• Users Online: 212
  • Print this page
  • Email this page

 Table of Contents  
Year : 2021  |  Volume : 8  |  Issue : 1  |  Page : 9-16

Correlation between thorax computed tomography findings and clinical and laboratory data on patients with coronavirus disease 2019

1 Department of Radiology, Yozgat City Hospital, Yozgat, Turkey
2 Department of Thoracic Diseases, Yozgat City Hospital, Yozgat, Turkey

Date of Submission10-Nov-2020
Date of Acceptance20-Mar-2021
Date of Web Publication18-Nov-2021

Correspondence Address:
Dr. Ruken Ergenc
Department of Radiology, Yozgat City Hospital, Yozgat
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/RID.RID_2_21

Rights and Permissions

OBJECTIVE: We investigated the correlation between computed tomography (CT) scores, laboratory findings, and clinical symptoms in patients with coronavirus disease 2019 (COVID-19).
MATERIALS AND METHODS: Clinical, laboratory, and thorax CT findings on the admission of 121 patients with COVID-19 were retrospectively evaluated. CT scores based on lobe involvement and CT patterns (i.e., ground-glass abnormalities, consolidation, and crazy-paving patterns) were estimated, and the relationship between CT score and symptomatic (e.g. fever, cough) versus asymptomatic (e.g., inflammation, coagulation, liver and kidney function) clinical laboratory findings were statistically analyzed.
RESULTS: Sixty-eight of 121 patients (56%) were symptomatic; 53 (44%) were asymptomatic. The CT scores of symptomatic patients, especially those with coughing and dyspnea, were statistically higher (2 [0–9] vs. 0 [0–1]; P < 0.001). Erythrocyte sedimentation rate, C-reactive protein, ferritin, D-dimer, fibrinogen, aspartate aminotransferase, lactate dehydrogenase, glucose, prothrombin time and alanine amino transferase values were correlated with CT scores (ρ = 0.638, P < 0.001, ρ = 0.512, P < 0.001; ρ = 0.325, P = 0.001; ρ = 0.452, P < 0.001; ρ = 0.525, P < 0.001; ρ = 0.379, P < 0.001; ρ = 0.445, P < 0.001; ρ = 0.332, P < 0.001, ρ = 0.296, P = 0.003; ρ = 0.222, P = 0.015, respectively). Albumin values were negatively correlated with CT scores (ρ = −0.398, P < 0.001).
CONCLUSION: CT scores may help clinicians evaluate the severity of COVID-19 pneumonia and thus help in managing the disease.

Keywords: Computed tomography score, coronavirus disease 2019 pneumonia, laboratory findings, thorax computed tomography

How to cite this article:
Ergenc R, Okray DG, Mutlu U, Tanyeri A, Şahin MN. Correlation between thorax computed tomography findings and clinical and laboratory data on patients with coronavirus disease 2019. Radiol Infect Dis 2021;8:9-16

How to cite this URL:
Ergenc R, Okray DG, Mutlu U, Tanyeri A, Şahin MN. Correlation between thorax computed tomography findings and clinical and laboratory data on patients with coronavirus disease 2019. Radiol Infect Dis [serial online] 2021 [cited 2022 Dec 4];8:9-16. Available from: http://www.ridiseases.org/text.asp?2021/8/1/9/330563

  Introduction Top

In December 2019, several pneumonia cases with unknown causes were reported in Wuhan, China, and a new coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was isolated from lower respiratory tract samples from these patients and described as pathogenic in February 2020.[1],[2] Since March 11, 2020, the World Health Organization declared coronavirus disease 2019 (COVID-19) to be a pandemic.

