Assessing the Risk of Heart Attack: A Bayesian Kernel Machine Regression Analysis of Heavy Metal Mixtures.

Background: The assessment of heavy metals' effects on human health is frequently limited to investigating one metal or a group of related metals. The effect of heavy metals mixture on heart attack is unknown. Methods: This study applied the Bayesian kernel machine regression model (BKMR) to the 2011-2016 National Health and Nutrition Examination Survey (NHANES) data to investigate the association between heavy metal mixture exposure with heart attack. 2972 participants over the age of 20 were included in the study. Results: Results indicate that heart attack patients have higher levels of cadmium and lead in the blood and cadmium, cobalt, and tin in the urine, while having lower levels of mercury, manganese, and selenium in the blood and manganese, barium, tungsten, and strontium in the urine. The estimated risk of heart attack showed a negative association of 0.0030 units when all the metals were at their 25th percentile compared to their 50th percentile and a positive association of 0.0285 units when all the metals were at their 75th percentile compared to their 50th percentile. The results suggest that heavy metal exposure, especially cadmium and lead, may increase the risk of heart attacks. Conclusions: This study suggests a possible association between heavy metal mixture exposure and heart attack and, additionally, demonstrates how the BKMR model can be used to investigate new combinations of exposures in future studies.

The Incidence and Outcomes of Out-of-Hospital Cardiac Arrest During the COVID-19 Pandemic in South Korea: Multicenter Registry Study.

BACKGROUND: The COVID-19 pandemic has profoundly affected out-of-hospital cardiac arrest (OHCA) and disrupted the chain of survival. Even after the end of the pandemic, the risk of new variants and surges persists. Analyzing the characteristics of OHCA during the pandemic is important to prepare for the next pandemic and to avoid repeated negative outcomes. However, previous studies have yielded somewhat varied results, depending on the health care system or the specific characteristics of social structures. OBJECTIVE: We aimed to investigate and compare the incidence, outcomes, and characteristics of OHCA during the prepandemic and pandemic periods using data from a nationwide multicenter OHCA registry. METHODS: We conducted a multicenter, retrospective, observational study using data from the Korean Cardiac Arrest Resuscitation Consortium (KoCARC) registry. This study included adult patients with OHCA in South Korea across 3 distinct 1-year periods: the prepandemic period (from January to December 2019), early phase pandemic period (from July 2020 to June 2021), and late phase pandemic period (from July 2021 to June 2022). We extracted and contrasted the characteristics of patients with OHCA, prehospital time factors, and outcomes for the patients across these 3 periods. The primary outcomes were survival to hospital admission and survival to hospital discharge. The secondary outcome was good neurological outcome. RESULTS: From the 3 designated periods, a total of 9031 adult patients with OHCA were eligible for analysis (prepandemic: n=2728; early pandemic: n=2954; and late pandemic: n=3349). Witnessed arrest (P<.001) and arrest at home or residence (P=.001) were significantly more frequent during the pandemic period than during the prepandemic period, and automated external defibrillator use by bystanders was lower in the early phase of the pandemic than during other periods. As the pandemic advanced, the rates of the first monitored shockable rhythm (P=.10) and prehospital endotracheal intubation (P<.001) decreased significantly. Time from cardiac arrest cognition to emergency department arrival increased sequentially (prepandemic: 33 min; early pandemic: 35 min; and late pandemic: 36 min; P<.001). Both survival and neurological outcomes worsened as the pandemic progressed, with survival to discharge showing the largest statistical difference (prepandemic: 385/2728, 14.1%; early pandemic: 355/2954, 12%; and late pandemic: 392/3349, 11.7%; P=.01). Additionally, none of the outcomes differed significantly between the early and late phase pandemic periods (all P>.05). CONCLUSIONS: During the pandemic, especially amid community COVID-19 surges, the incidence of OHCA increased while survival rates and good neurological outcome at discharge decreased. Prehospital OHCA factors, which are directly related to OHCA prognosis, were adversely affected by the pandemic. Ongoing discussions are needed to maintain the chain of survival in the event of a new pandemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT03222999; https://classic.clinicaltrials.gov/ct2/show/NCT03222999.

