Crystal gazing: Myth or reality for critical care for covid-19 patients?

Abstract

Efforts are continuing worldwide to understand the epidemiology, pathogenesis, and treatments for COVID-19. However, at the moment treatment remains supportive with oxygen therapy, steroids, repurposed antivirals, and prevention of multiple organ dysfunction by using immunomodulators. COVID-19 remains challenging since the disease spectrum varies from asymptomatic infection to severe acute respiratory distress syndrome (ARDS) with high fatality rates. It is thus necessary to predict clinical outcomes and risk-stratify patients for ensuring early intensive care unit (ICU) admissions. An important aspect is building surge capacity, managing and optimizing therapeutic and operational resources. So far, data have been scarce, particularly from India, to identify predictors of poor outcomes and mortality early in the course of the disease. Risk models need to be developed in larger patient cohorts and the models need to be simple and easy to employ at the onset of the disease process to predict the risk of severe disease, need for mechanical ventilation, ICU length of stay (LOS), and mortality.