COVID-19 is highly contagious and is transmitted through respiratory droplets and close contact.[3] The most common symptoms are fever, coughing, dyspnea, fatigue, anorexia, and myalgia. Although COVID-19 causes mild symptoms with a good prognosis in most patients, it occasionally leads to acute respiratory distress syndrome, multiorgan deficiency and death.[4],[5]

Real-time reverse transcription-polymerase chain reaction (RT-PCR) is the gold standard method for diagnosing COVID-19.[6] However, thorax computed tomography (CT) is performed as a complementary diagnostic tool to RT-PCR for diagnosing COVID-19 pneumonia.[7] Thorax CT is important for timely diagnosing and isolation of patients with COVID-19 and in managing the outbreak, especially for patients with false-negative PCR results or without obvious symptoms.[8] Thorax CT is an effective, accessible, fast, and simple method that can help diagnose, treat, and assess disease progression and treatment response in patients with COVID-19 pneumonia.[9],[10]

The most common thorax CT findings are multilobar, peripheral, bilateral ground-glass opacity (GGO), especially in the lower lobes. GGO is commonly isolated and infrequently exhibits reticular/interlobular septal thickening (crazy-paving patterns) or consolidations.[11],[12] Francone et al. showed that CT results may be correlated with the laboratory and clinical findings of patients with COVID-19. CT scores may aid in clinically classifying patients with COVID-19 and estimating their short-term outcomes.[13] Zhang et al. showed that CT scores of patients in the progressive stage may be correlated with laboratory parameters, including neutrophil counts, white blood cell (WBC) counts, C-reactive protein (CRP), procalcitonin and lactate dehydrogenase (LDH).[14] Another study showed that CRP, erythrocyte sedimentation rate (ESR), and granulocyte/lymphocyte ratio were positively correlated with the severity of CT findings.[15]

This study was conducted to define the CT findings of patients with COVID-19 pneumonia confirmed via RT-PCR and investigate the correlation between CT score, laboratory findings, and clinical symptoms.

  Materials and Methods Top


The Turkey Ministry of Health and Ethics Commission of Bozok University Hospital (2017-KAEK-189_2020.06.23_19) approved this study. We assessed 124 patients diagnosed with COVID-19 between March 15, 2020, and June 1, 2020, in our hospital. Inclusion criteria were (1) patients with confirmed COVID-19 with positive RT-PCR results and (2) patients who underwent thorax CT imaging and laboratory examinations on their first day of hospitalization. Medical histories and physical examination findings of these patients were recorded. Exclusion criteria were (1) patients with severe artifacts on their CT scan, (2) patients without laboratory examinations, and (3) patients without RT-PCR-confirmed COVID-19. One patient was excluded because their first CT examination was taken at another hospital. Two other patients were excluded because they lacked evaluable and qualified CT images.

Clinical and laboratory parameters

Laboratory tests involved hemograms (i.e., hemoglobin, WBC, neutrophil, lymphocyte, thrombocyte, and monocyte counts), inflammatory markers (i.e., CRP, ESR, and procalcitonin), ferritin, liver function parameters (i.e., alanine aminotransferase [ALT], aspartate aminotransferase [AST], lactate dehydrogenase [LDH], total bilirubin, and albumin), kidney function parameters (i.e., creatinine and urea), creatine kinase (CK) and CK-Muscle/Brain (CK-MB), blood glucose level, and coagulation parameters (i.e., D-dimer, prothrombin time [PT], activated partial thromboplastin time [APTT], and fibrinogen). Some patients lacked these laboratory results. Body temperature, respiratory/heart rates and saturation levels, and systolic and diastolic blood pressure were also evaluated as vital signs.

Blood glucose levels in patients with diabetes mellitus (17 patients), liver function parameters in patients with liver failure (2 patients), and renal functional tests in patients with renal failure (13 patients) were excluded because these diseases could affect patients' laboratory results.

Computed tomography protocols and evaluation

Thorax CT images were taken using 16-and 128-MDCT scanners (Siemens Somatom Scope 16 and Perspective 128; Siemens Healthineers, Forchheim, Germany). Scans were conducted from the apex to the base of the lung. Images were acquired with a single breath-hold. The scan parameters used were tube voltage: 120 kV, tube current: 70–168 mAs, pitch: 0.8–1.2 mm, slice thickness: 1.5 mm, matrix: 512 × 512, FOV: 55 × 35 cm, and axial reconstruction image layer thickness: 1–1.5 mm. No contrast agent was used. All images were assessed using a picture archiving and communication system (Syngo. Via).

