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Cardiovascular disease (CVD) continues to be a major global health concern, underscoring the need for advancements in medical care. The use of electrocardiograms (ECGs) is crucial for diagnosing cardiac conditions. However, the reliance on professional expertise for manual ECG interpretation poses challenges for expanding accessible healthcare, particularly in community hospitals. To address this, there is a growing interest in leveraging automated and AI-driven ECG analysis systems, which can enhance diagnostic accuracy and efficiency, making quality cardiac care more accessible to a broader population. In this study, we implemented a novel deep two-dimensional convolutional neural network (2D-CNN) on a dataset of PTB-XL for cardiac disorder detection. The studies were performed on 2, 5, and 23 classes of cardiovascular diseases. The our network in classifying healthy/sick patients achived an AUC of 95% and an average accuracy of 87.85%. In 5-classes classification, our model achieved an AUC of 93.46% with an average accuracy of 89.87%. In a more complex scenario involving classification into 23 different classes, the model achieved an AUC of 92.18% and an accuracy of 96.88%. According to the experimental results, our model obtained the best classification result compared to the other methods based on the same public dataset. This indicates that our method can aid healthcare professionals in the clinical analysis of ECGs, offering valuable assistance in diagnosing CVD and contributing to the advancement of computer-aided diagnosis technology., (© 2024. The Author(s).)

Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospital. Cross-validation methods can be used to estimate the accuracy of such models on new patients originating from the same source, by repeated random splitting of the data. However, such estimates tend to be highly overoptimistic when compared to accuracy obtained from deploying models to sources not represented in the dataset, such as a new hospital. The increasing availability of multi-source medical datasets provides new opportunities for obtaining more comprehensive and realistic evaluations of expected accuracy through source-level cross-validation designs. In this study, we present a systematic empirical evaluation of standard K-fold cross-validation and leave-source-out cross-validation methods in a multi-source setting. We consider the task of electrocardiogram based cardiovascular disease classification, combining and harmonizing the openly available PhysioNet/CinC Challenge 2021 and the Shandong Provincial Hospital datasets for our study. Our results show that K-fold cross-validation, both on single-source and multi-source data, systemically overestimates prediction performance when the end goal is to generalize to new sources. Leave-source-out cross-validation provides more reliable performance estimates, having close to zero bias though larger variability. The evaluation highlights the dangers of obtaining misleading cross-validation results on medical data and demonstrates how these issues can be mitigated when having access to multi-source data., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Administrative healthcare databases can be utilised for research. The accuracy of the International Statistical Classification of Diseases and Related Health Problems, Tenth Edition, Australian Modification (ICD-10-AM) coding of cardiovascular conditions in New Zealand is not known and requires validation., Method: International Statistical Classification of Diseases and Related Health Problems, Tenth Edition, Australian Modification coded discharges for acute coronary syndrome (ACS), heart failure (HF) and atrial fibrillation (AF), in both primary and secondary diagnostic positions, were identified from four district health boards between 1 January 2019 and 31 June 2019. A sample was randomly selected for retrospective clinician review for evidence of the coded diagnosis according to contemporary diagnostic criteria. Positive predictive values (PPVs) for ICD-10-AM coding vs clinician review were calculated. This study is also known as All of New Zealand, Acute Coronary Syndrome-Quality Improvement (ANZACS-QI) 77., Results: A total of 600 cases (200 for each diagnosis, 5.0% of total identified cases) were reviewed. The PPV of ACS was 93% (95% confidence interval [CI] 89%-96%), HF was 93% (95% CI 89%-96%) and AF was 96% (95% CI 92%-98%). There were no differences in PPV between district health boards. PPV for ACS were lower in Māori vs non-Māori (72% vs 96%; p=0.004), discharge from non-Cardiology vs Cardiology services (89% vs 96%; p=0.048) and ICD-10-AM coding for unstable angina vs myocardial infarction (81% vs 95%; p=0.011). PPV for HF were higher in the primary vs secondary diagnostic position (100% vs 89%; p=0.001)., Conclusions: The PPVs of ICD-10-AM coding for ACS, HF, and AF were high in this validation study. ICD-10-AM coding can be used to identify these diagnoses in administrative databases for the purposes of healthcare evaluation and research., Competing Interests: Conflicts of Interest There are no conflicts of interest to disclose., (Copyright © 2024 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.)

Background: Sports medicine (injury and illnesses) requires distinct coding systems because the International Classification of Diseases is insufficient for sports medicine coding. The Orchard Sports Injury and Illness Classification System (OSIICS) is one of two sports medicine coding systems recommended by the International Olympic Committee. Regular updates of coding systems are required., Methods: For Version 15, updates for mental health conditions in athletes, sports cardiology, concussion sub-types, infectious diseases, and skin and eye conditions were considered particularly important., Results: Recommended codes were added from a recent International Olympic Committee consensus statement on mental health conditions in athletes. Two landmark sports cardiology papers were used to update a more comprehensive list of sports cardiology codes. Rugby union protocols on head injury assessment were used to create additional concussion codes., Conclusion: It is planned that OSIICS Version 15 will be translated into multiple new languages in a timely fashion to facilitate international accessibility. The large number of recently published sport-specific and discipline-specific consensus statements on athlete surveillance warrant regular updating of OSIICS., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Cardiac characteristics underlying the time/frequency domain features are limited and not comprehensive enough to reflect the temporal/dynamical nature of ECG patterns. This paper proposes a dynamical ECG recognition framework for human identification and cardiovascular diseases classification via a dynamical neural learning mechanism. The proposed method consists of two phases: a training phase and a test phase. In the training phase, cardiac dynamics within ECG signals is extracted (approximated) accurately by using radial basis function (RBF) neural networks through deterministic learning mechanism. The obtained cardiac system dynamics is represented and stored in constant RBF networks. An ECG signature is then derived from the extracted cardiac dynamics along the periodic ECG state trajectories. A bank of estimators is constructed using the extracted cardiac dynamics to represent the trained gait patterns. In the test phase, recognition errors are generated and taken as the similarity measure by comparing the cardiac dynamics of the trained ECG patterns and the dynamics of the test ECG pattern. Rapid recognition of a test ECG pattern begins with measuring the state of test pattern, and automatically proceeds with the evolution of the recognition error system. According to the smallest error principle, the test ECG pattern can be rapidly recognized. This kind of cardiac dynamics information represents the beat-to-beat temporal change of ECG modifications and the temporal/dynamical nature of ECG patterns. Therefore, the amount of discriminability provided by the cardiac dynamics is larger than the original signals. This paper further discusses the extension of the proposed method for cardiovascular diseases classification. The constructed recognition system can distinguish and assign dynamical ECG patterns to predefined classes according to the similarity of cardiac dynamics. Experiments are carried out on the FuWai and PTB ECG databases to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The complex landscape of cardiovascular diseases encompasses a wide range of related pathologies arising from diverse molecular mechanisms and exhibiting heterogeneous phenotypes. This variety of manifestations poses significant challenges in the development of treatment strategies. The increasing availability of precise phenotypic and multiomics data of cardiovascular disease patient populations has spurred the development of a variety of computational disease subtyping techniques to identify distinct subgroups with unique underlying pathogeneses. In this review, we outline the essential components of computational approaches to select, integrate, and cluster omics and clinical data in the context of cardiovascular disease research. We delve into the challenges faced during different stages of the analysis, including feature selection and extraction, data integration, and clustering algorithms. Next, we highlight representative applications of subtyping pipelines in heart failure and coronary artery disease. Finally, we discuss the current challenges and future directions in the development of robust subtyping approaches that can be implemented in clinical workflows, ultimately contributing to the ongoing evolution of precision medicine in health care., Competing Interests: Disclosures None.

The prevalence of cardiocerebrovascular disease (CVD) is continuously increasing, and it is the leading cause of human death. Since it is difficult for physicians to screen thousands of people, high-accuracy and interpretable methods need to be presented. We developed four machine learning-based CVD classifiers (i.e., multi-layer perceptron, support vector machine, random forest, and light gradient boosting) based on the Korea National Health and Nutrition Examination Survey. We resampled and rebalanced KNHANES data using complex sampling weights such that the rebalanced dataset mimics a uniformly sampled dataset from overall population. For clear risk factor analysis, we removed multicollinearity and CVD-irrelevant variables using VIF-based filtering and the Boruta algorithm. We applied synthetic minority oversampling technique and random undersampling before ML training. We demonstrated that the proposed classifiers achieved excellent performance with AUCs over 0.853. Using Shapley value-based risk factor analysis, we identified that the most significant risk factors of CVD were age, sex, and the prevalence of hypertension. Additionally, we identified that age, hypertension, and BMI were positively correlated with CVD prevalence, while sex (female), alcohol consumption and, monthly income were negative. The results showed that the feature selection and the class balancing technique effectively improve the interpretability of models., (© 2022. The Author(s).)

