On two-dimensional surface attractors and repellers on 3-manifolds

We show that if $f: M^3\to M^3$ is an $A$-diffeomorphism with a surface two-dimensional attractor or repeller $\mathcal B$ and $M^2_ \mathcal B$ is a supporting surface for $\mathcal B$, then $\mathcal B = M^2_{\mathcal B}$ and there is $k\geq 1$ such that: 1) $M^2_{\mathcal B}$ is a union $M^2_1\cup...\cup M^2_k$ of disjoint tame surfaces such that every $M^2_i$ is homeomorphic to the 2-torus $T^2$. 2) the restriction of $f^k$ to $M^2_i$ $(i\in\{1,...,k\})$ is conjugate to Anosov automorphism of $T^2$

Confronting system barriers for ST- elevation MI in low and middle income countries with a focus on India

© 2017 Our previous research found seven specific factors that cause system delays in ST-elevation Myocardial infarction management in developing countries. These delays, in conjunction with a lack of organized STEMI systems of care, result in inefficient processes to treat AMI in developing countries. In our present opinion paper, we have specifically explored the three most pertinent causes that afflict the seven specific factors responsible for system delays. In doing so, we incorporated a unique strategy of global STEMI expertise. With this methodology, the recommendations were provided by expert Indian cardiologist and final guidelines were drafted after comprehensive discussions by the entire group of submitting authors. We expect these recommendations to be utilitarian in improving STEMI care in developing countries

Management of Acute Myocardial Infarction During the COVID-19 Pandemic.

The worldwide pandemic caused by the novel acute respiratory syndrome coronavirus 2 (SARS-CoV2) has resulted in a new and lethal disease termed coronavirus disease 2019 (COVID-19). Although there is an association between cardiovascular disease and COVID-19, the majority of patients who need cardiovascular care for the management of ischemic heart disease may not be infected with COVID-19. The objective of this document is to provide recommendations for a systematic approach for the care of patients with an acute myocardial infarction (AMI) during the COVID-19 pandemic. There is a recognition of two major challenges in providing recommendations for AMI care in the COVID-19 era. Cardiovascular manifestations of COVID-19 are complex with patients presenting with AMI, myocarditis simulating a ST-elevation MI presentation, stress cardiomyopathy, non-ischemic cardiomyopathy, coronary spasm, or nonspecific myocardial injury and the prevalence of COVID-19 disease in the US population remains unknown with risk of asymptomatic spread. This document addresses the care of these patients focusing on 1) the varied clinical presentations; 2) appropriate personal protection equipment (PPE) for health care workers; 3) role of the Emergency Department, Emergency Medical System and the Cardiac Catheterization Laboratory; and 4) Regional STEMI systems of care. During the COVID-19 pandemic, primary PCI remains the standard of care for STEMI patients at PCI capable hospitals when it can be provided in a timely fashion, with an expert team outfitted with PPE in a dedicated CCL room. A fibrinolysis-based strategy may be entertained at non-PCI capable referral hospitals or in specific situations where primary PCI cannot be executed or is not deemed the best option

Racial, Ethnic, and Sex Disparities in Patients With STEMI and Cardiogenic Shock

OBJECTIVES: The aim of this study was to evaluate the combined impact of race, ethnicity, and sex on in-hospital outcomes using data from the National Inpatient Sample. BACKGROUND: Cardiogenic shock (CS) is a major cause of mortality following ST-segment elevation myocardial infarction (STEMI). Early revascularization reduces mortality in such patients. Mechanical circulatory support (MCS) devices are increasingly used to hemodynamically support patients during revascularization. Little is known about racial, ethnic, and sex disparities in patients with STEMI and CS. METHODS: The National Inpatient Sample was queried from January 2006 to September 2015 for hospitalizations with STEMI and CS. The associations between sex, race, ethnicity, and outcomes were examined using complex-samples multivariate logistic or generalized linear model regressions. RESULTS: Of 159,339 patients with STEMI and CS, 57,839 (36.3%) were women. In-hospital mortality was higher for all women (range 40% to 45.4%) compared with men (range 30.4% to 34.7%). Women (adjusted odds ratio [aOR]: 1.11; 95% confidence interval [CI]: 1.06 to 1.16; p \u3c 0.001) as well as Black (aOR: 1.18; 95% CI: 1.04 to 1.34; p = 0.011) and Hispanic (aOR: 1.19; 95% CI: 1.06 to 1.33; p = 0.003) men had higher odds of in-hospital mortality compared with White men, with Hispanic women having the highest odds of in-hospital mortality (aOR: 1.46; 95% CI: 1.26 to 1.70; p \u3c 0.001). Women were older (age: 69.8 years vs. 63.2 years), had more comorbidities, and underwent fewer invasive cardiac procedures, including revascularization, right heart catheterization, and MCS. CONCLUSIONS: There are significant racial, ethnic, and sex differences in procedural utilization and clinical outcomes in patients with STEMI and CS. Women are less likely to undergo invasive cardiac procedures, including revascularization and MCS. Women as well as Black and Hispanic patients have a higher likelihood of death compared with White men