Moving towards health promoting schools: effectiveness of an educational intervention to improve knowledge, attitude and beliefs regarding heart attack, and CPR knowledge in high school students in Lebanon.

Background: Health promoting schools (HPS) prioritize the health of students and community. One important target of HPS is noncommunicable diseases (NCDs), including prevention of heart attacks, due to their burden on healthcare. Objective: This study assesses the effectiveness of an educational intervention to promote knowledge of signs and symptoms, beliefs and attitudes towards heart attack, and promote knowledge of Cardiopulmonary resuscitation (CPR). Methods: The intervention consisted of a 6-minute educational video between a pre-and post-survey. Among other questions, the survey included the Calgary Charter on Health literacy scale, the acute coronary syndrome response index questionnaire, and items assessing knowledge of CPR. Results: A total of 401 high school students participated (58.9% females). Few students had adequate baseline knowledge of heart attack symptoms (22%) and CPR (7%). The sample showed moderate level of health literacy (12 ± 2.7). Chest pain was the most identified symptom (95%) while abdominal pain was the least identified (14.25%). The intervention significantly increased knowledge, beliefs and attitudes towards heart attack, and knowledge of CPR (p < 0.001). Following the intervention, 83.2% of students demonstrated sufficient knowledge of heart attack symptoms, and 45% exhibited adequate knowledge of CPR. Variables predictive of better attitude, in other words higher confidence in recognizing and reacting to symptoms of heart attack, included having higher health literacy and prior knowledge of risk factors (p < 0.05). Needing help reading medical instructions sometimes predicted worse belief in their capacity to act if they experienced or witnessed a heart attack [score (p < 0.05)]. It was also predictive of worse attitude towards heart attack (OR = 0.18). Conclusion: High school students in Lebanon lack appropriate knowledge, attitudes, and beliefs toward heart attack, and lack CPR qualifications. Scale up of this educational initiative, along with training of teachers and school personnel, can be used as part of a holistic HPS program aimed at raising awareness of heart attack and first responder preparedness.

Xylitol is prothrombotic and associated with cardiovascular risk.

BACKGROUND AND AIMS: The pathways and metabolites that contribute to residual cardiovascular disease risks are unclear. Low-calorie sweeteners are widely used sugar substitutes in processed foods with presumed health benefits. Many low-calorie sweeteners are sugar alcohols that also are produced endogenously, albeit at levels over 1000-fold lower than observed following consumption as a sugar substitute. METHODS: Untargeted metabolomics studies were performed on overnight fasting plasma samples in a discovery cohort (n = 1157) of sequential stable subjects undergoing elective diagnostic cardiac evaluations; subsequent stable isotope dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) analyses were performed on an independent, non-overlapping validation cohort (n = 2149). Complementary isolated human platelet, platelet-rich plasma, whole blood, and animal model studies examined the effect of xylitol on platelet responsiveness and thrombus formation in vivo. Finally, an intervention study was performed to assess the effects of xylitol consumption on platelet function in healthy volunteers (n = 10). RESULTS: In initial untargeted metabolomics studies (discovery cohort), circulating levels of a polyol tentatively assigned as xylitol were associated with incident (3-year) major adverse cardiovascular event (MACE) risk. Subsequent stable isotope dilution LC-MS/MS analyses (validation cohort) specific for xylitol (and not its structural isomers) confirmed its association with incident MACE risk [third vs. first tertile adjusted hazard ratio (95% confidence interval), 1.57 (1.12-2.21), P < .01]. Complementary mechanistic studies showed xylitol-enhanced multiple indices of platelet reactivity and in vivo thrombosis formation at levels observed in fasting plasma. In interventional studies, consumption of a xylitol-sweetened drink markedly raised plasma levels and enhanced multiple functional measures of platelet responsiveness in all subjects. CONCLUSIONS: Xylitol is associated with incident MACE risk. Moreover, xylitol both enhanced platelet reactivity and thrombosis potential in vivo. Further studies examining the cardiovascular safety of xylitol are warranted.

