Tomographic score (RAD-Covid Score) to assess the clinical severity of the novel coronavirus infection

Abstract

Objectives The severity of pulmonary Covid-19 infection can be assessed by the pattern and extent of parenchymal involvement observed in computed tomography (CT), and it is important to standardize the analysis through objective, practical, and reproducible systems. We propose a method for stratifying the radiological severity of pulmonary disease, the Radiological Severity Score (RAD-Covid Score), in Covid-19 patients by quantifying infiltrate in chest CT, including assessment of its accuracy in predicting disease severity. Methods This retrospective, single-center study analyzed patients with a confirmed diagnosis of Covid-19 infection by real-time reverse-transcriptase polymerase chain reaction, who underwent chest CT at hospital admission between March 6 and April 6, 2020. CT scans were classified as positive, negative, or equivocal, and a radiological severity score (RAD-Covid Score) was assigned. Clinical severity was also assessed upon hospital admission. Results 658 patients were included. Agreement beyond chance (kappa statistic) for the RAD-Covid Score was almost perfect among observers (0.833), with an overall agreement of 89.5%. The RAD-Covid Score was positively correlated with clinical severity and death, i.e., the higher the RAD-Covid Score, the greater the clinical severity and mortality. This association proved independent of age and comorbidities. Accuracy of this score was 66.9%. Conclusions The RAD-Covid Score showed good accuracy in predicting clinical severity at hospital admission and mortality in patients with confirmed Covid-19 infection and was an independent predictor of severity.

HRCT chest in patients suffering from COVID-19: Experience from a tertiary care centre in India during second wave of the pandemic

“…High-resolution computed tomography (HRCT) of chest has an important role in the initial assessment of the severity of lung disease, monitoring treatment response and in the diagnosis of pulmonary complications during or after treatment. Some studies have investigated the correlation between clinical severity of COVID-19 upon presentation and the severity of pulmonary involvement in their chest CT scans [9]. The quantitative severity can be assessed using a visual method (as in our study) or a software that determines the percentage of affected lung volumes using the machine learning algorithms [8].…”

Total severity score and age predict long-term hospitalization in COVID-19 pneumonia

“…TSS refers to a scoring system that accurately evaluates lung involvement and is estimated by at least two well-trained and experienced radiologists to assess the severity of COVID-19 in CT scans ( 23 ). Studies suggest the use of chest CT to facilitate diagnosis in patients with a high rate of suspicion and a negative PCR ( 24 , 25 ); nevertheless, in our study, CT was used in known cases.…”

Investigation of the relationship of CO-RADS and CT patterns with laboratory parameters in COVID-19 patients and a new perspective on the total CT scoring system

“…In our study, when the total CT score and the structured total CT score values were compared according to the CO-RADS groups 3, 4 and 5, significant differences were found between the groups 3 and 5 in terms of the structured total CT score and between the groups 3 and 5 and groups 4 and 5 in terms of the total CT score value. In a previous study, scoring was performed according to < 25% lung involvement, mild; 25–50% involvement, moderate; and > 50% involvement, advanced [ 23 ]. In our study, scoring was undertaken separately for each lung lobe, and therefore we consider this to be an innovative feature of our study since we obtained a structured total CT lung score by taking into account the pattern groups.…”

“…In our study, when the total CT score and the structured total CT score values were compared according to the CO-RADS groups 3, 4 and 5, significant Table 4 Relationship of the pattern groups with clinical and laboratory parameters p < 0.001*Significant difference in oxygen saturation between the pattern groups 0 and 1 (p < 0.001), and the pattern groups 0 and 2 (p = 0.031) p = 0.006*Significant difference in creatinine between the pattern groups 1 and 2 (p = 0.024), and the pattern groups 0 and 1 (p = 0.003) p < 0.001*Significant difference in C-reactive protein between the pattern groups 0 and 1 (p < 0.001) differences were found between the groups 3 and 5 in terms of the structured total CT score and between the groups 3 and 5 and groups 4 and 5 in terms of the total CT score value. In a previous study, scoring was performed according to < 25% lung involvement, mild; 25-50% involvement, moderate; and > 50% involvement, advanced [23]. In our study, scoring was undertaken separately for each lung lobe, and therefore we consider this to be an innovative feature of our study since we obtained a structured total CT lung score by taking into account the pattern groups.…”