scholarly journals Arrhythmia Risk During the 2016 US Presidential Election: The Cost of Stressful Politics

2021 ◽  
Author(s):  
Lindsey Rosman ◽  
Elena Salmoirago‐Blotcher ◽  
Rafat Mahmood ◽  
Hannan Yang ◽  
Quefeng Li ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Cardiac Arrhythmias ◽  
Presidential Election ◽  
Control Period ◽  
Political Affiliation ◽  
County Level ◽  
Extreme Stress ◽  
Cardiac Devices ◽  
Us Presidential Election ◽  
Election Results

Background Anger and extreme stress can trigger potentially fatal cardiovascular events in susceptible people. Political elections, such as the 2016 US presidential election, are significant stressors. Whether they can trigger cardiac arrhythmias is unknown. Methods and Results In this retrospective case‐crossover study, we linked cardiac device data, electronic health records, and historic voter registration records from 2436 patients with implanted cardiac devices. The incidence of arrhythmias during the election was compared with a control period with Poisson regression. We also tested for effect modification by demographics, comorbidities, political affiliation, and whether an individual's political affiliation was concordant with county‐level election results. Overall, 2592 arrhythmic events occurred in 655 patients during the hazard period compared with 1533 events in 472 patients during the control period. There was a significant increase in the incidence of composite outcomes for any arrhythmia (incidence rate ratio [IRR], 1.77 [95% CI, 1.42–2.21]), supraventricular arrhythmia (IRR, 1.82 [95% CI, 1.36–2.43]), and ventricular arrhythmia (IRR, 1.60 [95% CI, 1.22–2.10]) during the election relative to the control period. There was also an increase in specific types of arrhythmia, including atrial fibrillation (IRR, 1.50 [95% CI, 1.06–2.11]), supraventricular tachycardia (IRR, 3.7 [95% CI, 2.2–6.2]), nonsustained ventricular tachycardia (IRR, 1.7 [95% CI, 1.3–2.2]), and daily atrial fibrillation burden ( P <0.001). No significant interaction was found for sex, race/ethnicity, device type, age ≥65 years, hypertension, coronary artery disease, heart failure, political affiliation, or concordance between individual political affiliation and county‐level election results. Conclusions There was a significant increase in cardiac arrhythmias during the 2016 US presidential election. These findings suggest that exposure to stressful sociopolitical events may trigger arrhythmogenesis in susceptible people.

MAPS AND CARTOGRAMS OF THE 2004 US PRESIDENTIAL ELECTION RESULTS

2005 ◽  
Vol 08 (01) ◽  
pp. 117-123 ◽  
Author(s):  
M. T. GASTNER ◽  
C. R. SHALIZI ◽  
M. E. J. NEWMAN
Keyword(s):  
United States ◽  
Presidential Election ◽  
Popular Support ◽  
Us Presidential Election ◽  
Election Results

Conventional maps of election results can give a misleading picture of the popular support that candidates have because population is highly non-uniform and equal areas on a map may not correspond to equal numbers of voters. Taking the example of the 2004 United States presidential election, we show how this problem can be corrected using a cartogram — a map in which the sizes of regions such as states are rescaled according to population or some other variable of interest.

Subclinical Atrial Fibrillation: A Silent Threat with Uncertain Implications

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Anthony H. Kashou ◽  
Demilade A. Adedinsewo ◽  
Peter A. Noseworthy
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Atrial Fibrillation ◽  
Cardiac Arrhythmias ◽  
Online Publication ◽  
Stroke Risk ◽  
Annual Review ◽  
Publication Date ◽  
Cardiac Devices ◽  
All Cause Mortality

Atrial fibrillation (AF) is one of the most common cardiac arrhythmias. Implantable and wearable cardiac devices have enabled the detection of asymptomatic AF episodes—termed subclinical AF (SCAF). SCAF, the prevalence of which is likely significantly underestimated, is associated with increased cardiovascular and all-cause mortality and a significant stroke risk. Recent advances in machine learning, namely artificial intelligence–enabled ECG (AI-ECG), have enabled identification of patients at higher likelihood of SCAF. Leveraging the capabilities of AI-ECG algorithms to drive screening protocols could eventually allow for earlier detection and treatment and help reduce the burden associated with AF. Expected final online publication date for the Annual Review of Medicine, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Was the Joke on the Democrats Again? Turnout and Partisan Choice in the 2004 U.S. Election

2007 ◽  
Vol 28 ◽  
pp. 81-95 ◽  
Author(s):  
Michael Martinez ◽  
David Hill
Keyword(s):  
Presidential Election ◽  
County Level ◽  
Electoral Participation ◽  
Major Party ◽  
Gubernatorial Elections ◽  
Turnout Rate ◽  
Election Results ◽  
Gubernatorial Election ◽  
2004 Presidential Election

The peak turnout rate in the 2004 presidential election highlights an important question for students of electoral participation: Did the higher levels of turnout advantage one of the two major party candidates? In this paper, we analyze state and county-level presidential and gubernatorial election results in 2000 and 2004, and find that Bush won the presidential election in spite of, rather than because of, the increase in turnout. The partisan effects of turnout varied across gubernatorial elections, and we found no evidence that local partisan minorities benefited from higher levels of turnout.

scholarly journals The Effects of Compression on the Detection of Atrial Fibrillation in ECG Signals

2021 ◽  
Vol 11 (13) ◽  
pp. 5908
Author(s):  
Raquel Cervigón ◽  
Brian McGinley ◽  
Darren Craven ◽  
Martin Glavin ◽  
Edward Jones
Keyword(s):  
Atrial Fibrillation ◽  
Characteristic Curve ◽  
Set Partitioning ◽  
Constrained Systems ◽  
Battery Life ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Signal Compression ◽  
Ecg Signals ◽  
Cardiac Devices