Only patients' first thorax CT was evaluated. Follow-up CT images were not assessed. We used the CT scoring criteria published by Huang et al. in March 2020.[16] The base CT score was determined according to the extent of the GGO and consolidation in the lobes and defined as follows: 0: No involvement; 1: <5% involvement; 2: 5%–25% involvement; 3: 26%–49% involvement; 4: 50%–75% involvement; and 5: >75% involvement. If crazy-paving patterns were seen in a lobe, the base CT score was increased by 1; if consolidation appeared (either with or without a crazy-paving pattern), the base CT score was increased by 2. The maximum possible CT score for each lobe was 7. Total CT scores ranged from 0 to 35. [Figure 1] and [Figure 2] show sample images from our patients. Two radiologists with 5 and 16 years of experience each evaluated the patients' CT images. Final CT scores were assigned by consensus.
Figure 1: (a-d) Noncontrast chest computed tomography images of a 52-year old man who presented with fever and cough. computed tomography scans show multiple ground-glass opacities and consolidations in multiple lung segments with predominantly peripheral distribution, the computed tomography score is 22

Click here to view
Figure 2: (a-f) Non-contrast chest computed tomography images of a 62-year-old man who presented with fever. computed tomography scans show multiple ground-glass opacities and crazy paving pattern in multiple lung segments, the computed tomography score is 12

Click here to view

Statistical analysis

Statistical analysis was performed using SPSS (version 17.0; SPSS Inc., Chicago, IL, USA). Continuous data with a normal distribution are expressed as the mean ± standard deviation; noncontinuous data are expressed as the median (range). Student's t-test and the Mann–Whitney U test were used to compare the laboratory examination data and vital signs of patients with and without COVID-19-associated CT findings. Spearman analysis was performed to evaluate the correlation between patients' CT scores and laboratory results. Correlation coefficients (ρ) were as follows: 0–0.3: No/poor correlation; 0.3–0.6: Moderate; 0.6–0.75: Good; and 0.75: Strong. P < 0.05 was considered statistically significant.

  Results Top

Patients' demographic data

We evaluated 121 patients with positive RT-PCR test results (86 male patients, 35 female patients). The age range was 1–91 years. The mean age of the male patients was 42.5 ± 18.2 years; the mean age of the female patients was 48.7 ± 20.9 years. CT scores did not statistically differ between the male and female patients. Age was positively correlated with CT scores (ρ = 0.304, P = 0.001). [Table 1] shows the patients' demographics, comorbidities, and clinical manifestations.
Table 1: Demographic, comorbidities and clinical characteristics of patients

Click here to view

Lung involvement patterns

Of the 121 patients, 62 (51%) had COVID-19-associated pneumonia on thorax CT; 59 (49%) lacked obvious CT findings. The most common CT abnormalities were multifocal GGO (40/62; 65%), consolidation (22/62; 35%), focal GGO (12/62; 19%) and crazy-paving patterns (5/62; 8%). Distributions on the CT findings were predominantly peripheric (48/62; 77%), less commonly diffuse (9/62; 15%), and central (5/62; 8%). The involved lungs were bilateral (33/62; 53%), right (18/62; 29%), and left (11/62; 18%). Of the patients, 48% had single lobe involvement; 55% had 2 or more lobes involved [Table 2].
Table 2: Computed tomography features of 121 patients with coronavirus disease 2019 at admission

Click here to view

Correlation between laboratory data and computed tomography scores

Most patients had normal WBC (98/121;81%), neutrophil (106/121;88%), lymphocyte (77/121;64%), CRP (70/117; 60%), ALT (109/121;90%), AST (110/121;91%), LDH (82/118;69%), albumin (96/118;81%), ESR (32/56;57%), ferritin (65/98;66%), D-dimer (77/118;65%), fibrinogen (73/99;74%), and PT (91/99;92%) values.