Long-term returns to local health-care spending.

This paper investigates the effects of health-care spending on mortality rates of patients who experienced a heart attack. We relate in-hospital deaths to in-hospital spending and post-discharge deaths to post-discharge health-care spending. In our analysis, we use detailed administrative data on individual personal characteristics including comorbidities, information about the type of medical treatment and information about health-care expenses at the regional level. To account for potential selectivity in the region of health-care treatment we compare local patients with visitors and stayers with recent movers from a different region. We find that in regions with higher health-care spending mortality after heart attacks is substantially lower. From this we conclude that there are long-term returns to local health-care spending.

A Systematic Review of Herbal Interventions for the Management of Cardiovascular Diseases.

BACKGROUND: Cardiovascular diseases represent a significant global health burden, necessitating diverse approaches for effective management. Herbal interventions have gained attention as potential adjuncts or alternatives to conventional therapies due to their perceived safety and therapeutic potential. This structured abstract provides a comprehensive review of herbal interventions for the management of CVDs, summarising key findings, mechanisms of action, and clinical implications. OBJECTIVE: This systematic review aims to evaluate the impact of various herbal interventions employed for managing cardiovascular diseases. METHOD: We conducted an extensive literature search across electronic databases, including PubMed, Scopus, and Web of Science, from inception to 2022. Studies were included if they investigated the use of herbal remedies for preventing or treating CVDs. Data extraction and synthesis focused on botanical sources, active compounds, mechanisms of action, and clinical outcomes. RESULT: Numerous herbal interventions have demonstrated promising cardiovascular benefits. A number of medicinal herbs well identified to treat CVD are Moringaoleifera, Ginseng, Ginkgo biloba, Celosia argentea, Gongronematrifolium, Gynostemmapentaphyllum, Bombaxceiba, Gentianalutea, Allium sativum, Crataegusspp, Curcuma longa, Camellia sinensis, and Zingiberofficinale. Mechanistic insights reveal that herbal interventions often target multiple pathways involved in CVD pathogenesis. These mechanisms encompass anti-inflammatory, antioxidant, anti-thrombotic, anti-hypertensive, and lipid-lowering effects. Additionally, some herbs enhance endothelial function, promote nitric oxide production, and exert vasodilatory effects, contributing to improved cardiovascular health. Clinical studies have provided evidence of the efficacy of certain herbal interventions in reducing CVD risk factors and improving patient outcomes. However, more rigorous, large-scale clinical trials are needed to establish their long-term safety and effectiveness. It is crucial to consider potential herb-drug interactions and standardise dosages for reliable therapeutic outcomes. CONCLUSION: This comprehensive review highlights the potential of herbal interventions as valuable adjuncts or alternatives for managing cardiovascular diseases. Herbal remedies offer diverse mechanisms of action, targeting key CVD risk factors and pathways. While promising, their clinical utility warrants further investigation through well-designed trials to establish their safety and efficacy, paving the way for integrated approaches to cardiovascular disease management. Healthcare providers and patients should engage in informed discussions about the use of herbal interventions alongside conventional therapies in the context of CVD prevention and treatment.

A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.

Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstruction of blood supply to a section of the heart muscle, leading to the deterioration or death of the affected tissue due to a lack of oxygen. MI, poses a significant public health concern worldwide, particularly affecting the citizens of the Chittagong Metropolitan Area. The challenges lie in both prevention and treatment, as the emergence of MI has inflicted considerable suffering among residents. Early warning systems are crucial for managing epidemics promptly, especially given the escalating disease burden in older populations and the complexities of assessing present and future demands. The primary objective of this study is to forecast MI incidence early using a deep learning model, predicting the prevalence of heart attacks in patients. Our approach involves a novel dataset collected from daily heart attack incidence Time Series Patient Data spanning January 1, 2020, to December 31, 2021, in the Chittagong Metropolitan Area. Initially, we applied various advanced models, including Autoregressive Integrated Moving Average (ARIMA), Error-Trend-Seasonal (ETS), Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal (TBATS), and Long Short Time Memory (LSTM). To enhance prediction accuracy, we propose a novel Myocardial Sequence Classification (MSC)-LSTM method tailored to forecast heart attack occurrences in patients using the newly collected data from the Chittagong Metropolitan Area. Comprehensive results comparisons reveal that the novel MSC-LSTM model outperforms other applied models in terms of performance, achieving a minimum Mean Percentage Error (MPE) score of 1.6477. This research aids in predicting the likely future course of heart attack occurrences, facilitating the development of thorough plans for future preventive measures. The forecasting of MI occurrences contributes to effective resource allocation, capacity planning, policy creation, budgeting, public awareness, research identification, quality improvement, and disaster preparedness.