Cardiovascular care is expensive; hence, economic evaluation is required to estimate resources being consumed and to ensure their optimal utilization. There is dearth of data regarding cost analysis of treating various diseases including cardiac diseases from developing countries. The study aimed to analyze resource consumption in treating cardio-vascular disease patients in a super-specialty hospital. An observational and descriptive study was carried out from April 2017 to June 2018 in the Department of Cardiology, Cardio-Thoracic (CT) Centre of All India Institute of Medical Sciences, New Delhi, India. As per World Health Organization, common cardiovascular diseases i.e. Coronary Artery Disease (CAD), Rheumatic Heart Disease (RHD), Cardiomyopathy, Congenital heart diseases, Cardiac Arrhythmias etc. were considered for cost analysis. Medical records of 100 admitted patients (Ward & Cardiac Care Unit) of cardiovascular diseases were studied till discharge and number of patient records for a particular CVD was identified using prevalence-based ratio of admitted CVD patient data. Traditional Costing and Time Driven Activity Based Costing (TDABC) methods were used for cost computation. Per bed per day cost incurred by the hospital for admitted patients in Cardiac Care Unit, adult and pediatric cardiology ward was calculated to be Indian Rupee (INR) 28,144 (US$ 434), INR 22,210 (US$ 342) and INR 18,774 (US$ 289), respectively. Inpatient cost constituted almost 70% of the total cost and equipment cost accounted for more than 50% of the inpatient cost followed by human resource cost (28%). Per patient cost of treating any CVD was computed to be INR 2,47,822 (US $ 3842). Cost of treating Rheumatic Heart Disease was the highest among all CVDs followed by Cardiomyopathy and other CVDs. Cost of treating cardiovascular diseases in India is less than what has been reported in developed countries. Findings of this study would aid policy makers considering recent radical changes and massive policy reforms ushered in by the Government of India in healthcare delivery., Competing Interests: None declared.

Background: Pivotal trials of chimeric antigen receptor T-cell (CAR-T) have identified common toxicities but may have been underpowered to detect cardiovascular and pulmonary adverse events (CPAEs)., Objectives: This study sought to investigate CPAEs associated with commercial CD19-directed CAR-T therapy., Methods: In this retrospective, pharmacovigilance study, the authors used the Food and Drug Administration adverse event reporting system to identify CPAEs associated with axicabtagene-ciloleucel and tisagenlecleucel. The authors evaluated disproportionate reporting by the reporting odds ratio (ROR) and the lower bound of the information component 95% credibility interval (IC 025 >0 is deemed significant). Significant associations were further adjusted to age and sex (adj.ROR)., Results: The authors identified CAR-T reports of 2,657 patients, including 546 CPAEs (20.5%). CPAEs overlapped with cytokine release syndrome in 68.3% (373 of 546) of the reports. Compared with the full database, CAR-T was associated with overreporting of tachyarrhythmias (n = 74 [2.8%], adj.ROR = 2.78 [95% CI: 2.21-3.51]), cardiomyopathy (n = 69 [2.6%], adj.ROR = 3.51 [2.42-5.09]), pleural disorders (n = 46 [1.7%], adj.ROR = 3.91 [2.92-5.23]), and pericardial diseases (n = 11 [0.4%], adj.ROR = 2.26 [1.25-4.09], all IC 025 >0). Venous thromboembolic events (VTEs) were associated only with axicabtagene-ciloleucel therapy (n = 28 [1.6%], adj.ROR = 1.80 [1.24-2.62], IC 025 >0). Atrial fibrillation (n = 55) was the leading tachyarrhythmia, followed by ventricular arrhythmias (n = 14). Tachyarrhythmias and VTEs were reported more often following axicabtagene-ciloleucel than tisagenlecleucel in an age- and sex-adjusted model (adj.ROR = 1.82 [1.04-3.18] and adj.ROR = 2.86 [1.18-6.93], respectively). Finally, the fatality rate of CPAEs was 30.9%., Conclusions: In this largest post-marketing study to date, the authors identified an association between CAR-T and various CPAEs, including tachyarrhythmias, cardiomyopathy, pericardial and pleural disorders, and VTEs. These findings should be considered in the multidisciplinary assessment for and monitoring of CAR-T therapy recipients., Competing Interests: Funding Support and Author Disclosures This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748. This study was supported in part by NIH/NCI grant RO1-CA 233610 (Dr Herrmann). Dr Perales has received personal fees from Abbvie, Bellicum, Bristol Myers Squibb, Celgene, Cidara Theraputics, Incyte, Kite/Gilead, Medigene, Miltenyi, MolMed, Nektar Therapeutics, NexImmune, Novartis, Omeros, Merck, Servier, and Tekeda; has served on data safety and monitoring boards for Cidara Therapeutics, Medigene, and Servier; and has received clinical trial support from Incyte, Kite/Gilead, and Miltenyi. Data presented in this study do not represent the opinion of the United States Food and Drug Administration (FDA). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objective: To investigate whether dual-energy x-ray absorptiometry (DXA) estimates of adiposity improve risk prediction for cardiometabolic diseases over traditional surrogates, body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) in older women., Patients and Methods: We analyzed up to 9744 postmenopausal women aged 50 to 79 years participating in the Women's Health Initiative who underwent a DXA scan and were free of cardiovascular disease and diabetes at baseline (October 1993 to December 1998) and followed through September 2015. Baseline BMI, WC, WHR, and DXA-derived percent total-body and trunk fat (%TrF) were incorporated into multivariable Cox proportional hazards models to estimate the risk of incident diabetes, atherosclerosis-related cardiovascular diseases (ASCVDs), heart failure, and death. Concordance probability estimates assessed the relative discriminatory value between pairs of adiposity measures., Results: A total of 1327 diabetes cases, 1266 atherosclerotic cardiovascular disease (ASCVD) cases, 292 heart failure cases, and 1811 deaths from any cause accrued during a median follow-up of up to 17.2 years. The largest hazard ratio observed per 1 standard deviation increase of an adiposity measure was for %TrF and diabetes (1.77; 95% CI, 1.66-1.88) followed by %TrF and broadly defined ASCVD (1.22; 95% CI, 1.15-1.30). These hazard ratios remained significant for both diabetes (1.47; 95% CI, 1.37-1.57) and ASCVD (1.22; 95% CI, 1.14-1.31) even after adjusting for the best traditional surrogate measure of adiposity, WC. Percentage of trunk fat was also the only adiposity measure to demonstrate statistically significant improved concordance probability estimates over BMI, WC, and WHR for diabetes and ASCVD (all P<0.05)., Conclusion: DXA-derived estimates of abdominal adiposity in postmenopausal women may allow for substantially improved risk prediction of diabetes over standard clinical risk models. Larger DXA studies with complete lipid biomarker profiles and clinical trials are needed before firm conclusions can be made., (Copyright © 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Introduction: Previous cardiovascular disease (CVD) and myocardial involvement are common in coronavirus disease-19 (COVID-19). We investigated relationships between CVD, cardiac biomarkers and outcome in COVID-19., Methods: We analyzed n = 252 patients from a multicenter study and provided comparison according to the presence or absence of underlying CVD. Cardiac biomarkers high-sensitivity Troponin [upper reference of normality (URN) 35 pg/ml for Troponin I and 14 pg/ml for Troponin T] and natriuretic peptides (Nt-pro-B-type natriuretic peptide, URN 300 pg/ml and B-type natriuretic peptide, URN 100 pg/ml) were both available in n = 136., Results: Mean age was 69 ± 16 years (56% men, 31% with previous CVD). Raised hs-Troponin and natriuretic peptides were detected in 36 and 50% of the cases respectively. Age, chronic obstructive pulmonary disease, hemoglobin, hs-Troponin and natriuretic peptides were independently associated with underlying CVD (P < 0.05 for all). Compared with the normal biomarkers subgroups, patients with isolated hs-Troponin elevation had higher in-hospital mortality (31 vs. 4%, P < 0.05), similar CVD prevalence (15 vs. 11%) and trend towards higher D-dimer (930 vs. 397 ng/ml, P = 0.140). Patients with both biomarkers elevated had higher age, D-dimer, CVD and in-hospital mortality prevalence compared with other subgroups (all P < 0.05 for trend). Outcome analysis revealed previous CVD [model 1: OR 2.72 (95% CI 1.14-6.49), P = 0.024. model 2: OR 2.65 (95% CI 1.05-6.71), P = 0.039], hs-Troponin (log10) [OR 2.61 (95% CI 1.21-5.66), P = 0.015] and natriuretic peptides (log10) [OR 5.84 (95%CI 2.43-14), P < 0.001] to be independently associated with in-hospital mortality., Conclusion: In our population, previous CVD was part of a vulnerable phenotype including older age, comorbidities, increased cardiac biomarkers and worse prognosis. Patients with isolated increase in hs-Troponin suffered higher mortality rates despite low prevalence of CVD, possibly explained by higher COVID-19-related systemic involvement., (Copyright © 2021 Italian Federation of Cardiology - I.F.C. All rights reserved.)

