Archives of Academic Emergency Medicine. 2020; 8(1): e57 OR I G I N A L RE S E A RC H Correlation between Chest Computed Tomography Scan Findings and Mortality of COVID-19 Cases; a Cross sec- tional Study Masoomeh Raoufi1, Seyed Amir Ahmad Safavi Naini2, Zahra Azizan2, Fatemeh Jafar Zade2, Fatemeh Shojaeian2, Masoud Ghanbari Boroujeni2, Farzaneh Robatjazi3, Mehrdad Haghighi4, Ali Arhami Dolatabadi5, Hossein Soleimantabar1, Simindokht Shoaee4, Hamidreza Hatamabadi5∗ 1. Department of Radiology, School of Medicine, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Imam Hossein Clinical Research Development Center, Imam Hossein Hospital, Shahid Beheshti university of Medical Science, Tehran, Iran. 3. Department of Radiology, School of Medicine, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 4. Department of Infectious Diseases, Imam Hossein Teaching and Medical Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. Department of Emergency Medicine, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Received: May 2020; Accepted: May 2020; Published online: 14 May 2020 Abstract: Introduction: Predicting the outcomes of COVID-19 cases using different clinical, laboratory, and imaging pa- rameters is one of the most interesting fields of research in this regard. This study aimed to evaluate the correla- tion between chest computed tomography (CT) scan findings and outcomes of COVID-19 cases. Methods: This cross sectional study was carried out on confirmed COVID-19 cases with clinical manifestations and chest CT scan findings based on Iran’s National Guidelines for defining COVID-19. Baseline and chest CT scan character- istics of patients were investigated and their correlation with mortality was analyzed and reported using SPSS 21.0. Results: 380 patients with the mean age of 53.62 ± 16.66 years were evaluated (66.1% male). The most frequent chest CT scan abnormalities were in peripheral (86.6%) and peribronchovascular interstitium (34.6%), with ground glass pattern (54.1%), and round (53.6%) or linear (46.7%) shape. There was a significant correlation between shape of abnormalities (p = 0.003), CT scan Severity Score (CTSS) (p <0.0001), and pulmonary artery CT diameter (p = 0. 01) with mortality. The mean CTSS of non-survived cases was significantly higher (13.68 ± 4.59 versus 8.72 ± 4.42; <0.0001). The area under the receiver operating characteristic (ROC) curve of CTSS in predicting the patients’ mortality was 0.800 (95% CI: 0.716-0.884). The best cut off point of chest CTSS in this regard was 12 with 75.82% (95% CI: 56.07%-88.98%) sensitivity and 75.78% (95% CI: 70.88%-80.10%) specificity. The mean main pulmonary artery diameter in patients with CTSS ≥ 12 was higher than cases with CTSS < 12 (27.89 ± 3.73 vs 26.24 ± 3.14 mm; p < 0.0001). Conclusion: Based on the results of the present study it seems that there is a significant correlation between chest CT scan characteristics and mortality of COVID-19 cases. Patients with lower CTSS, lower pulmonary artery CT diameter, and round shape opacity had lower mortality. Keywords: Tomography scanners, x-ray computed; epidemiology; COVID-19; severe acute respiratory syndrome coron- avirus 2; mortality; prognosis; patient outcome assessment Cite this article as: Raoufi M, Safavi Naini S A A, Azizan Z, Jafar Zade F, Shojaeian F, Ghanbari Boroujeni M, Robatjazi F, Haghighi M, Arhami Dolatabadi A, Soleimantabar H, Shoaee S, Hatamabadi H. Correlation between Chest Computed Tomography Scan Findings and Mortality of COVID-19 Cases; a Cross sectional Study. Arch Acad Emerg Med. 2020; 8(1): e57. ∗Corresponding Author: Hamidreza Hatamabadi; Department of Emergency Medicine, Imam Hossein Hospital, Shahid Madani Avenue, Imam Hossein Square, Tehran 1617763141, Iran. Tel: +98 2173432380 Fax: +98 2177557069, Email: hhatamabadi@yahoo.com. 1. Introduction Corona Virus Disease 2019 (COVID-19), was declared to be a global health emergency by the World Health Organiza- tion (WHO) on January 30th, 2020. It is necessary to rec- ognize predictors of poor prognosis based on clinical man- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem M. Raouf et al. 2 ifestations, laboratory tests, and radiologic patterns of lung involvement to properly deal with patients suspected to have COVID-19 (1). Analyses have introduced comorbidities such as Chronic Obstructive Pulmonary Disease (COPD), di- abetes, hypertension and malignancy, high Sequential Organ Failure Assessment (SOFA) score, and higher levels of Ery- throcyte Sedimentation Rate (ESR), d-dimer, albumin and IL- 6 as poor prognostic factors, especially in older males (2-5). Although RT-PCR has become a standard test for detecting patients, some studies have reported that clinical and radi- ological investigation could be used as an easier and more readily available way to detect patients, especially since it takes less time and has a lower cost compared to RT-PCR (6- 9). With the passage of time from the onset of the symp- toms, chest computed tomography (CT) scan findings be- come more frequent. The chest CT findings include consoli- dation, linear opacities, crazy-paving pattern, and the reverse halo with ground glass opacification being the predominant pattern (9-12). The chest CT scan Severity Score (CTSS) was suggested as a quick means to evaluate the severity of pul- monary involvement with an optimal threshold of 19.5 out of 40 (13). CT scan features were indicated to be helpful in evaluation of the severity and extent of the disease (14) as well as monitor- ing the clinical course (15). Consolidation, linear opacities, crazy-paving pattern, and bronchial wall thickening were re- ported to be significantly higher in severe/critical patients, who also had higher CT scores and more extra-pulmonary lesions (16). It is worth noting that many prediction mod- els were presented in the academic literature and the most frequently reported predictors of prognosis included CT scan features (17). Furthermore, pulmonary indication value was reported to be significantly correlated with the main clinical symptoms and laboratory results (18). Based on the above- mentioned facts, this study aimed to evaluate the correlation between chest CT scan findings and outcome of COVID-19 cases. 2. Methods 2.1. Study design and setting This retrospective single-center cross sectional study was carried out on COVID-19 patients diagnosed with clini- cal manifestations and chest CT scans based on Iran’s Na- tional Guidelines. These patients were admitted to the emergency department (ED) of Imam Hossein Hospital, Tehran, Iran, from February 22th 2020, until March 22th 2020. The Ethics Committee of Shahid Beheshti Univer- sity of Medical Science approved the study (Ethics ID: IR.SBMU.RETECH.REC.1399.003). Informed consent was obtained from all those who were enrolled and confidential- ity of patients’ data was maintained. Figure 1: Area under the receiver operating characteristic (ROC) curve of chest computed tomography severity score in predicting COVID-19 mortality. 2.2. Participants Cases with suspected COVID-19 based on Iran’s national guidelines for defining COVID-19, whose chest CT scan find- ings were strongly in favor of COVID-19, were enrolled in the study. Based on this definition, patients with acute respi- ratory infection who do not positively respond to the usual pneumonia treatment or who have had recent travel history to China as well as patients having respiratory symptoms with any severity, who have had physical contact with an in- dividual diagnosed with or suspected to have COVID-19 were considered suspected cases for COVID-19. Definite diagnosis of the patients was based on chest CT scan and RT-PCR (for admitted cases). Patients were excluded if they had a normal chest CT scan upon arrival to ED, two negative RT-PCRs, or declined to participate in the study. 