Exploring mitochondrial DNA copy number in circulating cell-free DNA and extracellular vesicles across cardiovascular health status: A prospective case-control pilot study.

Cardiovascular disease (CVD) is a leading global cause of mortality, difficult to predict in advance. Evidence indicates that the copy number of mitochondrial DNA (mtDNAcn) in blood is altered in individuals with CVD. MtDNA released into circulation may act as a mediator of inflammation, a recognized factor in the development of CVD, in the long distance. This pilot study aims to test if levels of mtDNAcn in buffy coat DNA (BC-mtDNA), in circulating cellfree DNA (cf-mtDNA), or in DNA extracted from plasma extracellular vesicles (EV-mtDNA) are altered in CVD patients and if they can predict heart attack in advance. A group of 144 people with different CVD statuses (50 that had CVD, 94 healthy) was selected from the LifeLines Biobank according to the incidence of new cardiovascular event monitored in 6 years (50 among controls had heart attack after the basal assessment). MtDNAcn was quantified in total cf-DNA and EV-DNA from plasma as well as in buffy coat. EVs have been characterized by their size, polydispersity index, count rate, and zeta potential, by Dynamic Light Scattering. BC-mtDNAcn and cf-mtDNAcn were not different between CVD patients and healthy subjects. EVs carried higher mtDNAcn in subject with a previous history of CVD than controls, also adjusting the analysis for the EVs derived count rate. Despite mtDNAcn was not able to predict CVD in advance, the detection of increased EV-mtDNAcn in CVD patients in this pilot study suggests the need for further investigations to determine its pathophysiological role in inflammation.

Survival Prediction of Patients after Heart Attack and Breast Cancer Surgery with a Hybrid Model Built with Particle Swarm Optimization, Stacked AutoEncoders, and the Softmax Classifier.

The prediction of patient survival is crucial for guiding the treatment process in healthcare. Healthcare professionals rely on analyzing patients' clinical characteristics and findings to determine treatment plans, making accurate predictions essential for efficient resource utilization and optimal patient support during recovery. In this study, a hybrid architecture combining Stacked AutoEncoders, Particle Swarm Optimization, and the Softmax Classifier was developed for predicting patient survival. The architecture was evaluated using the Haberman's Survival dataset and the Echocardiogram dataset from UCI. The results were compared with several Machine Learning methods, including Decision Trees, K-Nearest Neighbors, Support Vector Machines, Neural Networks, Gradient Boosting, and Gradient Bagging applied to the same datasets. The findings indicate that the proposed architecture outperforms other Machine Learning methods in predicting patient survival for both datasets and surpasses the results reported in the literature for the Haberman's Survival dataset. In the light of the findings obtained, the models obtained with the proposed architecture can be used as a decision support system in determining patient care and applied methods.

Machine learning-driven predictions and interventions for cardiovascular occlusions.