Background: Nonalcoholic fatty liver disease (NAFLD) and metabolic dysfunction associated fatty liver disease (MAFLD) have important associations with cardiovascular disease (CVD). The main objective of this study was to compare the frequency of incidence rate of CVD in the NAFLD or MAFLD patients utilizing a large claims database., Methods: Using the JMDC database from April 2013 to March 2019, we retrospectively analyzed data for 1,542,688 and 2,452,949 people to estimate the relationship between CVD and NAFLD, MAFLD, respectively., Results: The incidence rates of CVD were 0.97 (95% CI 0.94-1.01) and 2.82 (95% CI 2.64-3.01) per 1000 person-years in the non-NAFLD and NAFLD groups, respectively, and 1.01 (95% CI 0.98-1.03) and 2.69 (95% CI 2.55-2.83) per 1000 person-years in the non-MAFLD and MAFLD groups, respectively. The overall prevalence of hypertriglyceridemia and diabetes mellitus (DM) was 13.1, and 4.2%, respectively, in the non-NAFLD group and 63.6, and 20.2%, respectively, in the NAFLD group. The overall prevalenceof hypertriglyceridemia and DM was 13.6 and 4.3%, respectively, in the non-MAFLD group and 64.1, and 20.6%, respectively, in the MAFLD group. HRs for CVD increased with hypertriglyceridemia and DM., Conclusions: Results indicated that incident rate of CVD increased with NAFLD/MAFLD; the complication rate of DM and hypertriglyceridemia among NAFLD/MAFLD patients is high and may affect the development of CVD., (© 2021. The Author(s).)

Atrial fibrillation (AF) has been associated with numerous diseases. However, whether AF is a cause or consequence of these diseases is uncertain. To clarify, we assessed the causal role of AF on ischemic heart disease (IHD), stroke, other cardiovascular disease (CVD) subtypes, type 2 diabetes mellitus (T2DM), and late-onset AD using bi-directional two-sample Mendelian randomization (MR) among people primarily of European descent. Genetically predicted log odds of AF was associated with any stroke (odds ratio (OR) 1.22, 95% CI 1.18 to 1.27), particularly cardioembolic stroke and possibly subdural hemorrhage, with sensitivity analyses showing similar positive findings. Genetically predicted AF was also associated with arterial thromboembolism (1.32, 1.13 to 1.53), and heart failure (1.26, 1.21 to 1.30). No association of genetically predicted AF with IHD, T2DM, cognitive function, or late-onset AD was found. Conversely, genetically predicted IHD, heart failure and possibly ischemic stroke, particularly cardioembolic stroke, were positively associated with AF. Atrial fibrillation plays a role in any stroke, arterial thromboembolism, and heart failure, corroborating current clinical guidelines on the importance of preventing these complications by effective AF management. In addition, patients with IHD, heart failure or possibly ischemic stroke might be predisposed to developing AF, with implications for management., (© 2021. The Author(s).)

Background: Limited convincing evidence is available of the relationship between habitual snoring and cardiovascular diseases (CVDs)., Research Question: Is habitual snoring associated with total CVD and CVD subtypes in different age groups of Chinese adults?, Study Design and Methods: The China Kadoorie Biobank study enrolled more than 0.5 million adults aged 30 to 79 years from 10 regions in China. Snoring status and other baseline characteristics were collected from 2004 to 2008, using an interviewer-administered laptop-based questionnaire. The current analysis included 489,583 participants without stroke or coronary heart disease at baseline. Cox proportional hazards models were used to calculate the adjusted hazard ratios (HRs) and 95% CIs of cardiovascular diseases (CVDs) for habitual snoring vs nonhabitual snoring., Results: During a median follow-up of 9.6 years, 130,935 participants developed CVDs. Associations between habitual snoring and CVDs varied with age. Among participants aged younger than 50 years at baseline, habitual snoring was associated with an increased risk of total CVD (HR, 1.11; 95% CI, 1.07-1.14) after adjustment for known CVD risk factors, including systolic BP. The corresponding HRs (95% CIs) for ischemic heart disease, ischemic stroke, and hemorrhagic stroke were 1.18 (1.12-1.24), 1.12 (1.05-1.19), and 1.05 (0.92-1.19), respectively. However, such associations in adults aged 50 to 64 years were much weaker, and no statistically significant association was observed among individuals aged ≥65 years. Age-specific risk estimates were generally similar across sex and obesity subgroups., Interpretation: Habitual snoring was associated with increased risks of total CVD, ischemic heart disease, ischemic stroke, but not hemorrhagic stroke in Chinese, and these associations were mainly limited to those aged <50 years. Clinicians in China are encouraged to identify snoring, particularly in younger adults., (Copyright © 2021. Published by Elsevier Inc.)

Background Guideline-based cardioprotective medical therapy is intended to reduce the burden of adverse cardiovascular and limb outcomes in patients with peripheral artery disease (PAD). However, contemporary data describing trends in use of medication remains limited. The present study, therefore, aims to investigate changes in use of cardioprotective medication in PAD. Methods and Results By using Danish national healthcare registries, we identified all patients with first-time diagnosis of PAD (1997-2016) and classified them into two groups: (1) PAD+ that includes all patients with PAD with a history of cardiovascular disease, ie, myocardial infarction, atrial fibrillation, and stroke (n=162 627); and (2) PAD (n=87 935) that comprise patients without a history of cardiovascular disease. We determined the use of medication in the first 12 months after the incident diagnosis of PAD and estimated age standardized 1-year mortality rates. Our results showed increase in use of cardioprotective medication throughout the study period in both groups. However, PAD+ had a higher use of medication (acetylsalicylic acid, 3.5%-48.4%; Clopidogrel, 0%-17.6%; vitamin K antagonists, 0.9%-7.8%; new oral anticoagulants, 0.0%-10.1%; Statins, 1.9%-58.1%; angiotensin-converting enzyme inhibitors, 1.2%-20.6%), compared with PAD (acetylsalicylic acid, 2.9%-54.4%; Clopidogrel, 0%-11.9%; vitamin K antagonists, 0.9%-2.4%; new oral anticoagulants, 0.0%-3.4%; Statins, 1.5%-56.9%; angiotensin-converting enzyme, 0.9%-17.2%), respectively. Furthermore, 1-year mortality rates in PAD declined with increased use of medications during study. Conclusions In this nationwide study, use of cardioprotective medication increased considerably with time, but compared to patients with other atherosclerotic diseases, there remains an underuse of guideline-based medical therapy in patients with PAD.

