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Introduction: Patients with atherosclerotic carotid artery disease are at high risk of mortality in the long-term follow-up after carotid endarterectomy (CEA), partly due to dysrhythmia. Atrial fibrillation (AF) is a common cardiac dysrhythmia linked to stroke and cardiovascular events. An artificial intelligence-based electrocardiogram (ECG) AF algorithm (AI-AF) can effectively identify silent AF. We aimed to assess the effectiveness of AI-AF in predicting mortality in patients with carotid artery disease undergoing CEA. Methods: Patients with carotid artery disease undergoing CEA at Mayo Clinic from 2002-2023 were included if they had >30 days follow-up and an ECG within one year before CEA. The ECG closest to the CEA date was used to calculate AI-AF (probability of AF ranging from 0 to 1). All-cause mortality rates after CEA were obtained from clinical records. The optimal AI-AF cut-off value for predicting mortality was calculated using a receiver operating characteristic curve and the Youden index. Long-term survival after CEA was depicted with a Kaplan Meier plot and compared with the Log-rank test. Univariate and multivariate Cox Regression models were used to assess the predictive value of AI-AF for mortality, adjusting for age, sex, body mass index, diabetes mellitus, hypertension, and hyperlipidemia. Results: A total of 636 patients with a median age of 72 [IQR: 66, 78] years and 414 (65.1%) males were included. The median AI-AF was 0.056 [IQR: <0, 0.171]. Over a median follow-up time of 7.1 [IQR: 2.7, 11.5] years, mortality occurred in 326 (51.3%) patients. AI-AF significantly predicted mortality in univariate and multivariate Cox regression analysis (HR: 3.47, 95%CI: 2.34-5.16, P<0.001; HR: 2.30, 95%CI: 1.44-3.68, P<0.001, respectively). The best cut-off value for AI-AF for mortality prediction was 0.025 (area under the curve: 0.608). High and low AI-AF were defined as AI-AF≥ 0.025 and <0.025, respectively. Mortality was significantly higher in high AI-AF compared to low AI-AF patients (P<0.001, Figure 1A,1B), and high AI-AF was a significant predictor of mortality (univariate: Figure 2; multivariate Cox regression: HR: 2.11, 95%CI: 1.56-2.84, P<0.001). Conclusion: AI-AF can identify patients with a higher risk of mortality after CEA. This finding supports a role for AI algorithms in risk stratification of patients with carotid artery disease following CEA. Future studies are needed to elucidate the contribution of AF to all-cause mortality.

Metabolic syndrome (MetS) is associated with low-grade inflammation, which can be exacerbated by renal artery stenosis (RAS) and renovascular hypertension, potentially worsening outcomes through pro-inflammatory cytokines. This study investigated whether mesenchymal stem/stromal cells (MSCs) could reduce fat inflammation in pigs with MetS and RAS. Twenty-four pigs were divided into Lean (control), MetS, MetS + RAS, and MetS + RAS + MSCs. In the MSC-treated group, autologous adipose-derived MSCs (107 cells) were injected into the renal artery six weeks after RAS induction. After four weeks, fat volumes and inflammatory markers were assessed. MSC treatment reduced levels of pro-inflammatory cytokines (MCP-1, TNF-a, IL-6) in the renal vein blood and in perirenal fat. The MSCs also decreased fat fibrosis, restored adipocyte size, and altered adipogenesis-related gene expression, particularly in the perirenal fat. These effects were less pronounced in subcutaneous fat. The MSC therapy attenuated fat inflammation and improved metabolic outcomes in pigs with MetS + RAS, suggesting that adipose-derived MSCs may offer a promising therapeutic approach for metabolic disorders.