BACKGROUND: Cardiovascular diseases remain a leading cause of global morbidity and mortality, with heart attacks and strokes representing significant health challenges. The accurate, early diagnosis and management of these conditions are paramount in improving patient outcomes. The specific disease, cardiovascular occlusions, has been chosen for the study due to the significant impact it has on public health. Cardiovascular diseases are a leading cause of mortality globally, and occlusions, which are blockages in the blood vessels, are a critical factor contributing to these conditions. OBJECTIVE: By focusing on cardiovascular occlusions, the study aims to leverage machine learning to improve the prediction and management of these events, potentially helping to reduce the incidence of heart attacks, strokes, and other related health issues. The use of machine learning in this context offers the promise of developing more accurate and timely interventions, thus improving patient outcomes. METHODS: We analyze diverse datasets to assess the efficacy of various machine learning algorithms in predicting heart attacks and strokes, comparing their performance to pinpoint the most accurate and reliable models. Additionally, we classify individuals by their predicted risk levels and examine key features that correlate with the incidence of cardiovascular events. The PyCaret machine learning library's Classification Module was key in developing predictive models which were evaluated with stratified cross-validation for reliable performance estimates. RESULTS: Our findings suggest that machine learning can significantly improve the prediction accuracy for heart attacks and strokes, facilitating earlier and more precise interventions. We also discuss the integration of machine learning models into clinical practice, addressing potential challenges and the need for healthcare professionals to interpret and apply these predictions effectively. CONCLUSIONS: The use of machine learning for risk stratification and the identification of modifiable factors may empower preemptive approaches to cardiovascular care, ultimately aiming to reduce the occurrence of life-threatening events and improve long-term patient health trajectories.

Knowledge and self-perceived competence about cardiopulmonary resuscitation among youths: a cross-sectional study in a sample of Italian undergraduates.

Introduction: Cardiopulmonary resuscitation is fundamental to improve the outcomes of a life-threatening event. The correct knowledge of first aid actions to provide may guarantee the victim's survival. This study was aimed at evaluating the competence about cardiopulmonary resuscitation and its predictors in a sample of Italian undergraduate students. Methods: Information on socio-demographic characteristics, first aid training, knowledge of stroke and heart attack symptoms and perceived ability to provide first aid, were collected through a web-based questionnaire. Results: On a total of 744 respondents (mean age 23.9±5.4 years, 62.5% female), 71.4% identified correctly first aid actions, 59.9% and 60.8% showed a good knowledge of stroke and heart attack symptoms, respectively. However, only 39.0% of them declared their ability to intervene in case of emergency. Attending a healthcare degree course and having had first aid training were associated with knowledge of symptoms and perceived ability to provide first aid. Female gender was negatively related with perceived ability to intervene. Conclusions: In spite of the satisfactory level of knowledge, these findings highlight the need to enhance the competence about cardiopulmonary resuscitation in the lay population, especially among females.

ChatGPT's Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines: Exploratory Study.

BACKGROUND: ChatGPT is the most advanced large language model to date, with prior iterations having passed medical licensing examinations, providing clinical decision support, and improved diagnostics. Although limited, past studies of ChatGPT's performance found that artificial intelligence could pass the American Heart Association's advanced cardiovascular life support (ACLS) examinations with modifications. ChatGPT's accuracy has not been studied in more complex clinical scenarios. As heart disease and cardiac arrest remain leading causes of morbidity and mortality in the United States, finding technologies that help increase adherence to ACLS algorithms, which improves survival outcomes, is critical. OBJECTIVE: This study aims to examine the accuracy of ChatGPT in following ACLS guidelines for bradycardia and cardiac arrest. METHODS: We evaluated the accuracy of ChatGPT's responses to 2 simulations based on the 2020 American Heart Association ACLS guidelines with 3 primary outcomes of interest: the mean individual step accuracy, the accuracy score per simulation attempt, and the accuracy score for each algorithm. For each simulation step, ChatGPT was scored for correctness (1 point) or incorrectness (0 points). Each simulation was conducted 20 times. RESULTS: ChatGPT's median accuracy for each step was 85% (IQR 40%-100%) for cardiac arrest and 30% (IQR 13%-81%) for bradycardia. ChatGPT's median accuracy over 20 simulation attempts for cardiac arrest was 69% (IQR 67%-74%) and for bradycardia was 42% (IQR 33%-50%). We found that ChatGPT's outputs varied despite consistent input, the same actions were persistently missed, repetitive overemphasis hindered guidance, and erroneous medication information was presented. CONCLUSIONS: This study highlights the need for consistent and reliable guidance to prevent potential medical errors and optimize the application of ChatGPT to enhance its reliability and effectiveness in clinical practice.

