Deadline for manuscript submissions: 08 February 2022Print Special Issue Flyer (17)
Emergency radiologist, Department of Radiology, Virgen de las Nieves University Hospital, Granada. Spain; Collaborating professor, department of Radiology and Physical Medicine, University of Granada, Spain; Co-leading researcher of the ‘Artificial Intelligence Applied to the Diagnosis and Prognosis of COVID-19’ project at the Distributed Computational Intelligence and Time Series Lab, University of Granada, Spain. https://dicits.ugr.es/covid19/
Interests: Emergency radiology, Artificial intelligence, COVID-19, Epidemiology, Medical education
The unprecedented impact of the COVID-19 pandemic has prompted a massive production of clinical research. However, many questions remain unanswered. In this regard, there are several limitations that hinder patient management in the emergency department, a cornerstone of hospital care for COVID-19 patients. Common problems in clinical practice include logistics and triaging of patients with non-specific symptoms, early identification of high-risk patients who should require hospital admission and more aggressive therapeutic approaches, or detection of associated complications such as pulmonary embolism. Changes in virus dynamics over time limit our understanding and ability to predict these clinical concerns in real-world practice. In this context, advanced statistics and artificial intelligence models have shown promising potential to assist specialists involved in patient management in the emergency department. However, there is significant variability and limitations depending on the methodologies, purposes and populations from which data are obtained.
This special issue focuses on exploiting epidemiological data of patients admitted to the emergency department due to suspected or confirmed COVID-19 infection with the aim to further our understanding of the dynamics of the virus and aid patient management in the emergency department. Notable interest topics include but are not limited to disease prevalence, diagnosis, laboratory and radiological findings, clinical management, complications and mortality. Conventional statistics and artificial intelligence methods analyzing differences between patients with overlapping symptoms, predicting patient outcomes, or assisting emergency specialists in decision-making regarding particular clinical questions which arise in daily practice are especially encouraged. In addition, studies tracking changes at different stages of the pandemic are of particular interest to gain insight into the clinical variability of COVID-19.
We welcome original articles, reviews and commentaries focused on the subject. The goal is to gain a longitudinal perspective on the challenges of the pandemics in the emergency department: how it started, the status quo and what can we expect with increasing vaccination across different countries.
SARS-CoV-2, COVID-19, Emergency care, Longitudinal management, Prognosis, Artificial intelligence, Statistics, Epidemiology
Manuscripts should be submitted online by submit system. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Original articles, case reports or comprehensive reviews are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Signa Viate is an international peer-reviewed open access journal published by MRE Press. As of January 2021, Signa Vitae will change to a bimonthly journal. Please visit the Instructions for Authors page before submitting a manuscript.The Article Processing Charge (APC) for publication in this open access journal is $1200. We normally offer a discount greater than 30% to all contributors invited by the Editor-in-Chief, Guest Editor (GE) and Editorial board member. Submitted papers should be well formatted and use good English.
An assessment of emergency department visits for cardiovascular diseases in the early phase of the COVID-19 pandemic in Istanbul
Factors associated with readmission to the Emergency Department in a cohort of COVID-19 hospitalized patients
Online publish date: 16 June 2021
Online publish date: 24 June 2021
Online publish date: 27 July 2021
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