Air Pollution in Cardio-Oncology and Unraveling the Environmental Nexus: JACC: CardioOncology State-of-the-Art Review.

Although recent advancements in cancer therapies have extended the lifespan of patients with cancer, they have also introduced new challenges, including chronic health issues such as cardiovascular disease arising from pre-existing risk factors or cancer therapies. Consequently, cardiovascular disease has become a leading cause of non-cancer-related death among cancer patients, driving the rapid evolution of the cardio-oncology field. Environmental factors, particularly air pollution, significantly contribute to deaths associated with cardiovascular disease and specific cancers, such as lung cancer. Despite these statistics, the health impact of air pollution in the context of cardio-oncology has been largely overlooked in patient care and research. Notably, the impact of air pollution varies widely across geographic areas and among individuals, leading to diverse exposure consequences. This review aims to consolidate epidemiologic and preclinical evidence linking air pollution to cardio-oncology while also exploring associated health disparities and environmental justice issues.

Neighborhood Walkability Is Associated With Lower Burden of Cardiovascular Risk Factors Among Cancer Patients.

Background: Modifiable cardiovascular risk factors constitute a significant cause of cardiovascular disease and mortality among patients with cancer. Recent studies suggest a potential link between neighborhood walkability and favorable cardiovascular risk factor profiles in the general population. Objectives: This study aimed to investigate whether neighborhood walkability is correlated with favorable cardiovascular risk factor profiles among patients with a history of cancer. Methods: We conducted a cross-sectional study using data from the Houston Methodist Learning Health System Outpatient Registry (2016-2022) comprising 1,171,768 adults aged 18 years and older. Neighborhood walkability was determined using the 2019 Walk Score and divided into 4 categories. Patients with a history of cancer were identified through International Classification of Diseases-10th Revision-Clinical Modification codes (C00-C96). We examined the prevalence and association between modifiable cardiovascular risk factors (hypertension, diabetes, smoking, dyslipidemia, and obesity) and neighborhood walkability categories in cancer patients. Results: The study included 121,109 patients with a history of cancer; 56.7% were female patients, and 68.8% were non-Hispanic Whites, with a mean age of 67.3 years. The prevalence of modifiable cardiovascular risk factors was lower among participants residing in the most walkable neighborhoods compared with those in the least walkable neighborhoods (76.7% and 86.0%, respectively). Patients with a history of cancer living in very walkable neighborhoods were 16% less likely to have any risk factor compared with car-dependent-all errands neighborhoods (adjusted OR: 0.84, 95% CI: 0.78-0.92). Sensitivity analyses considering the timing of events yielded similar results. Conclusions: Our findings demonstrate an association between neighborhood walkability and the burden of modifiable cardiovascular risk factors among patients with a medical history of cancer. Investments in walkable neighborhoods may present a viable opportunity for mitigating the growing burden of modifiable cardiovascular risk factors among patients with a history of cancer.

Elevated myocardial extracellular volume fraction is associated with the development of conduction pathway defects following transcatheter aortic valve replacement.

BACKGROUND: Transcatheter aortic valve replacement (TAVR) has become an established method of aortic stenosis treatment but suffers from the risk of heart block and pacemaker requirement. Risk stratification for patients who may develop heart block remains imperfect. Simultaneously, myocardial fibrosis as measured by cardiac magnetic resonance imaging (CMR) has been demonstrated as a prognostic indicator of ventricular recovery and mortality following TAVR. However, the association of CMR-based measures of myocardial fibrosis with post-TAVR conduction disturbances has not yet been explored. AIMS: We evaluated whether myocardial fibrosis, as measured by late gadolinium enhancement and extracellular volume (ECV) from CMR would be associated with new conduction abnormalities following TAVR. METHODS: One hundred seventy patients who underwent CMR within 2 months before TAVR were retrospectively reviewed. Septal late gadolinium enhancement (LGE) and ECV measurements were made as surrogates for replacement and interstitial fibrosis respectively. New conduction abnormalities were defined by the presence of transient or permanent atrioventricular block, new bundle branch blocks, and need for permanent pacemaker. Association of myocardial fibrosis and new conduction derangements were tested using receiver operator curve (ROC) and regression analysis in patients with and without pre-existing conduction issues. RESULTS: Forty-six (27.1%) patients developed post-TAVR conduction deficits. ECV was significantly higher among patients who experienced new conduction defects (26.2 ± 3.45% vs. 24.7% ± 4.15%, p value: 0.020). A greater fraction of patients that had new conduction defects had an elevated ECV of ≥26% (54.3% vs. 36.3%, p value: 0.026). ECV ≥ 26% was independently associated with the development of new conduction defects (odds ratio [OR]: 2.364, p value: 0.030). ROC analysis revealed a significant association of ECV with new conduction defects with an area under the receiver operating characteristic curve (AUC) of 0.632 (95% confidence interval: 0.555-0.705, p value: 0.005). The combination of prior right bundle branch block (RBBB) and ECV revealed a greater AUC of 0.779 (0.709-0.839, p value: <0.001) than RBBB alone (Delong p value: 0.049). No association of LGE/ECV with new conduction defects was observed among patients with pre-existing conduction disease. Among patients without baseline conduction disease, ECV was independently associated with the development of new conduction deficits (OR: 3.685, p value: 0.008). CONCLUSION: The present study explored the association of myocardial fibrosis, as measured by LGE and ECV with conduction deficits post-TAVR. Our results demonstrate an association of ECV, and thereby interstitial myocardial fibrosis, with new conduction derangement post-TAVR and introduce ECV as a potentially new risk stratification tool to identify patients at higher risk for needing post-TAVR surveillance and/or permanent pacemaker.