Acute prevention of a heart attack : Early identification of prodromal symptoms as the Rosetta Stone in decoding the heart attack problem.

Chest discomfort before severe chest pain represents a marker of clinical ischemia and indicates live myocardium in jeopardy and often precedes cardiac arrest or acute myocardial infarction (MI). The intermittent or "stuttering" symptoms that precede MI are referred to as "prodromal symptoms." These symptoms have been shown to correlate with cyclic ST changes and repeated episodes of spontaneous reperfusion and occlusion, occurring during a period of hours or days before the acute ischemia proceeds to death or heart damage. These symptoms of premonitory angina have been associated with improved outcomes due to ischemic pre-conditioning or opening of collateral vascular channels around the area of ischemia. Acute prevention of an MI through recognition of prodromal symptoms represents an opportunity to significantly reduce heart attack deaths. The Early Heart Attack Care (EHAC) program puts emphasis on prodromal symptom recognition and allows for a shift in time backward to prevent the ischemic process from proceeding to MI. This strategy has been shown to detect the 15% of patients with ischemia in the low-probability group and to reduce inappropriate admissions to hospital as well as to reduce the number of patients with missed MI being sent home from the emergency department.

Age and healthy lifestyle behavior's disparities and similarities on knowledge of myocardial infarction symptoms and risk factors among public and outpatients in a resource-limited setting, cross-sectional study in greater Gaborone, Botswana.

OBJECTIVES: In this cross-sectional study from Botswana, we investigated knowledge of myocardial infarction (MI) symptoms and risk factors among the general public and outpatients with MI risk factors based on age and lifestyle behaviors, in addition to assessing associations with sociodemographic and MI risk factors. METHOD: Open-ended questionnaires about 8 MI symptoms and 10 risk factors, were administered by research assistants to a representative selection of outpatients (n = 525) and the public (n = 2248). Weight and height were measured in all participants and BMI was calculated. Knowledge scores were compared between the two groups. We examined whether sociodemographic and MI risk factors had impact on the scores. Analyses were further adjusted for lifestyle behavior (smoking status, dietary status and physical activities). RESULTS: The valid response rate was 97.9% comprising 97.8% for the public (n = 2199) and 98.1% for outpatients (n = 515). Public respondents (35.2 ± 12.3 years) were younger than outpatients (38.5 ± 12.6 years). The public comprised 56.9% females while outpatients 54.6%. In general, outpatients had higher knowledge of MI symptoms than the public, with mean scores ± SD of 3.49 ± 2.84 vs 2.80 ± 2.54. Outpatients also had higher knowledge score of MI risk factors than the public, with mean scores, 5.33 ± 3.22 vs 3.82 ± 3.07. For MI symptoms, outpatients were more aware than the public for chest pains among all ages, for arm pain/ numbness, neck/ jaw pain radiating to/ from chest, and feeling sick or looking pallor on the skin among those aged 35-49 years. Among both the public and outpatients, lower knowledge of both MI symptoms and risk factors was associated with primary education, not residing/working together, history of hypertension, no history of heart disease/stroke, and obesity. There were similarities and disparities on MI knowledge among respondents with various numbers of healthy lifestyle behaviours. CONCLUSION: Results call for urgent educational campaigns on awareness and knowledge of MI and using strategies based on age and lifestyle behavior.

Differences in Attitudes and Barriers Towards Advance Care Planning Amongst Ischemic Heart Disease Patients: A Cross-Sectional Study.