ALT, AST, and LDH values of patients who had positive CT findings were statistically higher than the values of those who did not (24 [15–40] vs. 19 [12–26], P = 0.017; 29 [24–38] vs. 22 [18–28], P = 0.001; 241 [183–342] vs. 188 [161–214], P < 0.001, respectively). Patients with positive CT findings had lower albumin levels (4 [3.5–4.3] vs. 4.27 [4–4.49] P < 0.001). Blood glucose levels of CT-positive patients were statistically higher (107 [95–135] vs. 96 [90–104], P = 0.009).

Values of the inflammatory markers, CRP and ESR, were also higher in patients with consolidation and/or GGO on CT images (0.88 [0.38–9.47] vs. 0.24 [0.15–0.91], P < 0.001; 35 [17–46] vs. 6 [2.5–26.5], P < 0.001, respectively]. Similarly, ferritin, an acute-phase reactant, was higher in patients with positive CT findings (109.5 [42.9–294] vs. 56.5 [32.4–106], P = 0.011).

D-dimer and fibrinogen levels were significantly higher in COVİD-19 patients with positive CT findings than in those without positive CT findings (604 [291–1223] vs. 298 [203–455], P < 0.001; 356 [280–472] vs. 247 [210–303], P < 0.001, respectively). These patients also had less PT elongation than did those without obvious CT findings (12.75 [12–13.7] vs. 12.2 [11.8–12.7], P = 0.038).

WBC, neutrophil, lymphocyte, thrombocyte, and monocyte counts; hemoglobin levels; and renal function, CK, CK-MB, procalcitonin, and APTT values did not statistically differ between patients with and without positive CT findings. [Table 3] shows the laboratory findings of patients with and without COVID-19 pneumonia.
Table 3: Laboratory findings in patients with and without coronavirus disease 2019 pneumonia

Click here to view

PT and ALT values were poorly correlated with CT scores (ρ = 0.296, P = 0.003; ρ = 0.222, P = 0.015, respectively). CRP, ferritin, D-dimer, fibrinogen, AST, LDH, and glucose values were moderately positively correlated with patients' CT scores (ρ = 0.512, P < 0.001; ρ = 0.325, P = 0.001; ρ = 0.452, P < 0.001; ρ = 0.525, P < 0.001; ρ = 0.379, P < 0.001; ρ = 0.445, P < 0.001; ρ = 0.332, P < 0.001, respectively). Albumin levels were moderately negatively correlated with patients' CT scores (ρ = −0.398, P < 0.001). ESR values were well correlated with patients' CT scores [ρ = 0.638, P < 0.001; [Table 4]].
Table 4: Spearman analysis between computed tomography score and laboratory findings

Click here to view

Correlation between clinical data and computed tomography scores

The median time between patients' symptom onset and CT and laboratory examinations was 3 days (2–7 days). Hospitalization lasted 11.92 ± 5.36 days. CT scores were not correlated with the time from symptom onset to undergoing CT and laboratory examinations. The hospitalization period and CT scores were not correlated. Deceased patients (n = 6) had higher CT scores than did recovered patients (n = 115) (24 [12–30] vs. 0 [0–4], P < 0.001).

Of the 121 patients, 53 were asymptomatic. Coughing (36%), dyspnea (21%), sore throat (9%), and fatigue (7%) were the most frequent symptoms [Table 1]. Symptomatic patients had positive CT findings more frequently did than asymptomatic patients (66.2% vs. 32.1%, P < 0.001). In addition, CT scores of symptomatic patients were statistically higher than those of asymptomatic patients (2 [0–9] vs. 0 [0–1], P < 0.001). Patients with coughing or dyspnea had higher CT scores (3 [0–8] vs. 0 [0–1.25], P = 0.001; 2.5 [0.75–9.75] vs. 0 [0–3], P = 0.004, respectively).