Background: Recent studies have reported associations between alterations in gut microbiome composition (GMC) and cardiovascular disease risk factors (CVR). However, data regarding the use of GMC as a biomarker of CVR is scarce. Aims: The current study was designed to assess the distinct patterns in GMC among patients with varying degrees of CVR and/or atherosclerotic cardiovascular disease (ASCVD). Methods: Patients with a range of CVR including hypertension (HTN), hyperlipidemia (HLD), diabetes (DM), and/or ASCVD referring to Mayo Clinic from 2013 to 2018 were prospectively enrolled. DNA extracted from stool samples was analyzed using the V3-V5 region of the 16s data. Microbial α-diversity was assessed by the observed taxonomic units, Shannon, and Chao1 indices. β-diversity was assessed using Bray-Curtis dissimilarity and plotted using principal coordinates analysis. Hierarchical clustering was used to identify patterns in the GMC samples. Random Forest analysis was used to identify the most important clinical factors differentiating the clusters. Results: A total of 211 patients with a median age of 60 [IQR: 50,70] years and with 90 (42.7%) males were included. Two clusters of GMC were identified (Figure 1A) . Cluster 1 and 2 had 104 (49.3%) and 107 (50.7%) patients, respectively. Among CVRs, age and body mass index were the most prominent factors contributing to the difference in GMC among clusters ( Figure 1B ). Cluster 2 had a better α diversity profile than Cluster 1 (Figure 1C-E) . There was no significant difference in TMAO between clusters (P=0.6). Cluster 2 patients were younger (P<0.001), leaner (P=0.007), more physically active (P<0.001), less male (P=0.009), and had a lower prevalence of ASCVD (P=0.003), HTN (P=0.010), and HLD (P=0.005). There was no significant difference in the prevalence of DM (P=0.063), smoking (P=0.446), and alcohol intake (P=0.134) between the clusters. Conclusion: This study suggests the potential of GMC profiling as a valuable biomarker for assessing CVRs, with age and BMI as the most prominent factors associated with GMC clustering.

Background: Cardiac allograft vasculopathy (CAV) is one of the leading causes of graft failure and death after heart transplantation (HTx). Conventionally, CAV is characterized by concentric intimal thickening, however the long-term progression patterns of plaque morphology are not yet well understood. Research Question: This study aimed to assess the plaque morphology, including histology and eccentricity, in a temporal manner post-HTx using virtual histology intravascular ultrasonography (VH-IVUS). Methods: We included 50 patients who underwent serial VH-IVUS assessment at three assessment points (A1:0-1 year, A2:3-5 years, A3:7-10 years) after HTx. Differences in VH-IVUS findings between timepoints A1 to A2 (early period) and A2 to A3 (late period) were investigated. Plaque volume index was defined as (plaque volume/vessel volume) × 100%. Eccentricity index (EI) was defined as (maximum intimal thickness – minimum intimal thickness)/maximum intimal thickness and was evaluated in 39 patients with significant plaque (maximal intimal thickness >0.50 mm at the A3) at each timepoint. The serial changes of EI and relationship between EI and other VH-IVUS findings were investigated. Results: Of 50 patients, mean age was 51±13 years, 36 (72%) were males. In both early and late periods, the plaque volume (PV) index showed a significant increase, however, the rate of progression was significantly slower in late period. (5.8% [0.9, 13.2] vs 2.4% [-0.2, 7.4], p=0.015). The EI showed a trend of decrease in the early period, compared to increases in the late period (-0.040 [-0.103, 0.004] vs 0.003 [-0.030, 0.052], p=0.036). Patients with EI change in late period higher than median value had significantly lower proportion of fibrous plaque (70.8% [67.2, 75.1] vs 62.7 [55.5, 66.9], p=0.002) and higher dense calcium (1.1% [0.9, 1.9], 4.5% [1.8, 6.9], p=0.022) at A3. Conclusion: In heart transplant patients, coronary artery plaque progression in the late period showed more eccentric progression with lower fibrous plaque composition, a pattern commonly observed in typical and conventional coronary atherosclerosis. These findings may provide a novel mechanism and therapeutic insight into the temporal patterns in CAV progression during long term follow up.

Introduction: Atrial fibrillation (AF) is prevalent in patients with atherosclerotic coronary and carotid artery disease and is associated with elevated plasma inflammatory markers, such as Interleukin (IL)-6. In carotid artery atherosclerosis, macrophages are considered a local marker of inflammation. Hypothesis: We hypothesize that AF is independently associated with carotid plaque inflammation. Aims: In patients undergoing carotid endarterectomy (CEA), we aimed to determine whether carotid plaques inflammation is associated with AF. Approach: In this prospective cohort study, consecutive patients with carotid artery disease undergoing CEA were enrolled. From the plaques removed during surgery, fixed in formalin and embedded in paraffin blocks, sections were stained with antibodies against CD68 to detect macrophages (Fig.1A) . Digital copies of the slides were created by Motic Easy Scan and histologically annotated with QuPath. The percentage of CD68+ cells was defined as (CD68+ positive cells/total nuclei) x 100. Flash-frozen plaque segments were analyzed by ELISA for IL-6 concentration. Baseline demographics and clinical data, including AF diagnosis, were extracted from the electronic health records. Results: A total of 106 patients undergoing CEA, with a median age of 73 [67-78] years and comprising 83 (78.3%) males, were included in the study. AF was diagnosed prior to CEA in 13 (12.3%) patients. Univariate logistic regression showed that plaque CD68+ cell content was associated with AF (OR 1.048 [95% CI 1.010 – 1.088]; p = 0.013). Additionally, in Mann-Whitney test IL-6 levels were significantly over twofold higher in plaques of patients with AF compared to those without AF (82.4 [64.9-111.7] pg/mg vs 37.0 [18.4-93.3] pg/mg; p=0.020) (Fig. 1B) . Conclusions: The current study demonstrates an association between carotid atherosclerotic plaque macrophage content, IL6 levels and AF, supporting the role of inflammation in the pathogenesis of AF in these patients. Further studies are needed to determine the potential of plaque inflammation as a therapeutic target in AF.