OBJECTIVES: Perceptions towards advanced care planning (ACP) amongst individuals with Ischemic Heart Disease before or after a life-threatening Acute Myocardial Infarction event is underexamined and could impact the appropriate timing for ACP advocacy. This cross-sectional study assessed awareness and intentions regarding ACP in individuals with Ischemic Heart Disease, both before and after an Acute Myocardial Infarction, and explored the motivating effect of a near-fatal Acute Myocardial Infarction event on its engagement. METHODS: This study was conducted from 24 August 2021 through 13 March 2023, whereby patients were administered a one-time questionnaire with no follow-up required. Patients with either chronic Ischemic Heart Disease (group A) or a recent Acute Myocardial Infarction event (group B) were recruited from the outpatient National University Heart Centre, Singapore. RESULTS: 101 patients (n = 51 for Group A, n = 50 for Group B) were recruited. Mean age (SD) was 59 (10.5) years and 84 were male (83.2%). Between both groups, patients in group B reported significantly higher scores on 'Lack of information' and 'Self-efficacy' domains, and had no ACP awareness nor plans of doing an ACP compared to group A. ACP awareness was the sole significant predictor of intentions of doing an ACP in the final regression model (P < .05). CONCLUSIONS: Interestingly, this study suggests that surviving a potentially life-threatening heart condition did not result in higher intention of doing an ACP. Thus, advocacy of ACP in the community should simply start by raising awareness levels widely and may not need to be focused on individuals' state of health.

Cardiovascular Health, Lifestyle Factors, and Social Determinants in Asian Subpopulations in the United States.

Asian Americans are often aggregated in national public health surveillance efforts, which may conceal important differences in the health status of subgroups that are included in this highly diverse population. Little is known about how cardiovascular health varies across Asian subpopulations and the extent to which lifestyle and social risk factors contribute to any observed differences. This national study used data from the National Health Interview Survey to evaluate the burden of cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus) and cardiovascular diseases (heart attack, coronary heart disease, angina, stroke) across Asian groups (Chinese, Asian Indian, Filipino, Other Asian), and determine whether differences are related to lifestyle factors and/or social determinants of health. The weighted study population included 13,592,178 Asian adults. Filipino adults were more likely to have hypertension than Chinese adults (29.4% vs 15.4%; adjusted odds ratio [OR] 2.40, 95% confidence interval [1.91 to 3.02]), as were Asian Indians (15.7%; OR 1.59 [1.25 to 2.02]). These patterns were similar for hyperlipidemia and diabetes mellitus. For cardiovascular diseases, Filipino adults were significantly more likely to have coronary heart disease (4.2% vs 1.9%; OR 2.19 [1.32 to 3.56]), heart attack (2.6% vs 0.9%; OR 2.79 [1.44 to 5.41]), angina (1.8% vs 0.9%; OR 2.15 [1.06 to 4.32]), and stroke (2.1% vs 0.8%; OR 2.54 [1.42 to 4.55]) compared with Chinese adults, whereas there were no differences compared with Asian Indian adults. Adjustments for lifestyle factors and social determinants completely attenuated differences in coronary heart disease, heart attack, and angina among subpopulations. In conclusion, these findings demonstrate that cardiovascular risk factors and diseases vary significantly across Asian subpopulations, with Filipino adults experiencing the highest burden and Chinese adults the lowest, and that differences in cardiovascular disease are largely attenuated after adjustment for lifestyle and social determinants.

The Power of the Underutilized and Neglected Medicinal Plants and Herbs of the Middle East.

The Middle east and North Africa harbour many native species with pharmaceutical and nutraceutical potential. Since the beginning of history, food and herbal medicinal plants have been an essential part of human lives and the traditional Middle Eastern healthcare system. The notable medicinal plants that have been mentioned in the Bible, which are common in West Asia and some regions of North Africa, are Aloe vera, anise, balm, cassia, cinnamon, cumin, flax, and fig. Chemical components of Aloe vera are aloin, sinapinic acid, catechin, chromone, myricetin, quercitrin and syringic acid. Anethole, safrole, and estragole are the main chemical components of anise. The chemical components of cassia are coumarin, emodin, cinnamyl alcohol, and cinnamaldehyde. The major chemical ingredients of cumin are terpinene, cuminaldehyde, sabinene, thujene, and thymoquinone. The goal of this article is to review the considerable health benefits and pharmaceutical benefits of medicinal herbs and plants that have been neglected and underutilized in the Middle East and North Africa, as well as to promote their utilization. On the basis of the results, the experimented neglected medicinal plant can offer various advantages when used together with conventional medicinal treatments for various health conditions, such as palliative care in managing the side effects of conventional treatments, access to a wider range of treatments, increased patient satisfaction, and improved emotional and mental well-being. Moreover-, consuming medicinal plants may help to manage and prevent diabetes, cancer, and heart disease with notable anti-tumor, and anti-inflammatory properties.