The Society for Cardiovascular Magnetic Resonance Registry at 150,000.

OBJECTIVES: To summarize the status of the SCMR Registry at 150,000 exams. BACKGROUND: Cardiovascular magnetic resonance (CMR) is increasingly utilized to evaluate expanding cardiovascular conditions. The SCMR Registry is a central repository for real-world clinical data to support cardiovascular research, including those relating to outcomes, quality improvement, and machine learning. The SCMR Registry is built on a regulatory-compliant, cloud-based infrastructure that houses searchable content and Digital Imaging and Communications in Medicine (DICOM) images. METHODS: The processes for data security, data submission, and research access are outlined. We interrogated the Registry and present a summary of its contents. RESULTS: Data were compiled from 154,458 CMR scans across 20 United States sites, containing 299,622,066 total images (~100 terabytes of storage). The human subjects had an average age of 58 years (range 1 month to >90 years old), were 44% female, 72% Caucasian, and had a mortality rate of 8%. The most common indication was cardiomyopathy (27%), and most frequently used current procedural terminology (CPT) code was 75561 (35%). Macrocyclic gadolinium-based contrast agents represented 89% of contrast utilization after 2015. Short-axis cines were performed in 99% of scans, short-axis LGE in 66%, and stress perfusion sequences in 30%. Mortality data demonstrated increased mortality in patients with left ventricular ejection fraction (LVEF) < 35%, the presence of wall motion abnormalities, stress perfusion defects, and infarct late gadolinium enhancement (LGE), compared to those without these markers. There were 456,678 patient-years of all-cause mortality follow-up, with a median follow-up time of 3.6 years. CONCLUSIONS: The vision of the SCMR Registry is to promote evidence-based utilization of CMR through a collaborative effort by providing a web mechanism for centers to securely upload de-identified data and images for research, education, and quality control. The Registry quantifies changing practice over time and supports large-scale real-world multicenter observational studies of prognostic utility. CONDENSED ABSTRACT: The SCMR Registry is a central regulatory-compliant cloud-based repository for real-world clinical data and DICOM images for multicenter cardiovascular research, including outcomes-based data. The Registry contains 299,622,066 DICOM images and 456,678 patient-years follow-up. Data compiled from 154,458 CMR scans across 20 US sites demonstrated cardiomyopathy as the most common indication and 89% macrocyclic gadolinium contrast utilization after 2015. There was an overall mortality rate of 8%, with higher rates in those with LVEF<35%, abnormal wall motion, ischemia presence, or infarct LGE. The Registry aims to promote evidence-based CMR utilization through a collaborative effort to positively impact cardiovascular outcomes.

Social Phenotyping for Cardiovascular Risk Stratification in Electronic Health Registries.

