Bianchettin, Rosana G

Abstract Background Atherosclerotic cardiovascular disease (ASCVD) develops over a prolonged latent period, progressing from subclinical ASCVD to major cardiovascular events due to plaque accumulation. Subclinical ASCVD is a valid subrogate to assess potential risk factors or ASCVD. Dietary patterns are known to contribute to or prevent ASCVD. Dairy consumption has been associated with lower rates of obesity, hypertension, and diabetes, while saturated fats, present in most dairy products, have been associated with ASCVD. Studies assessing the association between subclinical ASCVD and dairy consumption have shown mixed results but have not been systematically analyzed Purpose This study aimed to systematically review and synthesize the existing evidence on the association between dairy product consumption and subclinical ASCVD Methods The study protocol was registered in the International Prospective Register of Systematic Reviews and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. We conducted a comprehensive search of PubMed, EMBASE, Scopus, Cochrane Central Register, Google Scholar, and Web of Science to identify experimental and observational studies that examined the association of dairy product consumption with measures of subclinical ASCVD assessed through coronary artery calcium (CAC) scanning, intima-media thickness (IMT), pulse pressure (PP) or pulse wave velocity (PWV), from inception to July 9, 2024. Titles and abstracts were screened in duplicate, followed by a full-text review and data abstraction from articles that met the study criteria. Dairy products were classified as: a) Dairy, according to the United States Department of Agriculture, encompassing milk, yogurt, cheese, lactose-free milk, and fortified soy milk/yogurt; and b) Dairy+, which further included higher fat content products such as cream cheese, sour cream, cream, and butter Results A total of 973 articles were identified; 22 met inclusion criteria representing 20 studies; being predominantly cross-sectional (55%) conducted in North America (50%); food frequency questionnaires were the most implemented tool for dietary assessment (86%), and 41% used PWV for subclinical ASCVD assessment; Fig. 1. Total Dairy and Dairy+ exhibited predominantly neutral effects with a trend toward a beneficial effect, similar to yogurt intake. Milk and cheese demonstrated contrasting effects, with studies reporting protective, neutral, and harmful associations, particularly for PWV and IMT. Limited data on CAC suggested no strong relationship with dairy consumption; Table 1 Conclusion Available evidence on the association between dairy consumption and subclinical ASCVD is complex with mixed effects across dairy products. No consistent evidence of harm or benefit was found; future research is needed to clarify the role of different dairy components in the development of subclinical ASCVD and incidence of cardiovascular eventsFig1.Summary of studies characteristics Table 1.Summary of effects

Background: Sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP1-RA) have known cardiovascular benefits. We aimed to assess the efficacy of GLP1-RA or SGLT2i initiation in reducing mortality or cardiovascular events in a community-based cohort of adults with ischemic stroke. Methods: Patients ≥18 years old admitted for acute ischemic stroke between Jan 2000 and June 2022 were identified using the Rochester Epidemiology Project. Subjects were considered exposed to SGLT-2i or GLP1-RA if they were treated with either medication after the index stroke and before the primary (all-cause mortality) or secondary outcomes (MI, recurrent ischemic stroke or composite). Kaplan-Meier curves and Cox models are shown in the Figures . Results: We included 7044 subjects, mean age 72±14 yr, 52% male, 94% white, over a median follow-up of 3 [1-7] years, 416 subjects (6%) had a second stroke, 426 (6%) had an incident MI and 3738 (53%) died. Those on SGLT2i/GLP1-RA had a decreased risk for mortality, incident MI, and composite in the univariate analysis. These associations remained significant after multivariable adjustment and were not affected by minimum time of exposure Figure 1&2 . SGLT2i/GLP1-RA use was associated with recurrent ischemic stroke in the multivariate analysis Figure 2C . All associations remained significant in most sub-analyses of individual medications except for the association between GLP1-RA and recurrent stroke Figure 3 Conclusions: SGLT2i or GLP-1 RA use was associated with decreased mortality and risk of myocardial infarction and recurrent stroke in patients with ischemic stroke.

Introduction: The effect of obesity on physiologic aging has not been completely established. We previously developed an artificial intelligence-enabled electrocardiogram (AI-ECG) algorithm that predicts age and determines that the difference between AI-ECG age and chronological age (Age-Gap) may reflect accelerated aging, as it is associated with increased total and cardiovascular (CV) mortality. Hypothesis: Obesity is associated with an increased Age-Gap reflecting morbidity and accelerated aging. Methods: We included adults undergoing a wellness evaluation including, body fat percentage (BF%) determination by air displacement plethysmography (Bod-Pod®) and a 12-lead ECG within 2 years. We excluded those with coronary artery disease, congestive heart failure, stroke or being underweight defined as having a BMI<18.5 kg/m2. Logistic regression models tested the association between obesity by BMI (≥30 kg/m2) or BF% quartiles (≥35% for men and ≥25 in women) and being older by AI-ECG. Results: We included 1295 subjects (70% women), mean chronological age 46.7 ± 13.1 years. Mean Age-gap positive difference compared to those with BMI<25 was 1.39, 2.06 and 2.83 for those with BMI 25-29.9, 30-34.9, and >35 respectively (p<0.05). In the BF% group, Age-gap difference compared to those in the 1st quartile was 0.008, 0.37 and 1.52 for those in the 2nd, 3rd, and 4th quartile (p<0.05). Those>3 years older by ECG were more likely to have obesity by BMI and BF%, see figure. Conclusions: Obesity, either by BMI or BF%, is associated with increased physiologic age as measured by AI-ECG, highlighting the importance of obesity as a health threat.

