COVID-19 Severity Index: A predictive score for hospitalized patients

ABSTRACT Introduction Pandemics pose a major challenge for public health preparedness, requiring a coordinated international response and the development of solid containment plans. An early and accurate identification of high-risk patients in the course of the actual COVID-19 pandemic is vital for planning and for making proper use of available resources. Objective The purpose of this study was to identify the key variables to create a predictive model that could be used effectively for triage. Methods A narrative literature review of 651 articles was conducted to assess clinical, laboratory and imaging findings of COVID-19 confirmed cases. After screening, 10 articles met the inclusion criteria and a list of suggested variables was gathered. A modified Delphi process analysis was performed to consult experts in order to generate a final list of variables for the creation of the predictive model. Results The modified Delphi process analysis identified 44 predictive variables that were used for building a severity prediction score, the COVID-19 Severity Index . Conclusion Specifically designed for current COVID-19 pandemic, COVID-19 Severity Index could be used as a reliable tool for strategic planning, organization and administration of resources by easily identifying hospitalized patients with higher risk of transfer to Intensive Care Unit (ICU).