PURPOSE OF REVIEW: Evaluation of social influences on cardiovascular care requires a comprehensive analysis encompassing economic, societal, and environmental factors. The increased utilization of electronic health registries provides a foundation for social phenotyping, yet standardization in methodology remains lacking. This review aimed to elucidate the primary approaches to social phenotyping for cardiovascular risk stratification through electronic health registries. RECENT FINDINGS: Social phenotyping in the context of cardiovascular risk stratification within electronic health registries can be separated into four principal approaches: place-based metrics, questionnaires, ICD Z-coding, and natural language processing. These methodologies vary in their complexity, advantages and limitations, and intended outcomes. Place-based metrics often rely on geospatial data to infer socioeconomic influences, while questionnaires may directly gather individual-level behavioral and social factors. Z-coding, a relatively new approach, can capture data directly related to social determinant of health domains in the clinical context. Natural language processing has been increasingly utilized to extract social influences from unstructured clinical narratives-offering nuanced insights for risk prediction models. Each method plays an important role in our understanding and approach to using social determinants data for improving population cardiovascular health. These four principal approaches to social phenotyping contribute to a more structured approach to social determinant of health research via electronic health registries, with a focus on cardiovascular risk stratification. Social phenotyping related research should prioritize refining predictive models for cardiovascular diseases and advancing health equity by integrating applied implementation science into public health strategies.

Lipoprotein(a) and Coronary Plaque in Asymptomatic Individuals: The Miami Heart Study at Baptist Health South Florida.

BACKGROUND: Elevated levels of lipoprotein(a) (Lp(a)) are independently associated with an increased risk of atherosclerotic cardiovascular disease events. However, the mechanisms driving this association are poorly understood. We aimed to evaluate the association between Lp(a) and coronary plaque characteristics in a contemporary US cohort without clinical atherosclerotic cardiovascular disease, undergoing coronary computed tomography angiography, the noninvasive gold standard for the assessment of coronary atherosclerosis. METHODS: We used baseline data from the Miami Heart Study-a community-based, prospective cohort study-which included asymptomatic adults aged 40 to 65 years evaluated using coronary computed tomography angiography. Those taking any lipid-lowering therapies were excluded. Elevated Lp(a) was defined as ≥125 nmol/L. Outcomes included any plaque, coronary artery calcium score >0, maximal stenosis ≥50%, presence of any high-risk plaque feature (positive remodeling, spotty calcification, low-attenuation plaque, napkin ring), and the presence of ≥2 high-risk plaque features. RESULTS: Among 1795 participants (median age, 52 years; 54.3% women; 49.6% Hispanic), 291 (16.2%) had Lp(a) ≥125 nmol/L. In unadjusted analyses, individuals with Lp(a) ≥125 nmol/L had a higher prevalence of all outcomes compared with Lp(a) <125 nmol/L, although differences were only statistically significant for the presence of any coronary plaque and ≥2 high-risk features. In multivariable models, elevated Lp(a) was independently associated with the presence of any coronary plaque (odds ratio, 1.40, [95% CI, 1.05-1.86]) and with ≥2 high-risk features (odds ratio, 3.94, [95% CI, 1.82-8.52]), although only 35 participants had this finding. Among participants with a coronary artery calcium score of 0 (n=1200), those with Lp(a) ≥125 nmol/L had a significantly higher percentage of any plaque compared with those with Lp(a) <125 nmol/L (24.2% versus 14.2%; P<0.001). CONCLUSIONS: In this contemporary analysis, elevated Lp(a) was independently associated with the presence of coronary plaque. Larger studies are needed to confirm the strong association observed with the presence of multiple high-risk coronary plaque features.

Air Pollution and Adverse Cardiovascular Events After Coronary Artery Bypass Grafting: A 10-Year Nationwide Study.

Background: Increased particulate matter <2.5 µm (PM2.5) air pollution is associated with adverse cardiovascular outcomes. However, its impact on patients with prior coronary artery bypass grafting (CABG) is unknown. Objectives: The purpose of this study was to evaluate the association between major adverse cardiovascular events (MACE) (defined as myocardial infarction, stroke, or cardiovascular death) and air pollution after CABG. Methods: We linked 26,403 U.S. veterans who underwent CABG (2010-2019) nationally with average annual ambient PM2.5 estimates using residential address. Over a 5-year median follow-up period, we identified MACE and fit a multivariable Cox proportional hazard model to determine the risk of MACE as per PM2.5 exposure. We also estimated the absolute potential reduction in PM2.5 attributable MACE simulating a hypothetical PM2.5 lowered to the revised World Health Organization standard of 5 µg/m3. Results: The observed median PM2.5 exposure was 7.9 µg/m3 (IQR: 7.0-8.9 µg/m3; 95% of patients were exposed to PM2.5 above 5 µg/m3). Increased PM2.5 exposure was associated with a higher 10-year MACE rate (first tertile 38% vs third tertile 45%; P < 0.001). Adjusting for demographic, racial, and clinical characteristics, a 10 µg/m3 increase in PM2.5 resulted in 27% relative risk for MACE (HR: 1.27, 95% CI: 1.10-1.46; P < 0.001). Currently, 10% of total MACE is attributable to PM2.5 exposure. Reducing maximum PM2.5 to 5 µg/m3 could result in a 7% absolute reduction in 10-year MACE rates. Conclusions: In this large nationwide CABG cohort, ambient PM2.5 air pollution was strongly associated with adverse 10-year cardiovascular outcomes. Reducing levels to World Health Organization-recommended standards would result in a substantial risk reduction at the population level.