2.3. Data gathering Using a predesigned checklist, demographic data (age, gen- der), underlying disease (diabetes mellitus, cardiovascular disease, smoking, kidney disease, asthma, respiratory dis- eases other than asthma, malignancy, hematologic disor- ders, rheumatologic disorders, neurologic disorders, use of steroids, hypertension), symptoms (fever, dyspnea, myalgia, headache, nausea, vomiting, chest pain, and etc.), vital signs, laboratory findings and outcome were collected for all cases. In addition, the chest CT scan findings, which were reported by an expert radiologist who was completely blind to clinical and laboratory findings, were recorded for all cases. Low dose lung CT scans were performed for all patients using a 16 detector CT scanner (SIEMENS; Emotion; SOMATOM) with patients in a supine position; other CT parameters were kvp: 100; mAs: 50-100; pitch:1.5; thickness: 4mm. The win- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2020; 8(1): e57 dow was set as mediastinal (window level, 50 HU; window width, 400 HU) and lung (window level, -400 to - 700 HU; window width, 1200±1500 HU). Patients were instructed to hold their breath in order to minimize motion artifacts. An expert attending radiologist (with 10 years of experience), reviewed the chest CT scans of the patients for involvement and severity of each lobe, pattern of involvement (such as ground glass, consolidation, crazy paving and reverse halo), form of parenchymal involvement (such as round opacity, linear opacity and no specific form), distribution of lung ab- normalities (peripheral, peribronchovascular and peri-hilar), associated findings (such as pleural effusion, pericardial effu- sion, mediastinal and hilar significant adenopathy and pul- monary solid nodules), severity of involvement (based on CTSS), and pulmonary artery diameter (including main pul- monary trunk (MPA), right and left pulmonary arteries (RPA and LPA)). The widest short-axis diameter of the main, right and left pulmonary artery were measured on the transverse section at the level of bifurcation of pulmonary artery trunk. CTSS, a semi-quantitative scoring, was used to estimate the severity of lung parenchymal involvement. Each of the 5 lung lobes were visually scored from 0 to 5 as: 0) no involvement; 1) < 5% involvment, 2) 5-25% involvement, 3) 26-49% in- volvement 4) 50-75% involvement, and 5) >75% involvement. The total CTSS was the sum of the individual lobar scores and ranged from 0 (no involvement) to 25 (maximum involve- ment). This scoring system was acquired from Fenj Pan and Tianhe Ye study (19). Five medical students were responsible for data gathering under the direct supervision of an emer- gency medicine specialist. Medical information of the pa- tients was collected from their electronic hospital records. 2.4. Statistical Analysis Analyses were performed using SPSS 21.0. The findings were presented as mean ± standard deviation or frequency (%). Student t-test, chi-square, and Fisher’s exact test were used for comparisons. Significance level was considered as p <0.05. Receiver Operating Characteristic (ROC) curve was used for finding the best cut off point of total chest CTSS in predicting the patients with higher risk of mortality. 3. Results 3.1. Baseline characteristics of studied cases Three hundred eighty patients with the mean age of 53.62 ± 16.66 (18 âĂŞ 97) years were evaluated (66.1% male). Dia- betes mellitus (22.81%), cardiovascular disease (13.2%), and hypertension (12.1%) were among the most frequent comor- bidities among the patients. The most frequent presenting clinical symptoms were cough (60.3%), fever (55.8%), and dyspnea (48.2%), respectively. 154 (53.8%) cases were admit- ted to the hospital and 133 (46.2%) patients were discharged and managed at home. The total and in-hospital mortal- ity rates during the 2-week follow up were 7.6% (29 from 380 cases) and 14.2% (22 from 154 cases) in this series, re- spectively. Tables 1 and 2 compare the baseline character- istics and laboratory parameters between survived and non- survived cases. 