Radiologic severity index can be used to predict mortality risk in patients with COVID-19

Abstract

Introduction: Pneumonia is a common symptom of coronavirus disease-2019 (COVID-19), and this study aimed to determine how analyzing initial thoracic computerized-tomography (CT) scans using semi-quantitative methods could be used to predict the outcomes for hospitalized patients. Materials and Methods: This study looked at previously collected data from adult patients who were hospitalized with a positive test for severe acute respiratory syndrome coronavirus-2 and had CT scans of their thorax at the time of presentation. The CT scans were evaluated for the extent of lung involvement using a semi-quantitative scoring system ranging from 0 to 72. The researchers then analyzed whether CT score could be used to predict outcomes. Results: The study included 124 patients, 55 being females, with a mean age of 46.13 years and an average duration of hospitalization of 11.69 days. Twelve patients (9.6%) died within an average of 17.2 days. The non-surviving patients were significantly older, had more underlying health conditions, and higher CT scores than the surviving patients. After taking age and comorbidities into account, each increase in CT score was associated with a 1.048 increase in the risk of mortality. CT score had a good ability to predict mortality, with an area under the curve of 0.857 and a sensitivity of 75% and specificity of 85.7% at a cut-off point of 25.5. Conclusion: Radiologic severity index, which is calculated using a semi-quantitative CT scoring system, can be used to predict the mortality of COVID-19 patients at the time of their initial hospitalization.