Environmental Pollution and Cardiovascular Disease: Part 2 of 2: Soil, Water, and Other Forms of Pollution.

With a growing body of evidence that now links environmental pollution to adverse cardiovascular disease (CVD) outcomes, pollution has emerged as an important risk factor for CVD. There is thus an urgent need to better understand the role of pollution in CVD, key pathophysiological mechanisms, and to raise awareness among health care providers, the scientific community, the general population, and regulatory authorities about the CV impact of pollution and strategies to reduce it. This article is part 2 of a 2-part state-of-the-art review on the topic of pollution and CVD-herein we discuss major environmental pollutants and their effects on CVD, highlighting pathophysiological mechanisms, and strategies to reduce CVD risk.

Environmental Pollution and Cardiovascular Disease: Part 1 of 2: Air Pollution.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Over the past 50 years, there has been a substantial decline in the incidence of CVD and related mortality in high-income countries, largely due to the mitigation of modifiable risk factors such as smoking, hypertension, and diabetes. However, a significant burden of CVD remains in low- to middle-income countries, despite their lower prevalence of traditional risk factors; other environmental factors, particularly pollution, play a significant role in this attributable risk. Mounting evidence underscores a strong association between pollution and adverse health effects, including CVD. This article is part 1 of a 2-part state-of-the-art review and discusses air pollution and its adverse effects on CVD, highlighting pathophysiological mechanisms and methods to reduce air pollution and exposure to these pollutants.

Historical neighborhood redlining and bystander CPR disparities in out-of-hospital cardiac arrest.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is associated with low survival rates. Bystander cardiopulmonary resuscitation (CPR) is essential for improving outcomes, but its utilization remains limited, particularly among racial and ethnic minorities. Historical redlining, a practice that classified neighborhoods for mortgage risk in 1930s, may have lasting implications for social and health outcomes. This study sought to investigate the influence of redlining on the provision of bystander CPR during witnessed OHCA. METHODS: We conducted an analysis using data from the comprehensive Cardiac Arrest Registry to Enhance Survival (CARES), encompassing 736,066 non-traumatic OHCA cases across the United States. The Home Owners' Loan Corporation (HOLC) map shapefiles were utilized to categorize census tracts of arrests into four grades (A signifying "best", B "still desirable", C "declining", and D "hazardous"). Multivariable hierarchical logistic regression models were employed to predict the likelihood of CPR provision, adjusting for various factors including age, sex, race/ethnicity, arrest location, calendar year, and state of occurrence. Additionally, we accounted for the percentage of Black residents and residents below poverty levels at the census tract level. RESULTS: Among the 43,186 witnessed cases of OHCA in graded HOLC census tracts, 37.2% received bystander CPR. The rates of bystander CPR exhibited a gradual decline across HOLC grades, ranging from 41.8% in HOLC grade A to 35.8% in HOLC grade D. In fully adjusted model, we observed significantly lower odds of receiving bystander CPR in HOLC grades C (OR 0.89, 95% CI 0.81-0.98, p = 0.016) and D (OR 0.86, 95% CI 0.78-0.95, p = 0.002) compared to HOLC grade A. CONCLUSION: Redlining, a historical segregation practice, is associated with reduced contemporary rates of bystander CPR during OHCA. Targeted CPR training in redlined neighborhoods may be imperative to enhance survival outcomes.

Association between socioeconomic and psychosocial factors with use of interventional and surgical treatments and outcomes in patients with myocardial infarction - Inpatient data of the largest European health care system.

