551 research outputs found
Atrial Fibrillation and Myocardial Infarction: A Systematic Review and Appraisal of Pathophysiologic Mechanisms
No full textA growing body of evidence suggests that atrial fibrillation (AF) is associated with myocardial infarction (MI). However, incidence and management of MI in AF is still undefined.
METHODS AND RESULTS:
We searched MEDLINE via PubMed and Cochrane database between 1965 and 2015. All observational clinical studies and interventional trials reporting 1-year incidence of MI in AF were included. We also discussed pathophysiological mechanisms, predictors, and therapeutic approaches to reduce the risk of MI in AF. Twenty-one observational studies and 10 clinical trials were included. The annual rate of MI in observational studies including AF patients ranged from 0.4% to 2.5%. Higher rates of MI were reported in AF patients with stable coronary artery disease (11.5%/year), vascular disease (4.47%/year), heart failure (2.9%/year), and in those undergoing coronary artery interventions (6.3%/year). However, lower annual rates have been described in AF patients from Eastern countries (0.2-0.3%/year), and in those enrolled in clinical trials (from 0.4 to 1.3%/year).
CONCLUSIONS:
AF patients had a significant residual risk of MI despite anticoagulant treatment. Coexistence of atherosclerotic risk factors and platelet activation account for the increased risk of MI in AF. Identification of high-risk AF patients is a needed first step to develop cost-effective approaches for prevention. A new score, the 2MACE score, has been recently developed to stratify MI risk in AF, and may help not only in allocating resources to high-risk groups, but also in design of studies examining novel therapies for prevention of MI in AF
Supplemental Material - Factors Associated With Fatigue in Persons With Atrial Fibrillation in the Atherosclerosis Risk in Communities (ARIC) Study
No full textSupplemental Material for Factors Associated With Fatigue in Persons With Atrial Fibrillation in the Atherosclerosis Risk in Communities (ARIC) Study by Kathryn A. Wood, PhD, RN, Aniqa B. Alam, MPH, Lin Yee Chen, MD, MS, Elsayed Z. Soliman, MD, MSc, MS, Arshed A. Quyyumi, MD, and Alvaro Alonso, MD, PhD in Biological Research For Nursing.</p
Cardiovascular Disease Burden in Low and Middle-Income Countries
No full textHealth discussion in developing countries
Race and atrial flutter: a needed update to understand the atrial fibrillation race paradox
No full textQuantifying secondary particle dose contributions in proton therapy
No full textIn order to create radiotherapy treatment plans for cancer patients, dose calculations need to be done as quickly as possible to get accurate results. However, current dose calculation algorithms take too much time to be deployed effectively. The current in house algorithm of the Medical Physics and Technology Section at the TU Delft, attempts to solve this problem by utilising a deterministic algorithm that has a significant time advantage over Monte Carlo algorithms. However, this comes with the cost of inaccuracy, one of which is that it assumesall dose is deposited locally along the beam path. This is inaccurate as secondary particles created from non-elastic nuclear interactions can deposit their dose far from the beam path due to retaining significant kinetic energy. This thesis attempts to reduce this inaccuracy by mapping and quantifying the secondary particles to assess their contribution in non-local dose deposition. And analysing the relevant particle’s energy and angle distributions to gain insight into the development of the particle's characteristics with depth. Thereafter the relevantparticle’s are then utilised as a source to emulate their production in a primary proton beam at different depths to obtain the relevant 3D dose distributions. The analysis concluded that secondary protons are the most relevant secondary particle as they contribute to 88% of the secondary dose and have a significant range to deposit their dose non locally. By utilising the secondary protons as a source, it was found that the relative error between the integrated depth dose (IDD) of the scored protons and the IDD obtained directly from Monte Carlo simulations is equal to 5.1% in the z-direction and 3.4% in the x and y-direction. The absolute difference was found to be 1.54 × 10−5 Gy which is equal to 0.096% of the total dose and 2.75% of the dose contributed by all secondary particles. The results show that the methodology can produce accurate 3D dose matrices for secondary protons at different depths, which can then be used to improve the accuracy of the in house algorithm by adding the precalculated 3D dose matrices to the algorithmApplied Physic
Left Atrial Mechanical Dysfunction and the Risk for Ischemic Stroke in People Without Prevalent Atrial Fibrillation or Stroke : A Prospective Cohort Study
No full textBackground: Atrial myopathy-characterized by changes in left atrial function and size-may precede and promote atrial fibrillation (AF) and cardiac thromboembolism. In people without prior AF or stroke, whether analysis of left atrial function and size can improve ischemic stroke prediction is unknown.Objective: To evaluate the association of echocardiographic left atrial function (reservoir, conduit, and contractile strain) and left atrial size (left atrial volume index) with ischemic stroke and determine whether these measures can improve the stroke prediction achieved by CHA(2)DS(2)-VASc score variables.Design: Prospective cohort study.Setting: ARIC (Atherosclerosis Risk in Communities) study.Participants: 4917 ARIC participants without prevalent stroke or AF.Measurements: Ischemic stroke events (2011 to 2019) were adjudicated by physicians. Left atrial strain was measured using speckle-tracking echocardiography.Results: Over 5 years, the cumulative incidences of ischemic stroke in the lowest quintiles of left atrial reservoir, conduit, and contractile strain were 2.99% (95% CI, 1.89% to 4.09%), 3.18% (CI, 2.14% to 4.22%), and 2.15% (CI, 1.09% to 3.21%), respectively, and that of severe left atrial enlargement was 1.99% (CI, 0.23% to 3.75%). On the basis of the Akaike information criterion, left atrial reservoir strain plus CHA(2)DS(2)-VASc variables was the best predictive model. With the addition of left atrial reservoir strain to CHA(2)DS(2)-VASc variables, 11.6% of the 112 participants with stroke after 5 years were reclassified to higher risk categories and 1.8% to lower risk categories. Among the 4805 participants who did not develop stroke, 12.2% were reclassified to lower and 12.7% to higher risk categories. Decision curve analysis showed a predicted net benefit of 1.34 per 1000 people at a 5-year risk threshold of 5%.Limitation: Underascertainment of subclinical AF.Conclusion: In people without prior AF or stroke, when added to CHA(2)DS(2)-VASc variables, left atrial reservoir strain improves stroke prediction and yields a predicted net benefit, as shown by decision curve analysis.Primary Funding Source: National Heart, Lung, and Blood Institute of the National Institutes of Health
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