Rajai, Nahid

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 <0.001), and remained significant in multivariable analysis with traditional risk factors (HR 1.35, 95% CI 1.27-1.43, p <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<0.001) (Fig.1A). Compared to the MN population, at 5 years of follow-up only patients <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

Abstract Background One of the main features of vulnerability in atherosclerotic carotid plaques is intraplaque hemorrhage (IPH), which is related to a higher incidence of cerebrovascular events in patients with carotid artery disease. Additionally, inflammation plays a pivotal role in the progression of atherosclerotic disease. Purpose We aimed to determine plasma and tissue levels of inflammatory cytokines in patients with carotid artery disease hypothesizing that plaques with IPH are characterized by the presence of a more inflamed environment. Methods We retrospectively enrolled 104 consecutive patients undergoing carotid endarterectomy (CEA) with symptomatic (ischemic stroke, TIA, amaurosis fugax) or asymptomatic ipsilateral carotid artery disease. Plasma and carotid plaque specimens were collected at CEA. The tissue samples were stained with H&E to identify IPH and classified as specimens with and without IPH. Frozen homogenates of both plasma and tissue were analyzed using a customized 10-plex Luminex assay to determine the levels of inflammatory cytokines such as MCP-1/CCL2, IL-8/CXCL8, IFN-gamma, IL-10, IL-1beta/IL-1F2, IL-6, PDGF-AA, PDGF-AB/BB, TNF-alpha, and VEGF. Results IPH was identified in 53 patients (51.0 %). Cytokine levels in plasma and tissue from patients with and without IPH are reported in Table 1. In the univariate logistic regression MCP-1/CCL2, IL-8/CXCL8, IFN-gamma, IL-10, IL6, PDGF-AA, and PDGF-AB/BB were associated with IPH (Table 2). In the multivariate logistic regression, IL-6 was an independent predictor of IPH (HR 1.026 [95% CI 1.005-1.047]; p=0.014) after adjusting for cardiovascular risk factors such as age, BMI, sex, hypertension, diabetes mellitus, hyperlipidemia, ipsilateral carotid stenosis %. Conclusions Carotid plaques with IPH have an elevated inflammatory burden, potentially impacting adverse outcomes in this patient cohort. The local inflammatory cytokines in carotid plaques with IPH might serve as biomarkers and therapeutic targets in patients with carotid artery disease.