ARGEN SHOCK: Mortality related to the use of Swan Ganz and to the hemodynamic pattern found in patients with AMICS.

The Swan Ganz Catheter (SGC) allows us to diagnose different types of cardiogenic shock (CS). OBJECTIVES: 1) Determine the frequency of use of SGC, 2) Analyze the clinical characteristics and mortality according to its use and 3) Analyze the prevalence, clinical characteristics and mortality according to the type of Shock. METHODS: The 114 patients (p) from the ARGEN SHOCK registry were analyzed. A "classic" pattern was defined as PCP > 15 mm Hg, CI < 2.2 L/min/ m2, SVR > 1,200 dynes × sec × cm-5. A "vasoplegic/mixed" pattern was defined when p did not meet the classic definition. CS due to right ventricle (RV) was excluded. RESULTS: SGC was used in 35 % (n:37). There were no differences in clinical characteristics according to SGC use, but those with SGC were more likely to receive dobutamine, levosimendan, and intra aortic balloon pump (IABP). Mortality was similar (59.4 % vs 61.3 %). The pattern was "classic" in 70.2 %. There were no differences in clinical characteristics according to the type of pattern or the drugs used. Mortality was 54 % in patients with the classic pattern and 73 % with the mixed/vasoplegic pattern, but the difference did not reach statistical significance (p:0.23). CONCLUSIONS: SGC is used in one third of patients with CS. Its use does not imply differences in the drugs used or in mortality. Most patients have a classic hemodynamic pattern. There are no differences in mortality or in the type of vasoactive agents used according to the CS pattern found.

Vasomotor symptoms and cardiovascular health: findings from the SWAN and the MsHeart/MsBrain studies.

Vasomotor symptoms (VMS) are often considered the classic menopausal symptom and are experienced by most women during the menopause transition. VMS are well established to be associated with decrements in quality of life during the menopause. More recent research also links VMS to poorer cardiovascular health. This review summarizes key insights about links between VMS and cardiovascular disease (CVD) risk that come from the Study of Women's Health Across the Nation (SWAN), a longitudinal epidemiologic cohort study of the menopause transition, as well as from the MsHeart/MsBrain studies, clinical studies that leverage vascular imaging and brain imaging as well as wearable technologies that provide objective indicators of VMS. Using a range of methodologies and extensive consideration of confounders, these studies have shown that frequent and/or persistent VMS are associated with adverse CVD risk factor profiles, poorer underlying peripheral vascular and cerebrovascular health, and elevated risk for clinical CVD events. Collectively, the SWAN and MsHeart/MsBrain studies form complementary epidemiologic and clinical studies that point to the importance of VMS to women's cardiovascular health during the menopause transition and beyond.

Prevalence of myocardial bridges in the Mexican population: A morphometric and histological analysis.

BACKGROUND: Myocardial bridge (MB) is described as an abnormal band of myocardium covering a variable portion of any coronary artery. METHODS: The current study explores the presence of MB throughout the coronary arterial system and provides a morphometric description through instrumented dissection of a sample of 100 human hearts. The study shows a higher prevalence of MB in the Mexican population than in previous reports. RESULTS: In the total sample (n=100), MB was identified in 96% of it. A total of 421 MBs were observed, with a mean of 4.38mm (±0.28) per dissected heart. The most frequently affected vessel is the anterior interventricular artery where a total of 52 MBs were found, of the total sample studied. DISCUSSION: The high prevalence of MB among Mexican patients could be the result of a genetic association for this population or the neoformation of MB after birth due to lifestyle-associated factors. Further studies are required to better understand the high prevalence of MB among Mexican subjects.