, carbohydrate, energy, and vitamin/cofactor metabolism. Finally, chemicals and pathways were integrated to derive exposure–effect correlation networks by site. These networks demonstrate the shared and differential chemical–metabolome associations by site and highlight important pathways that are likely relevant to PSC. The USA patients demonstrated higher environmental chemical bile content and increased associations between chemicals and metabolic pathways than those in Norway. Polychlorinated biphenyl (PCB)-118 and PCB-101 were identified as chemicals of interest for additional investigation in PSC given broad associations with metabolomic pathways in both the USA and Norway patients. Associated pathways include glycan degradation pathways, which play a key role in microbiome regulation and thus may be implicated in PSC pathophysiology.

Abstract Background: Primary sclerosing cholangitis (PSC) patients have a risk of developing cholangiocarcinoma (CCA). Establishing predictive models for CCA in PSC is important. Methods: In a large cohort of 1,459 PSC patients seen at Mayo Clinic (1993-2020), we quantified the impact of clinical/laboratory variables on CCA development using univariate and multivariate Cox models and predicted CCA using statistical and artificial intelligence approaches. We explored plasma bile acid (BA) levels’ predictive power of CCA (subset of 300 patients, BA cohort). Results: Eight significant risk factors (false discovery rate: 20%) were identified with univariate analysis; prolonged inflammatory bowel disease (IBD) was the most important one. IBD duration, PSC duration, and total bilirubin remained significant (p<0.05) with multivariate analysis. Clinical/laboratory variables predicted CCA with cross-validated C-indexes of 0.68–0.71 at different time points of disease, significantly better compared to commonly used PSC risk scores. Lower chenodeoxycholic acid, higher conjugated fraction of lithocholic acid and hyodeoxycholic acid, and higher ratio of cholic acid to chenodeoxycholic acid were predictive of CCA. BAs predicted CCA with a cross-validated C-index of 0.66 (std: 0.11, BA cohort), similar to clinical/laboratory variables (C-index=0.64, std: 0.11, BA cohort). Combining BAs with clinical/laboratory variables leads to the best average C-index of 0.67 (std: 0.13, BA cohort). Conclusions: In a large PSC cohort, we identified clinical and laboratory risk factors for CCA development and demonstrated the first artificial intelligence based predictive models that performed significantly better than common risk scores. More predictive data modalities are needed for clinical adoption of these models.