Objective: More knowledge about the development of sudden cardiac death (SCD) in the general population is needed to develop meaningful predictors of SCD. Our aim with this study was to estimate the incidence of SCD in the general population and examine the temporal changes, demographics and clinical characteristics., Methods: All participants in the Copenhagen City Heart Study were followed from 1993 to 2016. All death certificates, autopsy reports and national registry data were used to identify all cases of SCD., Results: A total of 14 562 subjects were included in this study. There were 8394 deaths with all information available, whereof 1335 were categorised as SCD. The incidence of SCD decreased during the study period by 41% for persons aged 40-90 years, and the standardised incidence rates decreased from 504 per 100 000 person-years (95% CI 447 to 569) to 237 per 100 000 person-years (95% CI 195 to 289). The incidence rate ratio of SCD between men and women ≤75 years was 1.99 (95% CI 1.62 to 2.46). The proportion of SCD of all cardiac deaths decreased during the observation period and decreased with increasing age. Men had more cardiovascular comorbidities (OR 1.34, 95% CI 1.07 to 1.68, p<0. 01), and SCD was the first registered manifestation of cardiac disease in 50% of all cases., Conclusion: The incidence of SCD in the general population has declined significantly during the study period but should be further investigated for more recent variations as well as novel risk predictors for persons with low to medium risk of SCD., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: To consolidate evidence to determine (i) the association between cardiovascular risk factors and health outcomes with coronavirus 2019 (COVID-19); and (ii) the impact of COVID-19 on cardiovascular health., Methods and Results: An umbrella review of systematic reviews was conducted. Fourteen medical databases and pre-print servers were searched from 1 January 2020 to 5 November 2020. The review focused on reviews rated as moderate or high-quality using the AMSTAR 2 tool. Eighty-four reviews were identified; 31 reviews were assessed as moderate quality and one was high-quality. The following risk factors were associated with higher mortality and severe COVID-19: renal disease [odds ratio (OR) (95% confidence interval) for mortality 3.07 (2.43-3.88)], diabetes mellitus [OR 2.09 (1.80-2.42)], hypertension [OR 2.50 (2.02-3.11)], smoking history [risk ratio (RR) 1.26 (1.20-1.32)], cerebrovascular disease [RR 2.75 (1.54-4.89)], and cardiovascular disease [OR 2.65 (1.86-3.78)]. Liver disease was associated with higher odds of mortality [OR 2.81 (1.31-6.01)], but not severe COVID-19. Current smoking was associated with a higher risk of severe COVID-19 [RR 1.80 (1.14-2.85)], but not mortality. Obesity associated with higher odds of mortality [OR 2.18 (1.10-4.34)], but there was an absence of evidence for severe COVID-19. In patients hospitalized with COVID-19, the following incident cardiovascular complications were identified: acute heart failure (2%), myocardial infarction (4%), deep vein thrombosis (7%), myocardial injury (10%), angina (10%), arrhythmias (18%), pulmonary embolism (19%), and venous thromboembolism (25%)., Conclusion: Many of the risk factors identified as associated with adverse outcomes with COVID-19 are potentially modifiable. Primary and secondary prevention strategies that target cardiovascular risk factors may improve outcomes for people following COVID-19., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Aims: Crossover between direct oral anticoagulants (DOACs) has been underinvestigated, but happens frequently in clinical practice. The purpose of this study was to evaluate causes, rates and outcomes of a DOAC-to-DOAC switch., Methods: Patients receiving their first DOAC prescription at the Anticoagulation Center, Cardiology Dept, Bologna-Bellaria Hospital in 2017-2018 were consecutively included and prospectively followed up. DOAC-to-DOAC switch was the main outcome; causes of switch (cardiovascular events and noncardiovascular drug-related adverse events) had direct biannual assessment before and after the switch., Results: Among 300 patients enrolled (mean age = 79.3 years, mean follow-up = 1.5 years), with no difference in cardiovascular risk factors depending on index DOAC, 13% underwent DOAC-to-DOAC switch, minor bleeding and noncardiovascular adverse events being the most frequent causes. Dabigatran carried a three-fold increase in risk of switch compared with other DOACs, but the mean age of patients who switched was 83. Factors leading to switch resolved in 87% of cases afterwards. Annual rates of cardiovascular/noncardiovascular V events did not differ before and after the switch., Conclusion: DOAC-to-DOAC switch happens in 9% of patients using DOAC each year, and seems not to impact rates of cardiovascular events after switch. Dabigatran, in the elderly, might be associated with a higher risk of DOAC-to-DOAC switch. Further studies are needed to confirm the long-term safety and effectiveness of switching paradigm., (Copyright © 2020 Italian Federation of Cardiology - I.F.C. All rights reserved.)

The National Heart, Lung, and Blood Institute and the Cardiovascular Medical Research and Education Fund held a workshop on the application of pulmonary vascular disease omics data to the understanding, prevention, and treatment of pulmonary vascular disease. Experts in pulmonary vascular disease, omics, and data analytics met to identify knowledge gaps and formulate ideas for future research priorities in pulmonary vascular disease in line with National Heart, Lung, and Blood Institute Strategic Vision goals. The group identified opportunities to develop analytic approaches to multiomic datasets, to identify molecular pathways in pulmonary vascular disease pathobiology, and to link novel phenotypes to meaningful clinical outcomes. The committee suggested support for interdisciplinary research teams to develop and validate analytic methods, a national effort to coordinate biosamples and data, a consortium of preclinical investigators to expedite target evaluation and drug development, longitudinal assessment of molecular biomarkers in clinical trials, and a task force to develop a master clinical trials protocol for pulmonary vascular disease., Competing Interests: Funding Support and Author Disclosures Several authors report funding support from the National Institutes of Health/National Heart, Lung, and Blood Institute (K08HL128802 to Dr. Oldham; R35HL140019 to Dr. Aldred; R01HL146588 to Dr. Brittain; R01HL135142, R01HL137927, R01HL089856, and R01HL147148 to Dr. Cho; R01HL136603 to Dr. Desai; K01HL146980 to Dr. Kelly; U01HL125215 to Dr. Leopold; and K23HL144418 to Dr. Modena). Dr. Oldham has received a research grant from the Cardiovascular Medical Research and Education Fund. Dr. Leopold was supported by grants from the American Heart Association. Dr. Wilkins was supported by the British Heart Foundation (RE/18/4/34215 and SP/18/10/33975). Dr. Hemnes has served as a consultant for Actelion, Bayer, Complexa, and United Therapeutics; and owns shares in PHPrecisionMed, all outside of the submitted work. Dr. Chan has served as a consultant for Zogenix, Aerpio, and United Therapeutics; is a director, officer, and shareholder in Synhale Therapeutics; has held research grants from Actelion and Pfizer; and has filed patent applications regarding the targeting of BMP signaling and metabolic pathways in pulmonary hypertension, all outside of the submitted work. Dr. Cho has received grant support from Bayer and GlaxoSmithKline; and served as a consultant for Genentech, AstraZeneca, and Illumina, all outside of the submitted work. Dr. Desai has served as a consultant for Novartis, outside of the submitted work. Dr. Modena has received honoraria from AstraZeneca, Genentech, GlaxoSmithKline, Regeneron, Sanofi, and Teva for consulting or lectures in the past; and has current research funding from Genentech and GlaxoSmithKline, all outside of the submitted work. Dr. Rhodes has received personal advisory board fees from Janssen and United Therapeutics, outside of the submitted work. Dr. Wilkins has consulted with Actelion, Novartis, GlaxoSmithKline, and MorphogenIX in the development of biomarkers for pulmonary hypertension, all outside of the submitted work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. All rights reserved.)

Background: Data on long-term cardiovascular outcomes in systemic lupus erythematosus (SLE) are sparse., Objectives: This study sought to examine the long-term risk and prognosis associated with cardiovascular outcomes, including heart failure (HF), in patients with SLE., Methods: Using Danish administrative registries, risks of outcomes were compared between SLE patients (diagnosed 1996 to 2018, no history of cardiovascular disease) and age-, sex-, and comorbidity-matched control subjects from the background population (matched 1:4). Furthermore, mortality following HF diagnosis was compared between SLE patients developing HF and age- and sex-matched non-SLE control subjects with HF (matched 1:4)., Results: A total of 3,411 SLE patients (median age: 44.6 years [25th to 75th percentile: 31.9 to 57.0 years]; 14.1% men) were matched with 13,644 control subjects. The median follow-up was 8.5 years (25th to 75th percentile: 4.0 to 14.4 years). Absolute 10-year risks of outcomes were: HF, 3.71% (95% confidence interval [CI]: 3.02% to 4.51%) for SLE patients, 1.94% (95% CI: 1.68% to 2.24%) for control subjects; atrial fibrillation, 4.35% (95% CI: 3.61% to 5.18%) for SLE patients, 2.82% (95% CI: 2.50% to 3.16%) for control subjects; ischemic stroke, 3.75% (95% CI: 3.06% to 4.54%) for SLE patients, 1.92% (95% CI: 1.66% to 2.20%) for control subjects; myocardial infarction, 2.17% (95% CI: 1.66% to 2.80%) for SLE patients, 1.49% (95% CI: 1.26% to 1.75%) for control subjects; venous thromboembolism, 6.03% (95% CI: 5.17% to 6.98%) for SLE patients, 1.68% (95% CI: 1.44% to 1.95%) for control subjects; and the composite of implantable cardioverter-defibrillator implantation/ventricular arrhythmias/cardiac arrest, 0.89% (95% CI: 0.58% to 1.31%) for SLE patients, 0.30% (95% CI: 0.20% to 0.43%) for control subjects. SLE with subsequent HF was associated with higher mortality compared with HF without SLE (adjusted hazard ratio: 1.50; 95% CI: 1.08 to 2.08)., Conclusions: SLE patients had a higher associated risk of HF and other cardiovascular outcomes compared with matched control subjects. Among patients developing HF, a history of SLE was associated with higher mortality., Competing Interests: Funding Support and Author Disclosures All authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