Physical examination findings revealed that saturation levels, respiratory rates, and heart rates differed significantly between patients with and without positive CT findings. However, no other physical examination findings differed statistically between these patients [Table 5].
Table 5: Vital findings in patients with and without coronavirus disease 2019 pneumonia

Click here to view

  Discussion Top

The extent and severity of CT findings for patients with COVID 19 pneumonia were correlated with clinical symptoms and laboratory results. Here, we evaluated this correlation using the CT scoring criteria of Huang et al.[16] We evaluated the first CT and laboratory examinations on patients' first day of hospitalization. CT scores were associated with CRP, ESR, ferritin, D-dimer, fibrinogen, ALT, AST, LDH, and albumin levels.

The median time between the onset of COVID-19-related symptoms and CT/laboratory examinations was 3 days (2–7 days). In contrast to the findings of Wu et al.,[1] we found no correlation between the severity of CT findings and the time from symptom onset to CT examinations. Many patients with COVID-19 pneumonia (44%) were in the early stage without obvious symptoms, which led to laboratory results within the normal limits. Patients with COVID-19 pneumonia had abnormal laboratory values more frequently than did patients without (i.e. ESR: 65%, D-dimer: 48%, LDH: 47%, and fibrinogen: 40%). More patients with pneumonia than without (27%) had lower albumin levels. Similarly, Pan et al. showed that the median time between symptom onset and CT/laboratory examinations was 2 ± 2 days and that most laboratory values for patients with early-stage COVID-19 pneumonia were normal except the CRP, ESR, LDH, and D-dimer values.[17]

In this study, ALT, AST, and LDH values were higher and correlated with CT scores in patients with pneumonia. Zhang et al. found a correlation between CT score and LDH values in patients with progressive-stage COVID-19 pneumonia. CT score was correlated with AST in the early stage and with ALT values in the early, progressive and absorption stages.[14] Cheng et al.[18] found high LDH values in 50% of patients. AST and ALT tests indicate hepatic dysfunction, and high LDH values are associated with cardiac and hepatic injury, reflecting lung tissue injury and destruction in patients with severe pneumonia. These tests help determine whether patients need to stay in the intensive care unit.[19]

D-dimer and fibrinogen values were correlated with CT scores in patients with positive CT findings. Another study associated increased D-dimer and PT elongation with disseminated intravascular coagulopathy (DIC) in deceased patients.[20] Francone et al. determined that the increased D-dimer in patients with critical-severe COVID-19 pneumonia, which is associated with mortality, was correlated with CT score.[13] Zhang et al. also indicated that high CT scores were positively correlated with abnormal blood coagulation and that SARS-CoV-2 might affect the exogenous coagulation pathway.[21]

Here, CRP, ESR, and ferritin values were higher in patients with COVID-19 pneumonia. CRP values were increased in 51% of patients with pneumonia (32/59). One study showed that CRP was positively correlated with CT scores.[1],[13],[14],[15] Tan et al. grouped patients clinically as either mild or severe and radiologically by CT score. They found that CRP and ESR values, which were positively correlated with CT scores, were significantly increased at the early stage in patients with severe COVID-19, although the CT scores did not significantly differ between mild and severe patients. Sensitivity was higher to CRP than to ESR in evaluating clinical conditions. CRP, ESR, and ferritin are markers of inflammation. CRP values significantly increased in the early stage in patients with severe COVID-19 pneumonia and might be a potential prognostic tool for predicting infection severity because CRP values are high in deceased patients.[15],[22] Consistent with our study, Xiong et al. evaluated thorax CTs at the time of hospital admission and found that pneumonia severity on the thorax CTs was positively correlated with ESR, CRP, and LDH values.[23] Velavan et al.[24] found that CRP, D-dimer, and ferritin could be used to predict the severity of COVID-19 pneumonia in hospitalized patients. CT scores show the severity of COVID-19 pneumonia. Abnormalities such as consolidation and GGO may also correlate with diffuse alveolar damage. Patients with widespread consolidation and GGO often have severe systemic inflammation.[21] CRP levels may be correlated with virus-induced cytokine storms and tissue damage.[25],[26]

