Covid-19(Asterivir)

Background Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causing Covid-19 pandemic continues to be a global health threat with a massive burden on health care systems resulting in more than six million deaths in 188 countries. Because of wide clinical spectrum of disease severity, having clinically applicable prognostic tools for early identification of patients at high risk of progression to severe / critical illness is essential to guide clinical decision making and resource allocation efforts. So far, clinical prognostic tools have focused on host factors, but more recent data indicated a significant association between SARS-CoV-2 variants and the development of complications such as long COVID.
Objectives
Validation of the ALA & ALKA prediction tools for initial evaluation of patients diagnosed with COVID-19 infection.
Comparison of performance of the ALA & ALKA prediction tools with the currently clinical risk assessment scoring system used during initial evaluation of patients diagnosed with COVID-19 infection.
Evaluation of the clinical risk assessment scoring based on number of comorbidities in prediction of COVID-19 related complications
Assessment of the association between SARS-CoV-2 variants and the risk of COVID-19 severity
Assessment of the impact of SARS-CoV-2 variants on the performance of ALA & ALKA prediction tools
Methods Data will be abstracted from electronic medical records including demographics, clinical manifestation, comorbidities, and initial laboratory data in patients with Covid 19 infection of around 2000 patients presented initially to COVID assessment centre, including SARS CoV-2 sequencing data. Furthermore, population level SARS-CoV-2 RNA sequence data will also be examined and correlated with COVID-19 severity and the performance of prediction tools.