3.2. Chest CT scan findings The most frequent chest CT scan abnormalities were in peripheral (86.6%) and peribronchovascular interstitium (34.6%), with ground glass pattern (54.1%), and round (53.6%) or linear (46.7%) shape. The time between onset of initial symptoms and performing chest CT scan was less than 4 days in 30.8% (early stage), 4 - 6 days in 35.8% (intermediate stage), and more than 6 days in 33.3% (late stage) of patients. Stage of disease had no correlation with pattern of chest CT scan involvement (p= 0.692). There was a significant corre- lation between stage of disease and CTSS (p= 0.008). Table 3 compares the chest CT scan characteristics of cases between survived and non-survived cases. There was a significant cor- relation between shape of abnormalities (p = 0.003), CTSS (p <0.0001), and pulmonary artery CT diameter (p = 0. 01) with mortality. 3.3. Correlation of CTSS and mortality The mean CTSS of non-survived cases was significantly higher (13.68 ± 4.59 versus 8.72 ± 4.42; <0.0001). The area under the ROC curve of CTSS in predicting the patients’ mor- tality was 0.800 (95% CI: 0.716-0.884; figure 1). The best cut off point of chest CTSS in this regard was 12 with 75.82% (95% CI: 56.07%-88.98%) sensitivity and 75.78% (95% CI: 70.88%- 80.10%) specificity. 3.4. Correlation of pulmonary artery diameter and CTSS The mean main pulmonary artery diameter in patients with CTSS ≥ 12 was higher than cases with CTSS < 12 (27.89 ± 3.73 vs 26.24 ± 3.14 mm; p < 0.0001). The mean right pulmonary artery diameter was significantly higher in cases with higher CTSS of right middle (p= 0.045) and right lower (p < 0.0001) lobes of the lung. In addition, the mean left pulmonary artery diameter was significantly higher in cases with higher CTSS of left upper (p= 0.006) and left lower (p < 0.002) lobes of the lung. 4. Discussion Based on the results of the present study, it seems that there is a significant correlation between chest CT scan character- istics and mortality of COVID-19 cases. Patients with lower CTSS, lower pulmonary artery CT diameter, and round shape opacity had lower mortality. Ground Glass Opacity (GGO) This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem M. Raouf et al. 4 Table 1: Comparing the baseline characteristics of COVID-19 patients between survived and non-survived cases Variables Total (n=380) Survived (n=351) Died (n=29) P value Gender Female 129 (66.1) 122 (94.6) 7 (5.4) 0.246 Male 251 (33.9) 229 (91.2) 22 (8.8) Age (year) Mean ± SD 53.57 ± 16.66 52.85 ± 16.35 63.60 ± 17.68 0.002 Comorbid disease Yes 118 (40.8) 106 (89.8) 12 (10.2) 0.949 No 171 (59.2) 154 (90.1) 17 (9.9) Presenting vital sign Temperature (c) 37.34 ± 1.04 37.29 ± 1.00 37.94 ± 1.39 0.104 Systolic BP (mmHg) 118.21 ± 11.61 118.40 ± 11.6 115.00 ± 12.90 0.572 Respiratory rate (/min) 18.80 ± 4.32 18.36 ± 3.62 26.67 ± 8.62 0.001 Heart rate (/min) 89.99 ± 14.50 88.92 ± 13.30 103 ± 22.81 0.016 Saturation O2 (%) 93.43 ± 6.11 93.82 ± 5.88 87.13 ± 6.72 0.002 Clinical manifestations Fever 212 (55.8) 193 (72.0) 19 (65.5) 0.642 Cough 229 (60.3) 209 (77.1) 20 (74.1) 0.720 Dyspnea 183 (48.2) 163 (62.0) 20 (69.0) 0.460 Myalgia 182 (47.9) 168 (63.2) 14 (51.9) 0.249 Headache 128 (33.7) 121 (45.1) 7 (26.9) 0.074 Chest pain 77 (20.3) 68 (26.1) 9 (34.6) 0.347 Nausea or vomiting 98 (25.8) 88 (33.5) 10 (37.0) 0.708 Disposition Hospital admission 140 (48.6) 124 (47.0) 16 (66.7) ICU admission 14 (5.2) 9 (3.4) 6 (25.0) < 0.001 Home admission 133 (46.2) 131 (49.6) 2 (8.3) Data are presented as mean ± standard deviation (SD) or frequency (%). BP: blood pressure; ICU: intensive care unit. and consolidation were the most frequent chest CT scan findings, which was consistent with other studies (20, 21). The most common location of abnormalities was peripheral, followed by peribronchovascular interstitium. Lower zone involvement was observed more than upper zone, which was consistent with findings of other studies (2, 22). In order to evaluate the severity of lung involvement via CT, we used lo- bar severity score, which was significantly higher in deceased patients, in comparison with survived group, like Chen et al. and Yuan et al. studies (2, 21). An investigation on 121 patients carried out by Bernheim et al. revealed that the longer since the onset of symptoms, CT findings became more prominent (9). Similar to this study, our assessment has demonstrated that patients that presented at earlier stages had lower CTSS. Radiological pat- terns did not correlate with stage of the disease, which was in contrast to other studies (9, 19). The best cut off of chest CT score in predicting mortality in the present study was 12 out of 25, with acceptable sensitivity and specificity of 75.82% and 75.78%, respectively. However, Yang et al. used a different system, scoring 20 pulmonary regions in range of 0-2 with the best cut off point of 19 out of 40 with 94% specificity and 83% sensitivity (2). Consid- ering shapes of CT scan abnormalities, round opacities cor- related with better prognosis. To explain better prognosis of round opacities, more investigation is needed to under- stand whether this is due to early medical treatment or pos- sible low viral load of the patients as discussed by JSM Peiris et al. for SARS (19, 23). Hani et al. demonstrated that CT scan patterns of COVID-19 patients could transform to orga- nizing pneumonia and lung fibrosis as a sequela in advanced phases, which has also been concluded in other studies (24, 25). Therefore, for future follow up of pulmonary artery hy- pertension secondary to lung injury, we measured MPA, RPA, and LPA diameters as a baseline. Although mean Pulmonary Artery Diameters (PAD) in survived and non-survived group was not beyond the normal range, the differences between them were statically significant. Therefore, it could be used to predict patient prognosis. It is worth noting that the small differences between mean PAD of groups (about 2 millime- ters), could raise concerns for operator dependent errors. Although PAD increase, an indicator of pulmonary hyper- tension secondary to lung fibrosis, is expected in long term, acute rise of PAD could occur due to lung injury. As men- tioned before, patients whose diseases progressed to acute respiratory distress syndrome, showed dilation of pulmonary arteries in days (26). This research was carried out to explore chest CT scan pre- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2020; 8(1): e57 Table 2: Comparing the laboratory findings of COVID-19 patients between survived and non-survived cases Characteristics Survived (n=351) Died (n=29) P value Complete blood count WBC (109 /L) 6.90 ± 3.96 11.46 ± 7.96 < 0.0001 Hemoglobin (g/dl) 13.14± 1.91 12.85 ± 2.09 0.285 Hematocrit (%) 39.03 ± 5.13 38.21 ± 5.49 0.401 Platelet (109 /L) 195.15 ± 83.13 183.50 ± 62.60 0.487 Lymphocyte (%) 22.66 ± 11.37 11.42 ± 5.59 < 0.0001 Neutrophil (%) 69.81 ± 12.76 82.58 ± 6.55 < 0.0001 Blood gas analysis pH 7.43 ± 0.09 7.38 ± 0.17 0.038 PO2 (mm Hg) 34.50 ± 18.57 36.33 ± 24.96 0.654 PCO2 (mm Hg) 41.99 ± 10.76 37.32. ± 11.75 0.053 HCO3 (mEq/L) 27.01. ± 7.10 23.38 ± 7.01 0.016 Coagulation profile PT (s) 12.73 ± 3.17 15.07 ± 3.82 0.010 PTT (s) 28.27 ± 9.91 29.82 ± 5.32 0.526 INR (IU) 2.33 ± 10.57 1.35 ± 0.38 0.696 Liver enzymes AST (U/L) 64.38 ± 234.43 104.56 ± 117.76 0.533 ALT (U/L) 58.09 ± 208.98 63.78 ± 47.53 0.926 Kidney enzyme Urea ( mg/dL) 42.78 ± 33.42 66.81 ± 53.83 0.001 Creatinine (mg/dL) 1.97 ± 9.32 1.69 ± 0.95 0.877 Others Sodium (mEq/L) 137.43 ± 4.00 136.26 ± 7.13 0.187 Potassium (mEq/L) 3.97 ± 0.61 4.09 ± 0.79 0.325 Calcium (mg/dL) 8.23 ± 1.20 7.90 ± 0.82 0.314 Magnesium (mg/dL) 2.20 ± 1.50 2.09 ± 0.42 0.774 ESR (mm/hr) 49.56 ± 26.30 54.21 ± 31.03 0.486 CRP (mg/L) 46.47 ± 42.77 89.89 ± 68.71 < 0.0001 CPK (U/L) 216.38 ± 474.51 1033.45 ± 1754.19 < 0.0001 Blood sugar(mg/dL) 154.48 ± 71.49 159.54 ± 85.21 0.816 Data are presented as mean ± standard deviation. WBC: white blood cell; PT: prothrombin time; PTT: partial thromboplastin time; INR: international normalized ratio; AST: aspartate aminotransferase; ALT: alanine aminotransferase; ESR: erythrocyte sedimentation rate; CRP: C-reactive protein; CPK: creatinine phosphokinase. dictors of prognosis in COVID-19 patients. We found out that radiologic features, especially CT scan severity score, can be helpful in management of patients, along with clinical mani- festations. Moreover, we found that pulmonary artery diam- eter correlated with CT scan severity score and prognosis, al- though more investigations are needed. 