Semi-quantitative evaluation of chest computed tomography for coronavirus disease 2019 in a critical care unit: A case-control study

Abstract

The spread of abnormal opacity on chest computed tomography (CT) has been reported as a predictor of coronavirus disease 2019 (COVID-19) severity; however, the relationship between CT findings and prognosis in patients with severe COVID-19 remains unclear. The objective of this study was to evaluate the extent of abnormal opacity on chest CT and its association with prognosis in patients with COVID-19 in a critical care medical center, using a simple semi-quantitative method. This single-center casecontrol study included patients diagnosed with severe COVID-19 pneumonia who were admitted to a critical care center. The diagnosis of COVID-19 was based on positive results of a reverse transcription polymerase chain reaction test. All patients underwent non-contrast whole-body CT upon admission. Six representative axial chest CT images were selected for each patient to evaluate the extent of lung lesions. The percentage of the area involved in the representative CT images was visually assessed by 2 radiologists and scored on 4-point scale to obtain the bedside CT score, which was compared between patients who survived and those who died using the Mann-Whitney U test. A total of 63 patients were included in this study: 51 survived and 12 died after intensive treatment. The inter-rater reliability of bedside scores between the 2 radiologists was acceptable. The median bedside CT score of the survival group was 12.5 and that of the mortality group was 16.5; the difference between the 2 groups was statistically significant. The degree of opacity can be easily scored using representative CT images in patients with severe COVID-19 pneumonia, without sophisticated software. A greater extent of abnormal opacity is associated with poorer prognosis. Predicting the prognosis of patients with severe COVID-19 could facilitate prompt and appropriate treatment.

Prediction of prognosis in patients with severe COVID-19 pneumonia using CT score by emergency physicians: a single-center retrospective study

“…COVID-19 is not likely to be severe, but severe cases of pneumonia often lead to death 2 . Because CT is very useful in determining the severity of the disease, various scoring methods using CT have been used, and it has been found that higher scores are related to the severity of the disease 7,8,[11][12][13][14][15][16][17][18] . Three key points influence the scoring by CT.…”

“…A different way to read the lungs is to divide them into three zones: upper, middle, and lower. The upper section is from the apex of the lung to the bronchial bifurcation, the middle section is from the bronchial bifurcation to the right inferior pulmonary vein, and the lower section is from the right inferior pulmonary vein to the diaphragm, for a total of six locations on both sides 17,18 . In addition to this division, there is another method in which the lungs are divided into anterior and posterior sections for a total of 12 regions for reading 19 .…”

“…The radiologist CT score predicted death or ECMO group with ROC of 0.681 (0.518-0.844) with a cutoff value of 19.75, sensitivity of 75%, and specificity of 68%. The death or ECMO versus survival group (median [quartiles]) had a CT score of 21.7 (19.5-22.7) versus 18(15)(16)(17)(18)(19)(20)(21), p = 0.048. The prediction of death or ECMO group by the emergency physicians and radiologists was ROC 0.718 (0.561-0.875) versus 0.681 (0.518-0.844), p = 0.238, with no difference between the two groups.…”