Abstract

COVID-19 has now been declared a pandemic. To date, COVID-19 has affected over 2.5 million people worldwide, resulting in over 170,000 reported deaths. Numerous preventative strategies and non-pharmaceutical interventions have been employed to mitigate the spread of disease including careful infection control, the isolation of patients, and social distancing. Management is predominantly focused on the provision of supportive care, with oxygen therapy representing the major treatment intervention. Medical therapy involving corticosteroids and antivirals have also been encouraged as part of critical management schemes. However, there is at present no specific antiviral recommended for the treatment of COVID-19, and no vaccine is currently available. Despite the strategic implementation of these measures, the number of new reported cases continues to rise at a profoundly alarming rate. As new findings emerge, there is an urgent need for up-to-date management guidelines. In response to this call, we review what is currently known regarding the management of COVID-19, and offer an evidence-based review of current practice.

Keywords

MedicinePandemicCoronavirus disease 2019 (COVID-19)GuidelinePsychological interventionIntensive care medicineIsolation (microbiology)Social distanceIntervention (counseling)2019-20 coronavirus outbreakInfection controlDiseaseFamily medicineNursingInfectious disease (medical specialty)OutbreakVirologyPathologyBioinformatics

MeSH Terms

BetacoronavirusCOVID-19Coronavirus InfectionsCritical CareHumansInfection ControlPandemicsPneumoniaViralPractice Guidelines as TopicSARS-CoV-2

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Publication Info

Year
2020
Type
review
Volume
77
Pages
206-216
Citations
431
Access
Closed

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Cite This

Maria Nicola, Niamh O’Neill, Catrin Sohrabi et al. (2020). Evidence based management guideline for the COVID-19 pandemic - Review article. International Journal of Surgery , 77 , 206-216. https://doi.org/10.1016/j.ijsu.2020.04.001

Identifiers

DOI
10.1016/j.ijsu.2020.04.001
PMID
32289472
PMCID
PMC7151371

Data Quality

Data completeness: 86%