BACKGROUND: Myocardial infarction (MI) is an important driver of both morbidity and mortality on a global scale. Elucidating social inequalities may help to identify vulnerable groups as well as treatment imbalances and guide efforts to improve care for MI. METHODS: All hospitalized patient-cases with confirmed MI 2005-2020 in Germany were included in the study and stratified for socioeconomic or psychosocial factors (SPF) and the impact of SPF on treatment usage and adverse in-hospital events was analyzed. RESULTS: Overall, 4,409,597 hospitalizations of MI patients were included; of these, 17,297 (0.4 %) were coded with SPF. These patients were more often of female sex (49.4 % vs. 36.9 %, P<0.001), older (median 77.0 [IQR: 65.0-84.0] vs. 73.0 [62.0-81.0] years, P<0.001) and revealed an aggravated cardiovascular profile. Although SPF were independently associated with increased usage of cardiac catheterization (OR 1.174 [95 %CI 1.136-1.212]) and percutaneous coronary intervention (OR 1.167 [95 %CI 1.130-1.205]), they were accompanied by higher risk for a prolonged length of in-hospital stay >7 days (OR 1.236 [95 %CI 1.198-1.276]) and >10 days (OR 1.296 [95 %CI 1.254-1.339]). While SPF were associated with increased risk for deep venous thrombosis and/or thrombophlebitis (OR 1.634 [95 %CI 1.427-1.870]), pulmonary embolism (OR 1.337 [95 %CI 1.149-1.555]), and acute renal failure (OR 1.170 [95 %CI 1.105-1.240), these SPF were inversely associated with in-hospital case-fatality (OR 0.461 [95 %CI 0.433-0.490]). CONCLUSIONS: This study demonstrates that SPF in hospitalized MI patients have significant impacts on treatments and outcomes. Fortunately, our data did not revealed an underuse of interventional treatments in MI patients with SPF.

Geographic proximity to cardiovascular clinical trial sites: A National analysis in the United States.

INTRODUCTION: Suboptimal geographical access to cardiovascular clinical trial sites (CV-CTS) may be a cause of inadequate demographic representation in contemporary trials. Thus, we investigate access to CV-CTS in the US. METHODS: We obtained the location of CV-CTS from Clinicaltrials.gov. We calculated the distance in kilometers from each ZIP code to the nearest CV-CTS, stratifying our results based on urban/rural setting, sex and race. RESULTS: We identified a total of 10,506 studies in 4,630 US ZIP codes (10.5 %), of those only 237 (5 %) were rural. The overall median CV-CTS distance was 5.8 km (IQR: 2.7, 15.8). For urban residents, this distance was 4.5 km (IQR: 2.3, 9.2), while for rural residents, it was 24.2 km (IQR: 13.8, 42.2). RESULTS: We revealed important disparities involving geographical proximity to cardiovascular clinical trial sites. Increasing the representation of these populations in clinical trials is paramount to improving the applicability of their findings to real-world settings.

Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.

Importance: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality. Objective: To investigate the association between image-based built environment and the prevalence of cardiometabolic disease in urban cities. Design, Setting, and Participants: This cross-sectional study used features extracted from Google satellite images (GSI) to measure the built environment and link them with prevalence of cardiometabolic disease. Convolutional neural networks, light gradient-boosting machines, and activation maps were used to assess the association with health outcomes and identify feature associations with coronary heart disease (CHD), stroke, and chronic kidney disease (CKD). The study obtained aerial images from GSI covering census tracts in 7 cities (Cleveland, Ohio; Fremont, California; Kansas City, Missouri; Detroit, Michigan; Bellevue, Washington; Brownsville, Texas; and Denver, Colorado). The study used census tract-level data from the US Centers for Disease Control and Prevention's 500 Cities project. The data were originally collected from the Behavioral Risk Factor Surveillance System that surveyed people 18 years and older across the country. Analyses were conducted from February to December 2022. Exposures: GSI images of built environment and cardiometabolic disease prevalence. Main Outcomes and Measures: Census tract-level estimated prevalence of CHD, stroke, and CKD based on image-based built environment features. Results: The study obtained 31 786 aerial images from GSI covering 789 census tracts. Built environment features extracted from GSI using machine learning were associated with prevalence of CHD (R2 = 0.60), stroke (R2 = 0.65), and CKD (R2 = 0.64). The model performed better at distinguishing differences between cardiometabolic prevalence between cities than within cities (eg, highest within-city R2 = 0.39 vs between-city R2 = 0.64 for CKD). Addition of GSI features both outperformed and improved the model that only included age, sex, race, income, education, and composite indices for social determinants of health (R2 = 0.83 vs R2 = 0.76 for CHD; P <.001). Activation maps from the features revealed certain health-related built environment such as roads, highways, and railroads and recreational facilities such as amusement parks, arenas, and baseball parks. Conclusions and Relevance: In this cross-sectional study, a significant portion of cardiometabolic disease prevalence was associated with GSI-based built environment using convolutional neural networks.

