18 research outputs found

    Longer and better lives for patients with atrial fibrillation:the 9th AFNET/EHRA consensus conference

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    Aims: Recent trial data demonstrate beneficial effects of active rhythm management in patients with atrial fibrillation (AF) and support the concept that a low arrhythmia burden is associated with a low risk of AF-related complications. The aim of this document is to summarize the key outcomes of the 9th AFNET/EHRA Consensus Conference of the Atrial Fibrillation NETwork (AFNET) and the European Heart Rhythm Association (EHRA). Methods and results: Eighty-three international experts met in Münster for 2 days in September 2023. Key findings are as follows: (i) Active rhythm management should be part of the default initial treatment for all suitable patients with AF. (ii) Patients with device-detected AF have a low burden of AF and a low risk of stroke. Anticoagulation prevents some strokes and also increases major but non-lethal bleeding. (iii) More research is needed to improve stroke risk prediction in patients with AF, especially in those with a low AF burden. Biomolecules, genetics, and imaging can support this. (iv) The presence of AF should trigger systematic workup and comprehensive treatment of concomitant cardiovascular conditions. (v) Machine learning algorithms have been used to improve detection or likely development of AF. Cooperation between clinicians and data scientists is needed to leverage the potential of data science applications for patients with AF. Conclusions: Patients with AF and a low arrhythmia burden have a lower risk of stroke and other cardiovascular events than those with a high arrhythmia burden. Combining active rhythm control, anticoagulation, rate control, and therapy of concomitant cardiovascular conditions can improve the lives of patients with AF

    Determining crystal structures through crowdsourcing and coursework

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    We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality

    Clinical Characteristics of 46 Pregnant Women with a SARS-CoV-2 Infection in Washington State.

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    BACKGROUND: The impact of the coronavirus disease 2019 (Covid-19) on pregnant women is incompletely understood, but early data from case series suggest a variable course of illness from asymptomatic or mild disease to maternal death. It is unclear whether pregnant women manifest enhanced disease similar to influenza viral infection or whether specific risk factors might predispose to severe disease. OBJECTIVE: To describe maternal disease and obstetrical outcomes associated with Covid-19 disease in pregnancy to rapidly inform clinical care. STUDY DESIGN: Retrospective study of pregnant patients with a laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection from six hospital systems in Washington State between January 21, 2020 and April 17, 2020. Demographics, medical and obstetric history, and Covid-19 encounter data were abstracted from medical records. RESULTS: A total of 46 pregnant patients with a SARS-CoV-2 infection were identified from hospital systems capturing 40% of births in Washington State. Nearly all pregnant individuals with a SARS-CoV-2 infection were symptomatic (93.5%, n=43) and the majority were in their second or third trimester (43.5%, n=20 and 50.0%, n=23, respectively). Symptoms resolved in a median of 24 days (interquartile range 13-37). Seven women were hospitalized (16%) including one admitted to the intensive care unit. Six cases (15%) were categorized as severe Covid-19 disease with nearly all patients being either overweight or obese prior to pregnancy, asthma or other co-morbidities. Eight deliveries occurred during the study period, including a preterm birth at 33 weeks to improve pulmonary status in a woman with Class III obesity. One stillbirth occurred of unknown etiology. CONCLUSIONS: Nearly 15% of pregnant patients developed severe Covid-19, which occurred primarily in overweight or obese women with underlying conditions. Obesity and Covid-19 may synergistically increase risk for a medically-indicated preterm birth to improve maternal pulmonary status in late pregnancy. Collectively, these findings support categorizing pregnant patients as a higher risk group, particularly for those with chronic co-morbidities
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