Introduction: We have previously shown that ECG-derived age (ECG-Age) predicts all-cause and cardiovascular (CV) mortality, reflecting physiologic age. We hypothesized that ECG-Age minus chronological age (Age-Gap) would be associated with coronary artery calcium (CAC) assessed by computer tomography. Methods: We developed a neural network model to predict ECG-Age using 12 lead ECGs from 399,750 training, 99,977 validation and 275,056 testing patients. We then applied the algorithm to 41,202 consecutive patients that from 1997-2020 underwent clinically indicated CAC and ECG within 1 year. Major modifiable CV risk factors were collected as part of preventive cardiology or general medical evaluations. Exclusion criteria were statin therapy, pacemakers, or history of coronary artery disease. Results: We included 41,202 subjects (68.5% males, 83.6% Caucasian), mean chronological age was 55.2±9.1 yrs and the ECG-Age was 56.01±9.3 yrs. The mean Age-Gap was -0.78±7 yrs, R 2 =0.78, p<0.0001. Mean CAC score was 140.2±532.3, and 21,483 (52%) had CAC >0. After adjustment for age and sex, those older by ECG (defined as having a positive Age-Gap) were more likely to have CAC>0 (OR 1.35, 95% CI 1.34-2.37 for those with >1 but <2 SD of a positive Age-Gap; and OR 1.80, 95% CI 1.34-2.37 for those with ≥2 SD of a positive Age-Gap), while those younger by ECG were less likely to have any CAC (OR 0.70, 95% CI 0.57-0.87 for those with >1 but <2 SD of a negative Age-Gap; and OR 0.75, 95% CI 0.67-0.84 for those with ≥2 SD of a negative Age-Gap), respectively. This association remained significant after multivariate adjustment, Fig. A and increased with CAC burden, Fig. B , all P for trend <0.01. Conclusions: The difference between physiologic AI-ECG age and chronologic age, something likely representing rate of biological aging, is associated with presence of CAC, further supporting the hypothesis that AI-ECG age can identify people more likely to have subclinical coronary atherosclerosis.

Background: The body Mass Index (BMI) is commonly used in clinical practice to screen for obesity and resulting cardiometabolic conditions. Nonetheless, BMI has limited utility as it cannot differentiate body fat (BF). Hypothesis: We tested the hypothesis that BF content measured by air displacement plethysmography (Bod-Pod®) had a stronger association with prevalent hypertension (HTN), diabetes mellitus (DM) and dyslipidemia (DLP) when compared to BMI. Methods: We performed a community-based cross-sectional study on adults attending an employee wellness center from January 2007-December 2011 who had had a body composition assessment with Bod-Pod®. We excluded subjects with history of myocardial infarction, coronary artery disease, congestive heart failure, stroke at baseline. The prevalence of HTN, DM and DLP was assessed across quartiles of BF% and BMI categories. Their association with BF% and BMI was evaluated using linear regression models that adjusted for age, sex, and white race. Results: We included 3,052 individuals; 68 % were women, and the mean age ± SD was 42.09±12.8, BMI was 27.9±6.2; BF% 31.88±10.69, 892 (29.2%) were obese by BMI. Cardiometabolic conditions were prevalent in 496 (16.2%) with HTN, 378 (12.4%) with DM and 743 (24.4%) with DLP. While the prevalence of DM, HTN and DLP increased across BF% quartiles (all p for linearity>0.01), this was not always the case across BMI categories (p for linearity<0.05 for HTN and DLP, and 0.04 for DM) see Figure A . Elevated BF %, better identified individuals with HTN (AUC 0.766 vs 0.625; p<0.001), DM (AUC 0.643 vs. 0.568; p<0.001), DLP (AUC 0.758 vs. 0.593; p<0.001). Conclusion: BF content is better associated with a higher prevalence of HTN, DM, and DLP. Highlighting the role of body composition assessment in primary prevention. Dyslipidemia.

Introduction: Newly developed Systematic Coronary Risk Evaluation-2 (SCORE-2) and the version for older people [(SCORE2-OP) ≥70 years] algorithms for 10-yr incident cardiovascular disease (CVD) have been derived incorporating European and US populations. Its performance has not been externally validated in community-based populations representative of real-world clinical practice. Hypothesis: We tested the hypothesis that the SCORE-2 and SCORE2-OP algorithms will accurately estimate 10-yr risk of first-onset CVD in this population. Methods: Consecutive patients who, between 1998-2000, sought primary care in Olmsted county, MN, and were followed-up using the Rochester Epidemiology Project. Inclusion criteria were set as those used in the derivation of the original algorithm. The composite outcome of CVD was defined as first myocardial infarction, ischemic stroke, or cardiovascular mortality. We compared predicted and observed events and generated C-statistics across predefined risk subgroups. Results: We included 22,858 adults, mean age of 55.11±11.58 (13.50% >70 yr) 54% females. After a mean follow-up of 9.55±1.5 yr, 2,145 events were observed. 6.39% of subjects for SCORE-2 and 59.88% using SCORE2-OP were considered at high risk. Overall, the SCORE-2 had better discrimination than the SCORE2-OP (C-statistic: 0.72 and 0.64, respectively) (Fig B-D). The algorithms performed better in individuals 50-69 yr while underpredicting in younger individuals and overpredicting CVD in ages above 70 (in the low and moderate risk group) (Fig A-C). Prediction was mostly similar between men, women and middle-aged individuals but demonstrated pronounced underprediction in older men (Fig B-D). Conclusions: The SCORE-2 Risk prediction tool performed with marginal results whereas the SCORE2-OP had poor performance when predicting CVD events in a community cohort representing real-world clinical practice in a non-European population.