ORIGINAL ARTICLE Risk stratification in COVID‑19 629 the COVID‑19 mortality risk to be 3.4%. 2 Te me‑ dian time from symptom onset to radiological confrmation of this viral pneumonia is 5 days, whereas the median time from symptom onset to ICU admission is approximately 9.5 days. 3 To identify predictors of clinical outcomes in patients with COVID‑19 is essential in helping healthcare facilities in pandemic planning and INTROduCTION Coronavirus disease 2019 (COVID‑19), caused by the outbreak of se‑ vere acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2), has recently been announced a global pandemic by the World Health Organiza‑ tion. 1 Tis infection can lead to severe respiratory distress requiring intensive care unit (ICU) admis‑ sion. Te World Health Organization estimated ORIGINAL ARTICLE Novel coronavirus disease 2019: predicting prognosis with a computed tomography–based disease severity score and clinical laboratory data Ali Sabri 1* , Amir H. Davarpanah 2 * , Arash Mahdavi 3 , Alireza Abrishami 4 , Mehdi Khazaei 5 , Saman Heydari 5 , Reyhane Asgari 5 , Seyyed Mojtaba Nekooghadam 6 , Julian Dobranowski 1 , Morteza Sanei Taheri 7 1 Department of Radiology, McMaster University, Niagara Health, St. Catharines, Ontario, Canada 2 Department of Radiology, Emory University School of Medicine, Emory University Hospital, Atlanta, Georgia, United States 3 Department of Radiology, Shahid Beheshti University of Medical Sciences, Modarres Hospital, Tehran, Iran 4 Department of Radiology, Shahid Beheshti University of Medical Sciences, Labbafinejad Hospital, Tehran, Iran 5 Department of Radiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran 6 Department of Internal Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran 7 Department of Radiology, Shahid Beheshti University of Medical Sciences, Shohada‑e‑Tajrish Hospital, Tehran, Iran Correspondence to: Ali Sabri, MD, FRCPC, Department of Radiology, McMaster University, Niagara Health, 1200‑4th Ave, St. Catharines, L2S 0A9 Ontario, Canada, phone: +1 905 616 0202, email: sabri.ali@gmail.com Received: May 17, 2020. Revision accepted: June 2, 2020. Published online: June 5, 2020. Pol Arch Intern Med. 2020; 130 (7‑8): 629‑634 doi:10.20452/pamw.15422 Copyright by the Author(s), 2020 * AS and AHD contributed equally to this work. KEy wORds novel coronavirus, computed tomography– –based disease severity scoring, mortality, pandemic, risk stratification AbsTRACT INTROduCTION Currently, there are known contributing factors but no comprehensive methods for predicting the mortality risk or intensive care unit (ICU) admission in patients with novel coronavirus disease 2019 (COVID‑19). ObjECTIvEs The aim of this study was to explore risk factors for mortality and ICU admission in patients with COVID‑19, using computed tomography (CT) combined with clinical laboratory data. PATIENTs ANd mEThOds Patients with polymerase chain reaction–confirmed COVID‑19 (n = 63) from university hospitals in Tehran, Iran, were included. All patients underwent CT examination. Subsequently, a total CT score and the number of involved lung lobes were calculated and compared against collected laboratory and clinical characteristics. Univariable and multivariable proportional hazard analyses were used to determine the association among CT, laboratory and clinical data, ICU admission, and in‑hospital death. REsuLTs By univariable analysis, in‑hospital mortality was higher in patients with lower oxygen satu‑ ration on admission (below 88%), higher CT scores, and a higher number of lung lobes (more than 4) involved with a diffuse parenchymal pattern. By multivariable analysis, in‑hospital mortality was higher in those with oxygen saturation below 88% on admission and a higher number of lung lobes involved with a diffuse parenchymal pattern. The risk of ICU admission was higher in patients with comorbidities (hypertension and ischemic heart disease), arterial oxygen saturation below 88%, and pericardial effusion. CONCLusIONs We can identify factors affecting in‑hospital death and ICU admission in COVID‑19. This can help clinicians to determine which patients are likely to require ICU admission and to inform strategic healthcare planning in critical conditions such as the COVID‑19 pandemic.