• Kiran Hilal Department of Radiology, Aga Khan University, Karachi-Pakistan
  • Jehanzeb Shahid Department of Radiology, Aga Khan University, Karachi-Pakistan
  • Abullah Ameen Department of Radiology, Aga Khan University, Karachi-Pakistan
  • Russell Seth Martins Medical College, Aga Khan University, Karachi-Pakistan
  • Avinash Nankani Medical College, Dow University of Health Sciences, Karachi-Pakistan
  • Tanveer ul Haq Department of Radiology, Aga Khan University, Karachi-Pakistan
  • Ainan Arshad Department of Medicine, Aga Khan University, Karachi-Pakistan




Background: Though various computerized tomography (CT) severity scores have been described for risk prognostication for coronavirus disease 2019 (COVID-19), most are challenging to calculate and have variable inter-observer agreement. The objective of this study was to develop a simple CT severity score (CT-SS) with good inter-observer agreement and assess its correlation with clinical outcome. Methods: This retrospective study was conducted at the Aga Khan University Hospital (AKUH), from April-August 2020. All patients who were PCR positive for COVID-19 and underwent CT chest examination at AKUH were included. Severity of disease was described on the basis of a 10-point CT severity score (CT-SS) devised at our institution. CT-SS were categorized as Low (0–7) and High (8–10). Inter-observer reliability between radiologist and COVID-19 intensivist was assessed using the Kappa statistic. Results: A total of 73 patients were included, the majority male (58.9%) with mean age 55.8±13.93 years. The CT-SS rated on 0–10 showed substantial inter-observer reliability between radiologist and intensivist with a Kappa statistic of 0.78. Patients with CT-SS 8–10 had a significantly higher ICU admission & intubation rate (53.8% vs. 23.5%) and mortality rate (35.9% vs. 11.8%; p=0.017), as compared to those with CT-SS 0-7. Conclusion: We conclude that the described CT severity score (CT-SS) is a quick, effective, and easily reproducible tool for prediction of adverse clinical outcome in patients with COVID 19 pneumonia. The tool shows good inter-observer agreement when calculated by radiologist and physician independently.

Author Biography

Ainan Arshad, Department of Medicine, Aga Khan University, Karachi-Pakistan

Senior Intructor, Section of Internal Medicine, Department of Medicine, Aga Khan University, Karachi, Pakistan


WHO. Timeline of WHO’s response to COVID-19. 2020. [Internet]. updated 30th June 202012th July 2020 [cited 2021 March]. Available from:

Worldometer. COVID-19 Coronavirus Pandemic. [Internet]. 2020 [cited 2021 March]. Available from:

Surveillances V. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19)—China, 2020. China CDC Weekly 2020;2(8):113–22.

Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395(10223):497–506.

Pan Y, Guan H. Imaging changes in patients with 2019-nCov. Eur Radiol 2020;30(7):3612–3.

Lei J, Li J, Li X, Qi X. CT imaging of the 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology 2020;295(1):18.

Xu B, Xing Y, Peng J, Zheng Z, Tang W, Sun Y, et al. Chest CT for detecting COVID-19: a systematic review and meta-analysis of diagnostic accuracy. Eur Radiol 2020;30(10):5720–7.

Stephanie S, Shum T, Cleveland H, Challa SR, Herring A, Jacobson FL, et al. Determinants of Chest X-Ray Sensitivity for COVID-19: A Multi-Institutional Study in the United States. Radiol Cardiothorac Imaging 2020;2(5):e200337.

Yan L, Zhang HT, Goncalves J, Xiao Y, Wang M, Guo Y, et al. An interpretable mortality prediction model for COVID-19 patients. Nat Mach Intell 2020;2(5):283–8.

Zhou S, Wang Y, Zhu T, Xia L. CT features of coronavirus disease 2019 (COVID-19) pneumonia in 62 patients in Wuhan, China. Am J Roentgenol 2020;214(6):1287–94.

Simpson S, Kay FU, Abbara S, Bhalla S, Chung JH, Chung M, et al. Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA. Radiol Cardiothorac Imaging 2020;2(2):e200152.

Tian S, Xiong Y, Liu H, Niu L, Guo J, Liao M, et al. Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies. Mod Pathol 2020;33(6):1007–17.

Lippi G, Favaloro EJ. D-dimer is associated with severity of coronavirus disease 2019: a pooled analysis. Thromb Haemost 2020;120(5):876–8.

Liu F, Li L, Xu M, Wu J, Luo D, Zhu Y, et al. Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19. J Clin Virol 2020;127:104370.

Francone M, Iafrate F, Masci GM, Coco S, Cilia F, Manganaro L, et al. Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis. Eur Radiol 2020;30(12):6808–17.

Yang R, Li X, Liu H, Zhen Y, Zhang X, Xiong Q, et al. Chest CT severity score: an imaging tool for assessing severe COVID-19. Radiol Cardiothorac Imaging 2020;2(2):e200047.

Zhang J, Meng G, Li W, Shi B, Dong H, Su Z, et al. Relationship of chest CT score with clinical characteristics of 108 patients hospitalized with COVID-19 in Wuhan, China. Respir Res 2020;21(1):180.