The prevalence of cardiovascular disease (CVD) in pregnancy, both diagnosed and previously unknown, is rising, and CVD is a leading cause of maternal morbidity and mortality. Historically, women of child-bearing potential have been underrepresented in research, leading to lasting knowledge gaps in the cardiovascular care of pregnant and lactating women. Despite these limitations, clinicians should be familiar with the safety of frequently used diagnostic and therapeutic interventions to adequately care for this at-risk population. This review, the fourth of a 5-part series, provides evidence-based recommendations regarding the use of common cardiovascular diagnostic tests and medications in pregnant and lactating women., Competing Interests: Funding Support and Author Disclosures Dr. Bello is supported by National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI) Grants K23 HL136853-03 and R01 HL153382-01. Dr. Quesada is supported by NIH/NHLBI Gant K23 HL151867-01. Dr. Volgman is supported by NIH/National Institute of Nursing Research (NINR) Grant R01 NR018443 and Novartis TQJ230A12001 epidemiological study on lipoprotein a in patients with CVD. Dr. Bairey Merz serves as Board of Director for iRhythm; and receives personal fees paid through CSMC from Abbott Diagnostics, and Sanofi. Dr. Brown is a co-author on Up to Date–Maternal Mortality. Dr. Volgman has stock ownership in Apple Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Maternal morbidity and mortality continue to rise in the United States, with cardiovascular disease as the leading cause of maternal deaths. Congenital heart disease is now the most common cardiovascular condition encountered during pregnancy, and its prevalence will continue to grow. In tandem with these trends, maternal cardiovascular health is becoming increasingly complex. The identification of women at highest risk for cardiovascular complications is essential, and a team-based approach is recommended to optimize maternal and fetal outcomes. This document, the second of a 5-part series, will provide practical guidance from pre-conception through postpartum for cardiovascular conditions that are predominantly congenital or heritable in nature, including aortopathies, congenital heart disease, pulmonary hypertension, and valvular heart disease., Competing Interests: Funding Support and Author Disclosures Dr. Bairey Merz has served as a consultant for Abbott and Sanofi; and has served on the Board of Directors for iRhythm. Dr. Bello is supported by the National Institutes of Health/National Heart, Lung, and Blood Institute (K23 HL136853-03, R01 HL153382-01). Dr. Gomberg-Maitland has received research grant support to GWU-MFA from Acceleron, Bayer, Complexa, and United Therapeutics; and has served as a consultant for Actelion, Altavant, Acceleron, Bayer, Gilead, Insemed, Reata, and United Therapeutics. Dr. Park has served as a consultant for Abbott. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Acquired cardiovascular conditions are a leading cause of maternal morbidity and mortality. A growing number of pregnant women have acquired and heritable cardiovascular conditions and cardiovascular risk factors. As the average age of childbearing women increases, the prevalence of acute coronary syndromes, cardiomyopathy, and other cardiovascular complications in pregnancy are also expected to increase. This document, the third of a 5-part series, aims to provide practical guidance on the management of such conditions encompassing pre-conception through acute management and considerations for delivery., Competing Interests: Funding Support and Author Disclosures Supported by grants from the National Institutes of Health (NIH)/National Heart, Lung, and Blood Institute (NHLBI) to Dr. Bello (K23 HL136853-03, R01 HL153382-01), and Dr. Shah (5K08HL136850, Women As One); from the Clinical and Translational Science Institute (CTSI) to Dr. Minissian (F31NR015725; CTSI support UL1TR000124 and UL1TR001881-01); and the Preventive Cardiovascular Nurses Association through the American Nurses Foundation (#5362). Additional support was provided by the Cedars-Sinai Department of Obstetrics and Gynecology, Geri and Richard Brawerman Nursing Institute, Simms/Mann Family Foundation, Department of Nursing Research, Barbra Streisand Women’s Heart Center. Beta Chi Chapter. Cedars-Sinai Precision Health Institute (#42254). Dr. Park has received funding from Abbott. Dr. Bairey Merz has received research grants from Sanofi and Abbott; has received consulting fees from Bayer; and has served on the board for rRhythm. Dr. Minissian has received consulting fees from Amgen, Vox Media, Medtelligence, Minneapolis Heart Institute, Primed, Good Samaritan Hospital, Los Angeles, California, Cardiometabolic Health Congress, American Heart Association, National Lipid Association, Preventive Cardiovascular Nurses Association, and the American College of Cardiology; and has been a medical advisory board member for the North American Center for Continuing Medical Education, LLC. Dr. Reynolds has received in-kind donations for unrelated studies from Abbott Vascular, Siemens, and BioTelemetry. Dr. Volgman has stock ownership in Apple Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Published by Elsevier Inc.)

The specialty of cardio-obstetrics has emerged in response to the rising rates of maternal morbidity and mortality related to cardiovascular disease (CVD) during pregnancy. Women of childbearing age with or at risk for CVD should receive appropriate counseling regarding maternal and fetal risks of pregnancy, medical optimization, and contraception advice. A multidisciplinary cardio-obstetrics team should ensure appropriate monitoring during pregnancy, plan for labor and delivery, and ensure close follow-up during the postpartum period when CVD complications remain common. The hemodynamic changes throughout pregnancy and during labor and delivery should be considered with respect to the individual cardiac disease of the patient. The fourth trimester refers to the 12 weeks after delivery and is a key time to address contraception, mental health, cardiovascular risk factors, and identify any potential postpartum complications. Women with adverse pregnancy outcomes are at increased risk of long-term CVD and should receive appropriate education and longitudinal follow-up., Competing Interests: Funding Support and Author Disclosures Supported by National Institutes of Health/National Heart, Lung, and Blood Institute grants K23 HL136853-03 and R01 HL153382-01 (Dr. Bello). Dr. Brown is a coauthor of UpToDate. Dr. Park has served as a consultant for Abbott Diagnostics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background Metabolic dyslipidemia (high triglyceride) and low high-density lipoprotein cholesterol (HDL-C) is highly prevalent in type 2 diabetes mellitus (T2DM). The extent to which diabetes mellitus-related abnormalities in the triglyceride-HDL-C profile associates with cardiovascular disease (CVD) risk is incompletely understood. We evaluated the associations of triglyceride and HDL-C status with CVD outcomes in individuals with T2DM. Methods and Results We analyzed data from 4199 overweight/obese adults with T2DM free of CVD with available data on triglyceride and HDL-C at baseline (2001-2004) in the Look AHEAD (Action for Health in Diabetes) study. We used Cox proportional models to estimate hazard ratios (HRs) and 95% CIs of: (1) composite CVD outcome (myocardial infarction, stroke, hospitalization for angina, and/or death from cardiovascular causes); (2) coronary artery disease events; and (3) cerebrovascular accidents (stroke). Of the 4199 participants, 62% (n=2600) were women, with a mean age of 58 years (SD, 7), and 40% (n=1659) had metabolic dyslipidemia at baseline. Over a median follow-up of 9.5 years (interquartile range, 8.7-10.3), 500 participants experienced the composite CVD outcome, 396 experienced coronary artery disease events, and 100 experienced stroke. Low HDL-C was associated with higher hazards of the composite CVD outcome (HR, 1.36; 95% CI, 1.12-1.64 [ P =0.002]) and coronary artery disease events (HR, 1.46; 95% CI, 1.18-1.81 [ P =0.001]) but not stroke (HR, 1.38; 95% CI, 0.90-2.11 [ P =0.140]). Compared with patients with normal triglyceride and normal HDL, participants with metabolic dyslipidemia had higher risks of the composite CVD outcome (HR, 1.30; 95% CI, 1.03-1.63 [ P =0.025]) and coronary artery disease events (HR, 1.48; 95% CI, 1.14-1.93 [ P =0.003]) but not stroke (HR, 1.23; 95% CI, 0.74-2.05 [ P =0.420]). Conclusions In a large sample of overweight/obese individuals with T2DM, metabolic dyslipidemia was associated with higher risks of CVD outcomes. Our findings highlight the necessity to account for metabolic dyslipidemia in CVD risk stratification among patients with T2DM. Registration URL: https://www.lookaheadtrial.org; Unique identifier: NCT00017953.