Background A subset of individuals with major depressive disorder (MDD) have a high burden of cardiovascular risk factors and cerebral small‐vessel disease, implicating vascular disease in the development of depression. Cross‐sectional studies demonstrate a link between endothelial dysfunction and MDD, but the prospective association between peripheral endothelial dysfunction (PED) and an incident diagnosis of MDD is unknown. Methods and Results Patients undergoing a baseline assessment of cardiovascular risk were evaluated for PED using reactive hyperemia–peripheral arterial tonometry (≤1.8 consistent with PED). Patient medical records were reviewed to identify those who underwent a formal clinical evaluation of MDD after the index PED evaluation. The frequency of PED was compared in those with and without MDD. Logistic regression analyses were performed to assess the association between baseline PED and incident MDD. Between January 2006 and December 2020, 1614 patients underwent testing for PED. Four hundred eighty‐four (30.1%) patients underwent a formal evaluation for MDD after (0–15 years) the index procedure (mean±SD age, 52.8±13.8 years; 65.2% women). Of these, 157 (32.4%) had PED and 108 (31.0%) were diagnosed with MDD. Individuals with MDD had a higher frequency of PED (40.2% versus 30.2%; P =0.034) compared with those without MDD. In multivariable analyses, PED was significantly associated with MDD (odds ratio, 2.3 [95% CI, 1.4–3.8]; P <0.001). Conclusions PED is significantly associated with incident MDD. Thus, PED may be a useful marker to identify individuals at increased risk of depression who may benefit from more frequent and earlier management strategies.

Abstract Background Cardiovascular disease remains the leading cause of death and burden globally, warranting the need to explore novel predictors of major adverse cardiovascular events (MACE) using new technologies. Artificial Intelligence (AI)-enhanced ECG (AI-ECG) algorithms can provide information on cardiovascular health of individuals, independent of conventional risk factors. Purpose The current study aimed to understand whether a previously described AI-ECG sex estimation algorithm could be applied for risk stratification of major adverse cardiovascular events (MACE), with a focus on a population without previous history of MACE. Methods Patients having 12-lead ECGs between 2018-2019 were included and followed up until August 2023. Exclusion criterion was a prior history of MACE. AI-ECG sex estimation was determined using a previously described algorithm predicting sex based on 12-lead ECGs. The algorithm generates outputs ranging from 0 to 1, representing the estimated probability of being male. Outputs above 0.5 were considered as AI-ECG-estimated male, and below as AI-ECG-estimated female. This was compared with biological sex to determine whether the two matched. Inconsistency between AI-ECG estimated sex and biological sex was defined as discordance. MACE was defined as myocardial infarction, coronary revascularization, non-fatal stroke, and all-cause death. Results Among 80,578 subjects (mean age 59.1 ± 16.1 years, 52.4% female), 9.7% exhibited sex discordance in AI-ECG estimation. Discordance was associated with a 56% higher risk of MACE (HR, 1.56, 95% CI 1.46-1.65, p &lt;0.001), and remained significant in multivariable analysis with traditional risk factors (HR 1.35, 95% CI 1.27-1.43, p &lt;0.001) (Figure 1). Sex-specific analysis showed increased MACE risk in both discordant males and females (Figure 2). Conclusion In patients with no history of MACE, discordance in AI-ECG sex estimation is associated with increased risk of MACE. These findings suggest the potential of AI-ECG sex estimation algorithm for risk assessment, especially in patients with no history of MACE.Figure 1.Cox proportional hazard modelFigure 2.Kaplan-Meier of MACE by sex

