AbstractObjectives: To evaluate the computed tomography (CT) based scoring system, called as CT severity score (CT-SS), in the severity assessment of COVID cases with clinico-radiological correlation.
Methods: This retrospective study was done among 303 patients, who are RT-PCR positive for COVID-19. The CT chest images of the above patients were reviewed in the radiology database. CT severity score (CT-SS) was calculated as the sum of scores in five lobes, based on the percentage of parenchymal opacification (0:0%; 1, < 5%; 2:5–25%; 3:26–50%; 4:51–75%; 5, > 75%; range 0–5; global score 0–25). All patients were clinically categorized as mild, moderate and severe, based on severity by the Government of India Ministry of Health and Family Welfare, Directorate General of Health Services.
Results: The area under the ROC curve for identifying severe group was 0.937 and the optimal CT-SS threshold for identifying severe disease was 17.5, with a good sensitivity of 97.8% and specificity of 85.3%.
Conclusion: A CT-SS more than 17.5 could identify severe from non-severe forms of disease, and hence will be potentially useful in the triage of patients in scenarios combining high patient volumes and limited healthcare resources or PCR testing capabilities.
Clinical impact:
1. The CT severity score (CT-SS) was higher in patients with severe COVID-19 in comparison with patient with mild or moderate disease.
2. The optimal CT-SS threshold for identifying severe disease was 17.5, with 97.8% sensitivity and 85.3% specificity.
3. Hence, CT-SS will be very useful in triage of patients due to high patient volumes and limited available healthcare resources.