Enhancing cardiovascular risk prediction through AI-enabled calcium-omics.

Whole-heart coronary calcium Agatston score is a well-established predictor of major adverse cardiovascular events (MACE), but it does not account for individual calcification features related to the pathophysiology of the disease (e.g., multiple-vessel disease, spread of the disease along the vessel, stable calcifications, numbers of lesions, and density). We used novel, hand-crafted calcification features (calcium-omics); Cox time-to-event modeling; elastic net; and up and down synthetic sampling methods for imbalanced data, to assess MACE risk. We used 2457 CT calcium score (CTCS) images enriched for MACE events from our large no-cost CLARIFY program (ClinicalTrials.gov Identifier: NCT04075162). Among calcium-omics features, numbers of calcifications, LAD mass, and diffusivity (a measure of spatial distribution) were especially important determinants of increased risk, with dense calcification (> 1000HU, stable calcifications) associated with reduced risk Our calcium-omics model with (training/testing, 80/20) gave C-index (80.5%/71.6%) and 2-year AUC (82.4%/74.8%). Although the C-index is notoriously impervious to model improvements, calcium-omics compared favorably to Agatston and gave a significant difference (P < 0.001). The calcium-omics model identified 73.5% of MACE cases in the high-risk group, a 13.2% improvement as compared to Agatston, suggesting that calcium-omics could be used to better identity candidates for intensive follow-up and therapies. The categorical net-reclassification index was NRI = 0.153. Our findings from this exploratory study suggest the utility of calcium-omics in improved risk prediction. These promising results will pave the way for more extensive, multi-institutional studies of calcium-omics.

Houston Methodist cardiovascular learning health system (CVD-LHS) registry: Methods for development and implementation of an automated electronic medical record-based registry using an informatics framework approach.

Objectives: To investigate the potential value and feasibility of creating a listing system-wide registry of patients with at-risk and established Atherosclerotic Cardiovascular Disease (ASCVD) within a large healthcare system using automated data extraction methods to systematically identify burden, determinants, and the spectrum of at-risk patients to inform population health management. Additionally, the Houston Methodist Cardiovascular Disease Learning Health System (HM CVD-LHS) registry intends to create high-quality data-driven analytical insights to assess, track, and promote cardiovascular research and care. Methods: We conducted a retrospective multi-center, cohort analysis of adult patients who were seen in the outpatient settings of a large healthcare system between June 2016 - December 2022 to create an EMR-based registry. A common framework was developed to automatically extract clinical data from the EMR and then integrate it with the social determinants of health information retrieved from external sources. Microsoft's SQL Server Management Studio was used for creating multiple Extract-Transform-Load scripts and stored procedures for collecting, cleaning, storing, monitoring, reviewing, auto-updating, validating, and reporting the data based on the registry goals. Results: A real-time, programmatically deidentified, auto-updated EMR-based HM CVD-LHS registry was developed with ∼450 variables stored in multiple tables each containing information related to patient's demographics, encounters, diagnoses, vitals, labs, medication use, and comorbidities. Out of 1,171,768 adult individuals in the registry, 113,022 (9.6%) ASCVD patients were identified between June 2016 and December 2022 (mean age was 69.2 ± 12.2 years, with 55% Men and 15% Black individuals). Further, multi-level groupings of patients with laboratory test results and medication use have been analyzed for evaluating the outcomes of interest. Conclusions: HM CVD-LHS registry database was developed successfully providing the listing registry of patients with established ASCVD and those at risk. This approach empowers knowledge inference and provides support for efforts to move away from manual patient chart abstraction by suggesting that a common registry framework with a concurrent design of data collection tools and reporting rapidly extracting useful structured clinical data from EMRs for creating patient or specialty population registries.