5. Limitation Lack of RT-PCR in patients managed in an out-of-hospital setting, recall bias of patients during phone interviews, inter- pretation of CT scan images by only one person, differences between Iran’s National Guideline for COVID-19 and guide- lines of other countries, in addition to usual limitations of cross sectional studies, were among the most important lim- itations of this study. 6. Conclusion Based on the results of the present study it seems that there is a significant correlation between chest CT scan character- istics and mortality of COVID-19 cases. Patients with lower CTSS, lower pulmonary artery CT diameter, and round shape opacity had lower mortality. 7. Declarations 7.1. Acknowledgements The authors would like to acknowledge all the self-giving healthcare workers and appreciate the serenity of people. The assistance provided by Iman Nilforushan and Hossein- Ali Safavi-Naeini for English editing is much appreciated. 7.2. Author contribution All authors met the criteria for authorship contribution based on recommendations of international committee of medi- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem M. Raouf et al. 6 Table 3: Comparing the chest computed tomography (CT) scan findings of COVID-19 patients between survived and non-survived cases Characteristics Survived (n=351) Died (n=29) P value Location Peripheral 304 (86.6) 25 (88.2) 1.000 Peribronchovascular 122 (34.8) 10 (34.5) 0.976 Perihilar 1 (0.3) 0 (0.0) 1.000 Upper zone 23 (6.6) 0 (0.0) 0.240 Lower zone 60 (17.1) 5 (17.2) 0.984 Upper and lower zone 87 (24.8) 8 (27.6) 0.738 Presentation Ground glass 190 (54.1) 15 (51.4) 0.996 Consolidation 104 (29.6) 9 (31.0) Shape Round opacity 188 (53.6) 6 (20.7) 0.003 Linear opacity 150 (42.7) 15 (51.7) 0.348 Non specified 20 (5.7) 5 (17.2) 0.016 Crazy paving 11 (3.1) 3 (10.3) 0.082 Lobar CTSS Right upper lobe 1.71 ± 0.78 2.25 ± 0.96 0.001 Right middle lobe 2.02 ± 0.82 2.71 ± 0.93 < 0.0001 Right lower lobe 2.45 ± 0.86 3.25 ± 0.79 < 0.0001 Left Upper lobe 2.15 ± 0.86 3.76 ± 1.14 0.001 Left lower lobe 2.31 ± 0.89 3.21 1.13 < 0.0001 Total CTSS Mean ± SD 8.72 ± 4.42 13.68 ± 4.59 <0.0001 PA diameter (mm) Main 26.54 ± 3.29 28.93 ± 3.99 <0.0001 Right 17.84 ± 3.23 19.61 ± 4.11 0.007 Left 17.61 ± 2.86 19.61 ± 2.58 <0.0001 Data are presented as mean ± standard deviation (SD) or frequency (%). CTSS: Computed tomography severity score. PA: pulmonary artery. cal journal editors. M.R and H.H conceived the presented idea. H.H. and M.R. and S.A.S. and F.Sh and M.G. wrote the manuscript. H.H and M.R. and E.F. conceived the study and were in charge of overall direction and planning with the help of S.A.S. Z.A. and F.J. and S.A.S and F.Sh and M.G collected the data through Hospital information system and calling the pa- tients. M.R. and F.R examined radiology. Z.A. and F.J. filled out the radiologic forms. All authors discussed the results and commented on the manuscript. Authors ORCIDs Masoomeh Raoufi: 0000-0001-7269-1822 Seyed Amir Ahmad Safavi Naini: 0000-0001-9295-9283 Zahra Azizan: 0000-0002-2872-3599 Fatemeh Jafar Zade: 0000-0001-5367-4859 Fatemeh Shojaeian: 0000-0001-5972-9953 Masoud Ghanbari Boroujeni: 0000-0002-6220-2797 Farzaneh Robatjazi: 0000-0003-0651-0397 Mehrdad Haghighi: 0000-0003-3139-3225 Ali Arhami Dolatabadi: 0000-0001-9492-9520 Hossein Soleimantabar: 0000-0003-3329-0406 Simindokht shoaee: 0000-0003-3127-4875 7.3. Funding/Support This research was supported by grants from Vice chancellor of research and technology of Shahid Beheshti University of Medical Science (Grant number: 22973). 7.4. Conflict of interest The authors disclose that they have no competing interests. References 1. Huang H, Cai S, Li Y, Li Y, Fan Y, Li L, et al. Prognostic factors for COVID-19 pneumonia progression to severe symptom based on the earlier clinical features: a retro- spective analysis. medRxiv. 2020. 2. 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