Introduction of a Radiologic Severity Index for the 2019 Novel Corona Virus (COVID-19)
Abstract Background: Given the limited number of beds in intensive care units, establishing a system that can predict the outcome in COVID19 positive patients based on imaging plays an important role in using resources efficiently. Therefor this study was conducted to design an optimal scoring system related to the severity of COVID19 cases for distinguishing severe from non-severe patients. Materials and Methods: In this cross-sectional retrospective study, 82 patients with a definite diagnosis of COVID-19 infection, who had at least one chest CT scan in hospital course were enrolled.To assess the severity of pulmonary parenchymal involvement, we semi-quantitatively evaluated the extent and nature of abnormalities. The area of lung involvement was scored in three levels based on a 0-4 grading scale. Also, we established a 4-point scoring system for defining the nature of lung abnormalities. The two scores were multiplied by each other. A final radiologic severity score was determined after adding together the scores of all levels.Result: Of all cases, fifty-three (64.6%) were male with an average age of age 53.75. Among the patients in our study, 7 (8.5%) had severe disease and the mortality rate was 7.2%. The mean (±standard deviation) of the radiologic severity score was 34.3(±18.4) in the severe group and 11.3(±11.4) in the non-sever group. (P-value <0.05). Also, we found a significant reverse relationship between our severity score and O2 saturation (P-value <0.05).Conclusion: The radiologic severity score demonstrated a significant correlation with the patients' mortality and severity of illness in COVID-19 patients.