Background Socioeconomic status is associated with differences in risk factors of cardiovascular disease and increased risks of cardiovascular disease and mortality. However, it is unclear whether an association exists between cardiovascular disease and income, a common measure of socioeconomic status, among patients with hypertension. Methods and Results This population-based longitudinal study comprised 479 359 patients aged ≥19 years diagnosed with essential hypertension. Participants were categorized by income and blood pressure levels. Primary end point was all-cause and cardiovascular mortality and secondary end points were cardiovascular events, a composite of cardiovascular death, myocardial infarction, and stroke. Low income was significantly associated with high all-cause (hazard ratio [HR], 1.26; 95% CI, 1.23-1.29, lowest versus highest income) and cardiovascular mortality (HR, 1.31; 95% CI, 1.25-1.38) as well as cardiovascular events (HR, 1.07; 95% CI, 1.05-1.10) in patients with hypertension after adjusting for age, sex, systolic blood pressure, body mass index, smoking status, alcohol consumption, physical activity, fasting glucose, total cholesterol, and the use of aspirin or statins. In each blood pressure category, low-income levels were associated with high all-cause and cardiovascular mortality and cardiovascular events. The excess risks of all-cause and cardiovascular mortality and cardiovascular events associated with uncontrolled blood pressure were more prominent in the lowest income group. Conclusions Low income and uncontrolled blood pressure are associated with increased all-cause and cardiovascular mortality and cardiovascular events in patients with hypertension. These findings suggest that income is an important aspect of social determinants of health that has an impact on cardiovascular outcomes in the care of hypertension.

Background It is unclear what office blood pressure (BP) is the optimal treatment target range in patients with hypertension. Methods and Results Using the Korean National Health Insurance Service database, we extracted the data on 479 359 patients with hypertension with available BP measurements and no history of cardiovascular events from 2002 to 2011. The study end point was major cardiovascular events (MACE), a composite of cardiovascular death, myocardial infarction, or stroke. This cohort study evaluated the association of BP levels (<120/<70, 120-129/70-79, 130-139/80-89, 140-149/90-99, and ≥150/≥100 mm Hg) with MACE. During a median follow-up of 9 years, 55 401 MACE were documented in our cohort. The risk of MACE was the lowest (adjusted hazard ratio [HR], 0.79; 95% CI, 0.76-0.84) at BP level of <120/<70 mm Hg, and was the highest (HR, 1.32; 95% CI, 1.29-1.36) at ≥150/≥100 mm Hg in comparison with 130 to 139/80 to 89 mm Hg. These results were consistent in all age groups and both sexes. Among patients treated with antihypertensive medication (n=237 592, 49.5%), in comparison with a BP level of 130 to 139/80 to 89 mm Hg, the risk of MACE was significantly higher in patients with elevated BP (≥140/≥90 mm Hg), but not significantly lower in patients with BP of <130/<80 mm Hg. Low BP <120/70 mm Hg was associated with increased risk of all-cause or cardiovascular death in all age groups. Conclusions BP level is significantly correlated with the risk of MACE in all Korean patients with hypertension. However, there were no additional benefits for MACE amongst those treated for hypertension with BP <120/70 mm Hg.

Objective: To determine the ability of postprandial lipoprotein subclass concentrations to stratify patients with respect to their risk for cardiovascular disease (CVD)., Methods: Using the Framingham cardiovascular disease risk score (FRS) algorithm, a total of 112 consecutive patients referred for community health screening were stratified into two groups: (a) low-risk (FRS < 10%) and (b) intermediate/high-risk (FRS ≥ 10%). Serum lipoprotein subclass concentrations were determined by Vertical Auto Profile (VAP-II)., Results: Fasting and postprandial levels of LDL4, HDL2, VLDL1 + 2, VLDL3, and RLP, as well as fasting levels of ApoB and postprandial levels of LDL3 and IDL1, were significantly different in the intermediate/high risk FRS group vs. the low-risk group (P < 0.05). Correlations between Framingham CVD risk and LDL3, LDL4, IDL1, VLDL1 + 2, VLDL3, RLP, and ApoB were positive while negative for HDL2 in both the fasting and postprandial states. Intermediate/high risk for CVD was shown to be significantly associated with both fasting and postprandial levels of VLDL1 + 2 and RLP, as well as with postprandial LDL4 and VLDL3, as determined using forward conditional logistic regression analysis. Postprandial levels of VLDL1 + 2 were better at identifying patients in the intermediate/high-risk FRS group than fasting levels, although the differences were not significant due to overlapping reference intervals. In addition, the association between RLP and VLDL subclasses relative to Framingham CVD risk increased significantly in the postprandial state (ΔR 2  = 0.023; ΔF = 7.178; ΔP = 0.025) but not in the fasting state., Conclusions: The use of postprandial lipoprotein subclass concentrations is not inferior to the use of fasting levels in identifying intermediate/high-risk FRS individuals. In addition, changes in RLP and VLDL subclass concentrations in fasting vs. postprandial states may reveal lipid metabolic mechanisms associated with CVD., (Copyright © 2020 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)

Background The incidence of cardiovascular disease among pregnant women is rising in the United States. Data on racial disparities for the major cardiovascular events during pregnancy are limited. Methods and Results Pregnant and post-partum women hospitalized from January 2007 to December 2017 were identified from the Nationwide Inpatient Sample. The outcomes of interest included: in-hospital mortality, myocardial infarction, stroke, pulmonary embolism, and peripartum cardiomyopathy. Multivariate regression analysis was used to assess the independent association between race and in-hospital outcomes. Among 46 700 637 pregnancy-related hospitalizations, 21 663 575 (46.4%) were White, 6 302 089 (13.5%) were Black, and 8 914 065 (19.1%) were Hispanic. The trends of mortality and stroke declined significantly in Black women, but however, were mostly unchanged among White women. The incidence of mortality and cardiovascular morbidity was highest among Black women followed by White women, then Hispanic women. The majority of Blacks (62.3%) were insured by Medicaid while the majority of White patients had private insurance (61.9%). Most of Black women were below-median income (71.2%) while over half of the White patients were above the median income (52.7%). Compared with White women, Black women had the highest mortality with adjusted odds ratio (aOR) of 1.45, 95% CI (1.21-1.73); myocardial infarction with aOR of 1.23, 95% CI (1.06-1.42); stroke with aOR of 1.57, 95% CI (1.41-1.74); pulmonary embolism with aOR of 1.42, 95% CI (1.30-1.56); and peripartum cardiomyopathy with aOR of 1.71, 95 % CI (1.66-1.76). Conclusions Significant racial disparities exist in major cardiovascular events among pregnant and post-partum women. Further efforts are needed to minimize these differences.

Racial disparities in cardiovascular and cerebrovascular health outcomes are well described, and recent research has shed light on the mechanistic underpinnings of those disparities. However, "race" is a social construct that is poorly defined and continually evolving and is historically based on faulty premises. The continued categorization by race in physiological research suggests that there are inherent differences between races, rather than addressing the specific underlying factors that result in health disparities between groups. The purpose of this Perspectives article is to provide a brief history of the genesis of categorization by race, why such categorization should be reconsidered in physiology research, and offer recommendations to more directly investigate the underlying factors that result in group disparities in cardiovascular and cerebrovascular health.

Background: Monogenic diseases are individually rare but collectively common, and are likely underdiagnosed., Objectives: The purpose of this study was to estimate the prevalence of monogenic cardiovascular diseases (MCVDs) and potentially missed diagnoses in a cardiovascular cohort., Methods: Exomes from 8,574 individuals referred for cardiac catheterization were analyzed. Pathogenic/likely pathogenic (P/LP) variants associated with MCVD (cardiomyopathies, arrhythmias, connective tissue disorders, and familial hypercholesterolemia were identified. Electronic health records (EHRs) were reviewed for individuals harboring P/LP variants who were predicted to develop disease (G+). G+ individuals who did not have a documented relevant diagnosis were classified into groups of whether they may represent missed diagnoses (unknown, unlikely, possible, probable, or definite) based on relevant diagnostic criteria/features for that disease., Results: In total, 159 P/LP variants were identified; 2,361 individuals harbored at least 1 P/LP variant, of whom 389 G+ individuals (4.5% of total cohort) were predicted to have at least 1 MCVD. EHR review of 342 G+ individuals predicted to have 1 MCVD with sufficient EHR data revealed that 52 had been given the relevant clinical diagnosis. The remaining 290 individuals were classified as potentially having an MCVD as follows: 193 unlikely (66.6%), 50 possible (17.2%), 30 probable (10.3%), and 17 definite (5.9%). Grouping possible, probable, definite, and known diagnoses, 149 were considered to have an MCVD. Novel MCVD pathogenic variants were identified in 16 individuals., Conclusions: Overall, 149 individuals (1.7% of cohort) had MCVDs, but only 35% were diagnosed. These patients represents a "missed opportunity," which could be addressed by greater use of genetic testing of patients seen by cardiologists., (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Primary prevention of cardiovascular disease (CVD) has been traditionally guided by individual risk factors such hypertension and hypercholesterolaemia. An absolute risk-based approach is more effective., Objective: The aim of this article is to outline the superiority of an absolute risk-based approach when compared with individual risk factor management for the primary prevention of CVD, and to elaborate on the derivation and use of the Australian absolute CVD risk calculator., Discussion: An absolute risk-based approach is superior to the traditional individual risk factor approach when identifying which patients would benefit most from the prescription of blood pressure-lowering and lipid-lowering medications.