Although Atrial Fibrillation (AF) is the most frequent cause of cardioembolic stroke, the arrhythmia remains underdiagnosed, as it is often asymptomatic or intermittent. Automated detection of AF in ECG signals is important for patients with implantable cardiac devices, pacemakers or Holter systems. Such resource-constrained systems often operate by transmitting signals to a central server where diagnostic decisions are made. In this context, ECG signal compression is being increasingly investigated and employed to increase battery life, and hence the storage and transmission efficiency of these devices. At the same time, the diagnostic accuracy of AF detection must be preserved. This paper investigates the effects of ECG signal compression on an entropy-based AF detection algorithm that monitors R-R interval regularity. The compression and AF detection algorithms were applied to signals from the MIT-BIH AF database. The accuracy of AF detection on reconstructed signals is evaluated under varying degrees of compression using the state-of-the-art Set Partitioning In Hierarchical Trees (SPIHT) compression algorithm. Results demonstrate that compression ratios (CR) of up to 90 can be obtained while maintaining a detection accuracy, expressed in terms of the area under the receiver operating characteristic curve, of at least 0.9. This highlights the potential for significant energy savings on devices that transmit/store ECG signals for AF detection applications, while preserving the diagnostic integrity of the signals, and hence the detection performance.

Identity propaganda: Racial narratives and disinformation

2021 ◽  
pp. 146144482110292
Author(s):  
Madhavi Reddi ◽  
Rachel Kuo ◽  
Daniel Kreiss
Keyword(s):  
Presidential Election ◽  
Power Relations ◽  
Vice President ◽  
Power Structures ◽  
Marginalized Groups ◽  
Identity Based ◽  
Us Presidential Election ◽  
Social Orders ◽  
Racial Narratives

This article develops the concept of “identity propaganda,” or narratives that strategically target and exploit identity-based differences in accord with pre-existing power structures to maintain hegemonic social orders. In proposing and developing the concept of identity propaganda, we especially aim to help researchers find new insights into their data on misinformation, disinformation, and propaganda by outlining a framework for unpacking layers of historical power relations embedded in the content they analyze. We focus on three forms of identity propaganda: othering narratives that alienate and marginalize non-white or non-dominant groups; essentializing narratives that create generalizing tropes of marginalized groups; and authenticating narratives that call upon people to prove or undermine their claims to be part of certain groups. We demonstrate the utility of this framework through our analysis of identity propaganda around Vice President Kamala Harris during the 2020 US presidential election.

scholarly journals Strengthening the EU’s resilience to hybrid threats

European View ◽  
2021 ◽  
pp. 178168582110046
Author(s):  
Sandra Kalniete ◽  
Tomass Pildegovičs
Keyword(s):  
Case Studies ◽  
Presidential Election ◽  
Turning Point ◽  
Hybrid Methods ◽  
Cyber Attacks ◽  
Political Will ◽  
Member States ◽  
Eu Member States ◽  
Us Presidential Election ◽  
Hybrid Threats

Against the backdrop of the deterioration of EU–Russia relations in recent years, there has been a shift in the awareness of hybrid threats all across the Union. At the same time, there is evidence of a growing political will to strengthen resilience to these threats. While hostile foreign actors have long deployed hybrid methods to target Europe, Russia’s intervention in Ukraine in 2014, interference in the 2016 US presidential election, and repeated cyber-attacks and disinformation campaigns aimed at EU member states have marked a turning point, exposing Western countries’ unpreparedness and vulnerability to these threats. This article analyses the EU’s resilience to hybrid warfare from institutional, regulatory and societal perspectives, with a particular focus on the information space. By drawing on case studies from member states historically at the forefront of resisting and countering Russian-backed disinformation campaigns, this article outlines the case for a whole-of-society approach to countering hybrid threats and underscores the need for EU leadership in a standard-setting capacity.

scholarly journals A Data-Driven Framework for Coding the Intent and Extent of Political Tweeting, Disinformation, and Extremism

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 148
Author(s):  
Mahdi Hashemi
Keyword(s):  
Social Networks ◽  
Presidential Election ◽  
Online Social Networks ◽  
Data Driven ◽  
The Political ◽  
Political Affiliation ◽  
News Sources ◽  
The U.S

Disinformation campaigns on online social networks (OSNs) in recent years have underscored democracy’s vulnerability to such operations and the importance of identifying such operations and dissecting their methods, intents, and source. This paper is another milestone in a line of research on political disinformation, propaganda, and extremism on OSNs. A total of 40,000 original Tweets (not re-Tweets or Replies) related to the U.S. 2020 presidential election are collected. The intent, focus, and political affiliation of these political Tweets are determined through multiple discussions and revisions. There are three political affiliations: rightist, leftist, and neutral. A total of 171 different classes of intent or focus are defined for Tweets. A total of 25% of Tweets were left out while defining these classes of intent. The purpose is to assure that the defined classes would be able to cover the intent and focus of unseen Tweets (Tweets that were not used to determine and define these classes) and no new classes would be required. This paper provides these classes, their definition and size, and example Tweets from them. If any information is included in a Tweet, its factuality is verified through valid news sources and articles. If any opinion is included in a Tweet, it is determined that whether or not it is extreme, through multiple discussions and revisions. This paper provides analytics with regard to the political affiliation and intent of Tweets. The results show that disinformation and extreme opinions are more common among rightists Tweets than leftist Tweets. Additionally, Coronavirus pandemic is the topic of almost half of the Tweets, where 25.43% of Tweets express their unhappiness with how Republicans have handled this pandemic.

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