Abstract Background Patients with carotid artery disease undergoing carotid endarterectomy (CEA) appear to be at high risk of all-cause mortality during their follow-up. However, the possible predictors of this adverse outcome are not elucidated yet. Purpose We aimed to test cardiovascular (CV) risk factors as possible predictors of all-cause mortality in patients undergoing CEA and to determine whether there is a difference between the mortality rate of our study cohort and the general population. We hypothesize that CEA-treated patients have a higher mortality rate during follow-up after surgery than the general population, which is not related to the presence of CV risk factors. Methods We prospectively enrolled and followed up patients undergoing CEA. Univariate and multivariable Cox regression were performed to test whether common CV risk factors (demographics, laboratory values, comorbidities, and events before CEA) were predictive of all-cause mortality. We then compared the standardized mortality ratio (SMR) of our population and the age-sex-matched Minnesota (MN) general population at 5,10, and 21 years of follow-up after CEA. Results A total of 710 patients were followed for a median of 7.1 [2.9-11.9] years after CEA. Mortality occurred in 198 (27.0%) patients during the follow-up. The median time to event was 11.0 [10.0-12.0] years. Age was the only predictor of all-cause mortality in CEA-treated patients in multivariable models adjusted for known CV risk factors (Model 1: HR 1.03 [95%CI 1.01-1.06]; p=0.004; Model 2: HR 1.02 [95%CI 1.00-1.04]; p=0.023) (Table 1). However, the CEA-treated group had a higher mortality rate than would have been expected in the MN population (log-rank p&lt;0.001) (Fig.1A). Compared to the MN population, at 5 years of follow-up only patients &lt;60 years old had a higher SMR (4.53 [1.95-8.92]; p=0.001), whereas, at 10 years and 21 years of follow-up, our study population had a higher mortality rate at any age (Fig.1B). Conclusions The elevated mortality risk post-CEA in our cohort cannot be solely attributed to chronological aging. The underlying process of atherosclerosis likely contributes to all-cause mortality, and plaque characteristics may offer additional insight into the risk stratification of this patient group.All cause mortality predictors after CEAStudy population vs. MN population SMR

Abstract Background Patients with carotid artery disease undergoing carotid endarterectomy (CEA) have a high risk of experiencing Major Adverse Cardiovascular Events (MACE) after surgery. The occurrence of MACE in CEA-treated patients is not predicted by common cardiovascular (CV) risk factors. Purpose We aimed to identify the association between plasma and plaque inflammatory cytokines and the incidence of MACE in the follow-up after CEA. We hypothesized that MACE is related to a higher level of circulating inflammatory cytokines at the time of surgery. Methods We prospectively enrolled patients with carotid artery disease undergoing CEA. Plasma and carotid plaques were collected during the surgery. Inflammatory cytokines (MCP-1/CCL2, IL-8/CXCL8, IFN-gamma, IL-10, IL-1beta/IL-1F2, IL-6, PDGF-AA, PDGF-AB/BB, TNF-alpha, VEGF) were measured in plasma and tissue homogenates using a customized 10-plex Luminex assay. Baseline demographics and clinical data for all the patients were extracted from electronic health records. MACE after CEA was defined as a composite measure of nonfatal cardiac events such as myocardial infarction with or without revascularization, cerebrovascular events (ischemic stroke, TIA, and amaurosis fugax), and all-cause mortality. Results Of 107 patients who underwent CEA with a median age of 73 (67-78) years, 57 (53.2%) experienced MACE during a median follow-up of 5.2 [2.2-9.3] years: 23 (40.3%) cardiac events, 9 (15.7%) CVA, and 25 (43.8%) all-cause mortality. Plaque cytokines levels did not differ between the groups with and without MACE in the follow-up after CEA. Instead, plasma cytokines were associated with MACE in the follow-up after CEA, as summarized in Figure 1. In the logistic regression analysis, plasma levels of MCP-1/CCL2, IFN-gamma, and TNF-alpha were independent predictors of MACE in follow-up post-CEA in univariate and multivariable models adjusted for CV risk factors such as age, BMI, systolic and diastolic blood pressure, low-density lipoprotein, high-density lipoprotein, and glucose level: MCP1/CCL2 (HR 1.009 [1.002-1.015]; p=0.007), IFN-gamma (HR 1.368 [1.014-1.845]; p=0.040), and TNF-alpha (HR 1.121 [1.022-1.228]; p=0.015) (Table 1). Conclusions Plasma levels of CCL2, IFN-gamma, and TNF-alpha are associated with the high incidence of MACE in the follow-up after CEA, indicating that these are potential biomarkers of MACE in this patient population and potential therapeutic targets in patients' progression of systemic atherosclerosis.Plasma cytokines and MACE after CEACytokines logistic regression analysis