Cardiotoxicities are associated with immune checkpoint inhibitor (ICI) therapy. Recent case series and retrospective studies have shown that cardiac immune-related adverse events (irAEs) are rare but potentially fatal complications of immunotherapy, with various underlying risk factors such as combinations of different ICIs. High mortality rates and overreactive inflammation have been observed with ICI-associated cardiotoxicities, highlighting the necessity of baseline and serial evaluations and the identification and management of cardiac irAEs as early as possible. The clinical presentations of irAEs range from asymptomatic cardiac biomarker elevation, myocarditis and pericardial diseases to heart failure and mild to fatal arrhythmia. Troponin measurement and electrocardiogram are sensitive initial tests, whereas cardiac magnetic resonance imaging and endomyocardial biopsy are both gold standard components of the diagnostic criteria. Close monitoring and timely consultation with a cardiologist are important for the diagnosis of ICI-related cardiotoxicities, with decisions of stopping or rechallenging ICIs and strategies to manage heart injuries. Treatment principles are made according to risk stratifications. The first-line medication is glucocorticoids of various doses, and the second-line immunosuppression includes intravenous immunoglobin, antithymocyte globulin and other immunosuppressants, which are recommended in life-threatening cases or in cases of resistance/no response to steroids., (© 2020 John Wiley & Sons Australia, Ltd.)

Coronavirus disease (COVID-19) is a serious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The symptoms of the disease range from asymptomatic to mild respiratory symptoms and even potentially life-threatening cardiovascular and pulmonary complications. Cardiac complications include acute myocardial injury, arrhythmias, cardiogenic shock and even sudden death. Furthermore, drug interactions with COVID-19 therapies may place the patient at risk for arrhythmias, cardiomyopathy and sudden death. In this review, we summarise the cardiac manifestations of COVID-19 infection and propose a simplified algorithm for patient management during the COVID-19 pandemic., (Copyright © 2020 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.)

Background: Cardiovascular diseases (CVD) are the main cause of death and comorbidities worldwide. It is estimated that three quarters of all deaths related to CVD occur in low and middle income countries such as Brazil. Furthermore, it is estimated that emerging countries will present the highest worldwide prevalence of such diseases by 2050. In view of the above, this study aims to characterize Brazilian hospital admission distribution classified by the ICD-10 in adults between 2008 and 2017 in Brazil., Methods: This is a longitudinal descriptive study in which all data regarding hospital admissions registered in the Brazilian Hospital Information System of "Sistema Único de Saúde" (SIH/SUS) due to cardiovascular diseases (ICD-10) were included. All admissions from private or public services linked to the SUS from 2008 and 2017 were evaluated. The following variables were collected: number of hospital admissions, place of hospitalization classified by the ICD-10 and mortality rate at the federal level and according to regions. Absolute values and frequency of hospital admissions were grouped according to sex, age and living region as well as the number of deaths. The extracted data was stored in a Microsoft Excel 2013 program spreadsheet. Statistical analysis was performed by GraphPad Prism version 5.0 software., Results: There was a total of 11,345,821 hospital admissions due to CVD registered between 2008 and 2017. Individuals from 50 to 79 years old were the most affected. Heart failure (21.3%), other ischemic heart diseases (13.3%) and stroke (11.4%) were responsible for almost half of the hospital admissions associated to CVD. The number of registered deaths caused by any CVD was 867,838 and the national mortality rate was 7.82., Conclusion: CVD were responsible for around 10% of all hospital admissions in Brazil between 2008 and 2017. Moreover, it was possible to observe a decrease in hospital admissions as well as mortality rate over time after implementing governmental strategies to prevent cardiovascular diseases.

The relationship between various categories of blood pressure (BP), subtypes of hypertension, and development of cardiovascular disease (CVD) have not been extensively studied. Therefore, our study aimed to explore this relationship in a random population sample of men born in 1943, living in Sweden and followed over a 21-year period.Participants were examined for the first time in 1993 (age 50 years), where data on medical history, concomitant diseases, and general health were collected. The examination was repeated in 2003 and with additional echocardiography also in 2014. Classification of participants according to their BP at the age of 50 years was as follows: optimal-normal BP (systolic blood pressure [SBP] <130 and diastolic BP [DBP] <85 mmHg), high-normal BP (130 ≤ SBP < 140, 85 ≤ DBP < 90 mmHg), isolated systolic-diastolic hypertension (ISH-IDH) (SBP ≥140 and DBP <90 or SBP <140 and DBP ≥90 mmHg), and systolic-diastolic hypertension (SDH) (SBP ≥140 and DBP ≥90 mmHg).During the follow-up, the incidence of heart failure (HF), CVD, and coronary heart disease were all lowest for those with optimal-normal BP. Participants with high-normal BP showed greater wall thickness and left ventricular mass index, larger LV size and larger left atrial size when compared with the optimal-normal BP group. Furthermore, those with high-normal BP, ISH-IDH, and SDH had a higher risk of CVD than those with optimal-normal BP. The adjusted relative risk of CVD was highest for SDH (hazard ratio [HR] 1.95; 95% confidence interval [95% CI] 1.37-2.79), followed by ISH-IDH (HR 1.34; 95% CI 0.93-1.95) and high-normal BP (HR 1.31; 95% CI 0.91-1.89).Over a 21-year follow-up, the participants with high-normal BP or ISH-IDH had a higher relative risk of CVD than those with optimal-normal BP.

Background: Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population., Methods: We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person's Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell's c-statistic and the modified Hosmer-Lemeshow (mH-L) χ 2 statistic to assess the model discrimination and calibration, respectively., Results: The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L χ2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score., Conclusions: A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians., (Copyright © 2019 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.)

Introduction: The World Health Organization has estimated that 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the developed countries are due to cardiovascular diseases. The early prognosis of cardiovascular diseases can aid in making decisions on lifestyle changes in high risk patients., Aim: The aim of this paper is to build and compare classification techniques for cardiovascular diseases., Methods: The dataset contained 4270 patients and 14 attributes and it is available on the UCI data repository. The prediction is a binary outcome (event and no event). Variables of each attribute is a potential risk factor. There are both demographic, behavioral and medical risk factors. The classification goal is to predict whether the patient has 10-year risk of future coronary heart disease (CHD)., Results: Different classifiers were tested. The SMOTE technique was used in order to solve the class imbalance. The cross-validation method was used in order to estimate how accurately our predictive models will perform. We evaluate our classifiers by using the following metrics: precision, recall, F1-score, Accuracy, AUC (Area Under Curve)., Conclusions: Based on the resluts, the best scores have the Random Forest and Decision Tree classifiers., Competing Interests: There are no conflicts of interest to declare., (© 2020 John Minou, John Mantas, Flora Malamateniou, Daphne Kaitelidou.)

Background: The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basic DRG structure by incorporating four severity of illness (SOI) levels, which are used for determining hospital payment. A comprehensive report of all relevant diagnoses, namely the patient's underlying co-morbidities, is a key factor for ensuring that SOI determination will be adequate., Objective: In this study, we aimed to characterise the individual impact of co-morbidities on APR-DRG classification and hospital funding in the context of respiratory and cardiovascular diseases., Methods: Using 6 years of coded clinical data from a nationwide Portuguese inpatient database and support vector machine (SVM) models, we simulated and explored the APR-DRG classification to understand its response to individual removal of Charlson and Elixhauser co-morbidities. We also estimated the amount of hospital payments that could have been lost when co-morbidities are under-reported., Results: In our scenario, most Charlson and Elixhauser co-morbidities did considerably influence SOI determination but had little impact on base APR-DRG assignment. The degree of influence of each co-morbidity on SOI was, however, quite specific to the base APR-DRG. Under-coding of all studied co-morbidities led to losses in hospital payments. Furthermore, our results based on the SVM models were consistent with overall APR-DRG grouping logics., Conclusion and Implications: Comprehensive reporting of pre-existing or newly acquired co-morbidities should be encouraged in hospitals as they have an important influence on SOI assignment and thus on hospital funding. Furthermore, we recommend that future guidelines to be used by medical coders should include specific rules concerning coding of co-morbidities.