Outcomes of nonemergent percutaneous coronary intervention requiring mechanical circulatory support in patients without cardiogenic shock

BACKGROUND: The utilization of mechanical circulatory support (MCS) for percutaneous coronary intervention (PCI) using percutaneous ventricular assist device (PVAD) or intra-aortic balloon pump (IABP) has been increasing. We sought to evaluate the outcome of coronary intervention using PVAD compared with IABP in noncardiogenic shock and nonacute myocardial infarction patients. METHOD: Using the National Inpatient Sampling (NIS) database from 2005 to 2014, we identified patients who underwent PCI using ICD 9 codes. Patients with cardiogenic shock, acute coronary syndrome, or acute myocardial infarction were excluded. Patient was stratified based on the MCS used, either to PVAD or IABP. Univariate and multivariate logistic regression were performed to study PCI outcome using PVAD compared with IABP. RESULTS: Out of 21,848 patients who underwent PCI requiring MCS, 17,270 (79.0%) patients received IABP and 4,578 (21%) patients received PVAD. PVAD patients were older (69 vs. 67, p \u3c .001), were less likely to be women (23.3% vs. 33.3%, p \u3c .001), and had higher rates of hypertension, diabetes, hyperlipidemia prior PCI, prior coronary artery bypass graft surgery, anemia, chronic lung disease, liver disease, renal failure, and peripheral vascular disease compared with IABP group (p ≤ .007). Using Multivariate logistic regression, PVAD patients had lower in-hospital mortality (6.1% vs. 8.8%, adjusted odds ratio [aOR] 0.62; 95% CI 0.51, 0.77, p \u3c .001), vascular complications (4.3% vs. 7.5%, aOR 0.78; 95% CI 0.62, 0.99, p = .046), cardiac complications (5.6% vs. 14.5%, aOR 0.29; 95% CI 0.24, 0.36, p \u3c .001), and respiratory complications (3.8% vs. 9.8%, aOR 0.37; 95% CI 0.28, 0.48, p \u3c .001) compared with patients who received IABP. CONCLUSION: Despite higher comorbidities, nonemergent PCI procedures using PVAD were associated with lower mortality compared with IABP

Bayesian Hierarchical Models Combining Different Study Types and Adjusting for Covariate Imbalances: A Simulation Study to Assess Model Performance

BACKGROUND: Bayesian hierarchical models have been proposed to combine evidence from different types of study designs. However, when combining evidence from randomised and non-randomised controlled studies, imbalances in patient characteristics between study arms may bias the results. The objective of this study was to assess the performance of a proposed Bayesian approach to adjust for imbalances in patient level covariates when combining evidence from both types of study designs. METHODOLOGY/PRINCIPAL FINDINGS: Simulation techniques, in which the truth is known, were used to generate sets of data for randomised and non-randomised studies. Covariate imbalances between study arms were introduced in the non-randomised studies. The performance of the Bayesian hierarchical model adjusted for imbalances was assessed in terms of bias. The data were also modelled using three other Bayesian approaches for synthesising evidence from randomised and non-randomised studies. The simulations considered six scenarios aimed at assessing the sensitivity of the results to changes in the impact of the imbalances and the relative number and size of studies of each type. For all six scenarios considered, the Bayesian hierarchical model adjusted for differences within studies gave results that were unbiased and closest to the true value compared to the other models. CONCLUSIONS/SIGNIFICANCE: Where informed health care decision making requires the synthesis of evidence from randomised and non-randomised study designs, the proposed hierarchical Bayesian method adjusted for differences in patient characteristics between study arms may facilitate the optimal use of all available evidence leading to unbiased results compared to unadjusted analyses