ReviewHCA healthcare journal of medicine2020
COVID-19 and Arrhythmias: A Review of Cardiac Electrophysiology Associated with SARS-CoV-2.
Review in HCA healthcare journal of medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Description Coronavirus infectious disease 2019 (COVID-19) has become one of the most recognized viral illnesses to date. Most people infected with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have a benign clinical course, but there have also been catastrophic outcomes. Although, notoriously known to affect the respiratory system, extra-pulmonary manifestations have also been established. An increasing number of people have been reported to present with cardiac manifestations, which include but are not limited to arrhythmias. The cardiac conduction system can be damaged by various mechanisms in patients infected with SARS-CoV-2. In this review, we will attempt to briefly describe the arrhythmogenic potential of SARS-CoV-2 and the factors that play a key role in the electrophysiological pathology seen in COVID-19.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.