Whether circulating fatty acids (FAs) play a causal role in the development of cardiovascular disease (CVD) remains unclear. We conducted a Mendelian randomisation study to explore the associations between plasma phospholipid FA levels and 15 CVDs. Summary-level data from the CARDIoGRAMplusC4D, MEGASTROKE, and Atrial Fibrillation consortia and UK Biobank were used. Sixteen single-nucleotide polymorphisms (SNPs) associated with ten plasma FAs were used as instrumental variables. SNPs in or close to the FADS1 gene were associated with most FAs. We performed a secondary analysis of the association between a functional variant (rs174547) in FADS1 , which encodes ?5-desaturase (a key enzyme in the endogenous FA synthesis), and CVD. Genetic predisposition to higher plasma α-linolenic, linoleic, and oleic acid levels was associated with lower odds of large-artery stroke and venous thromboembolism, whereas higher arachidonic and stearic acid levels were associated with higher odds of these two CVDs. The associations were driven by SNPs in or close to FADS1 . In the secondary analysis, the minor allele of rs174547 in FADS1 was associated with significantly lower odds of any ischemic stroke, large-artery stroke, and venous thromboembolism and showed suggestive evidence of inverse association with coronary artery disease, abdominal aortic aneurysm and aortic valve stenosis. Genetically higher plasma α-linolenic, linoleic, and oleic acid levels are inversely associated with large-artery stroke and venous thromboembolism, whereas arachidonic and stearic acid levels are positively associated with these CVDs. The associations were driven by FADS1 , which was also associated with other CVDs.

Classifying subjects into clinically and biologically homogeneous subgroups will facilitate the understanding of disease pathophysiology and development of targeted prevention and intervention strategies. Traditionally, disease subtyping is based on clinical characteristics alone, but subtypes identified by such an approach may not conform exactly to the underlying biological mechanisms. Very few studies have integrated genomic profiles (e.g., those from GWASs) with clinical symptoms for disease subtyping. Here we proposed an analytic framework capable of finding complex diseases subgroups by leveraging both GWAS-predicted gene expression levels and clinical data by a multi-view bicluster analysis. This approach connects SNPs to genes via their effects on expression, so the analysis is more biologically relevant and interpretable than a pure SNP-based analysis. Transcriptome of different tissues can also be readily modeled. We also proposed various evaluation metrics for assessing clustering performance. Our framework was able to subtype schizophrenia subjects into diverse subgroups with different prognosis and treatment response. We also applied the framework to the Northern Finland Birth Cohort (NFBC) 1966 dataset and identified high and low cardiometabolic risk subgroups in a gender-stratified analysis. The prediction strength by cross-validation was generally greater than 80%, suggesting good stability of the clustering model. Our results suggest a more data-driven and biologically informed approach to defining metabolic syndrome and subtyping psychiatric disorders. Moreover, we found that the genes "blindly" selected by the algorithm are significantly enriched for known susceptibility genes discovered in GWASs of schizophrenia or cardiovascular diseases. The proposed framework opens up an approach to subject stratification., (Copyright © 2019 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background and Objective: The estimation of cardiovascular risk (CVR) with scores at 30 years old has a special interest in reclassifying in a suitable way <60 year subjects with intermediate CVR. This study analyzes what percentage of patients with intermediate CVR included in the MARK study is reclassified by applying the 30-year Framingham score (FS30). It also analyzes the degree of agreement between the two equations to classify high risk subjects., Patients and Methods: Cross-sectional study of 966 subjects included in the MARK study. The CVR was calculated with the two versions of the FS30 (based on lipids and body mass index) for "hard" cardiovascular events in subjects with intermediate CVR., Results: The 59% and 61% of the subjects with intermediate CVR would be classified as if they had high CVR to undergo a hard event if we used the FS30 in both versions. 70% of men and 35% of women would be classified as high CVR (p<0.01). The agreement percentage, measured with the Kappa index, between the equations FS30L and FS30BMI to classify the high-risk subjects was 67.9% (in men 67.4% and in women 68.7%)., Conclusions: In subjects with intermediate CVR the FS30 reclassifies more than the half as high RCV, 2 out of 3 men and 1 out of 3 women., (Copyright © 2019 Elsevier España, S.L.U. All rights reserved.)

Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to fundamentally change the practice of medicine. This field, known as "artificial intelligence" (AI), is making significant progress in areas such as automated clinical decision making, medical imaging analysis, and interventional procedures, and has the potential to dramatically influence the practice of interventional cardiology. The unique nature of interventional cardiology makes it an ideal target for the development of AI-based technologies designed to improve real-time clinical decision making, streamline workflow in the catheterization laboratory, and standardize catheter-based procedures through advanced robotics. This review provides an introduction to AI by highlighting its scope, potential applications, and limitations in interventional cardiology., (Copyright © 2019. Published by Elsevier Inc.)

Competing Interests: Competing interests: None declared.

Background: Young, non-obese adults are considered at low risk for cardiometabolic diseases, although markers of an unhealthy metabolic state are not uncommon findings in this population. Adipose tissue dysfunction, evaluated by the adipokine profile, significantly influences lipid and glucose metabolism and low-grade systemic inflammation., Aims: To determine the relation between adipose tissue dysfunction and the already confirmed cardiometabolic risk indicators, including the atherogenic index of plasma, lipid accumulation product, homeostatic model assessment of insulin resistance, and the low-grade inflammation markers, namely, interleukin 6 and high-sensitivity C-reactive protein., Study Design: Cross-sectional study., Methods: We recruited 93 non-obese, healthy young adults. Anthropometric, lipid profile, inflammatory markers, and adipokines were measured. An abnormal adipokine profile (high leptin-to-adiponectin ratio) was considered as a marker of a dysfunctional adipose tissue. The correlation between the leptin-to-adiponectin ratio and the anthropometric measurements, atherogenic index of plasma, lipid accumulation product, homeostatic model assessment of insulin resistance, interleukin 6, and high-sensitivity C-reactive protein was determined., Results: We found a direct correlation between the abnormal adipokine profile and the cardiometabolic risk indicators mentioned above, except for the low-grade inflammatory markers. In the regression model derived from our data, the leptin-to-adiponectin ratio was best correlated with the unfavorable plasma lipid profile, as estimated by the atherogenic index of plasma (r=0.097, confidence interval=0.015-0.180, p=0.021). A significantly higher leptin-to-adiponectin ratio was found in the insulin-resistant group (p=0.012) and in the highest lipid accumulation product quartile (p=0.032)., Conclusion: In a non-obese young population, the high rate of leptin-adiponectin may be a good predictor of cardiovascular and metabolic risk assessment.

Objective: Composite scores of cardiovascular (CV) risk factors underestimate the CV risk in patients with systemic lupus erythematosus (SLE). Carotid artery ultrasound (US) was found useful in identifying high CV-risk patients with inflammatory arthritis. We assessed the effect of carotid US assessments on the CV risk stratification of patients with SLE., Methods: This cross-sectional study included 276 patients with SLE. These indices were measured: lipid profile, Systematic COronary Risk Evaluation (SCORE) risk calculation, and disease activity (SLE Disease Activity Index), severity (Katz), and damage [Systemic Lupus International Collaborating Clinics (SLICC)/American College of Rheumatology Damage Index]. Carotid plaques were assessed by US. A multivariable regression analysis, adjusted for classic CV-related factors, was performed to evaluate how risk reclassification was influenced by disease characteristics in patients with SLE., Results: Thirty-six percent of patients had carotid plaques. However, only 6% of them fulfilled the definitions for high or very high risk according to the SCORE risk charts. Following carotid US assessment, 32% of the patients were reclassified as very high risk. Disease duration (OR 1.04, 95% CI 1.00-1.07, p = 0.025) and a SLICC > 0 (OR 2.48 95% CI 1.15-5.34, p = 0.020) were independently associated with a higher risk of reclassification. A predictive model for reclassification included age (cutoff 52 yrs, sensitivity 60%, specificity 86%), disease duration (cutoff 24 yrs, sensitivity 40%, specificity 82%), presence of hypertension, SLICC > 0, waist circumference (cutoff 102 cm, sensitivity 48%, specificity 84%), and C3 (cutoff 127 mg/dl, sensitivity 52%, specificity 92%) and triglyceride (cutoff 140 mg/dl, sensitivity 68%, specificity 79%) serum levels., Conclusion: Reclassification into a very high-risk category is frequent after carotid US assessments in patients with SLE. This is independently influenced by disease damage.