We found that albumin values were negatively correlated with CT scores. Albumin is a negative acute-phase reactant produced by the liver. Albumin is decreased in patients with severe COVID-19, and some researchers think that it may be associated with mortality.[27],[28] Possible mechanisms of hypoalbuminemia in COVID-19 patients may include hepatocellular injury, intense systemic inflammation, and increased capillary permeability.[28]

Bilateral involvement, peripheral distribution, GGO, and consolidation were more frequent patterns in patients with COVID-19 pneumonia, and the percentages we found were similar to those of other studies.[29],[30] Consistent with Francone et al., we observed that age and CT score were positively correlated.[13] CT scores were higher in deceased patients (6/121; 5%) than in recovered patients. Francone et al. observed an increased mortality risk in patients with higher CT scores.[13]

Physical examination results differed statistically and significantly between patients with and without positive CT findings; however, this difference was likely not clinically significant. Wu et al. found that body temperature was significantly correlated with the severity of the CT findings;[1] however, in our study, we found no such correlation.

In summary, the most important results of our study were the positive correlation between CT scores and liver function tests (ALT and AST), inflammatory markers (CRP, ESR, and ferritin), and coagulation parameters (D-dimer, fibrinogen, and PT time). These parameters may reflect inflammation severity and the risk of DIC. Expectedly, CT scores were higher in deceased patients, who also had higher CRP, ESR, and D-dimer values.

Our study had some limitations. (1) It was a retrospective, single-center study that included a small patient population. (2) We evaluated the thorax CT and laboratory findings only at the time of hospital admission. (3) Some laboratory examinations were missing for some patients. No histopathological samples (lung biopsy or autopsy) were available to confirm COVID-19 infection. (4) We did not regularly obtain follow-up CT images; thus, our study differed from other dynamic studies, and we could not evaluate the association between clinical laboratory progression and CT findings. (5) Our assessment of CT images was visually semiquantitative. Approximately 50% of our patients had no symptoms or CT findings. Normal laboratory findings in patients without symptoms or CT findings may have affected our results.

  Conclusion Top

The COVID-19 pandemic is a rapidly expanding global health crisis. Thorax CT, the most common imaging method for diagnosing COVID-19, is important for early diagnosis and evaluating treatment response and disease progression. CT scoring, whether based on quantitative methods with artificial intelligence or semiquantitative methods, is useful for assessing the severity of COVID-19 pneumonia, which is also correlated with laboratory findings.[13],[15],[21],[31] CT scoring may help decrease mortality by guiding clinicians in management and early treatment of the disease.[21],[31] CT scoring may help manage triage patients who need aggressive treatment or closer monitoring.[21] However, many unknowns remain regarding COVID-19, and more studies are needed.


We would like to thank Traci Raley, MS, ELS, from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing a draft of this manuscript.

Informed consent

Written informed consent was waived due to the retrospective nature of the study.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form the patients have given their consent for their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Wu J, Wu X, Zeng W, Guo D, Fang Z, Chen L. Chest CT findings in patients with corona virus disease 2019 and its relationship with clinical features. Invest Radiol 2020;55:257-61.  Back to cited text no. 1
Cheng Z, Lu Y, Cao Q, Qin L, Pan Z, Yan F, et al. Clinical features and chest CT manifestations of coronavirus disease 2019 (COVID-19) in a single-center study in Shanghai, China. AJR Am J Roentgenol 2020;215:121-6.  Back to cited text no. 2
Yang W, Sirajuddin A, Zhang X, Liu G, Teng Z, Zhao S, et al. The role of imaging in 2019 novel coronavirus pneumonia (COVID-19). Eur Radiol 2020;30:4874-82.  Back to cited text no. 3
Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020;395:507-13.  Back to cited text no. 4
Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, et al. CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology 2020;295:202-7.  Back to cited text no. 5
Li M. Chest CT features and their role in COVID-19. Radıol Infect Dis 2020;7:51-4.  Back to cited text no. 6
Hani C, Trieu NH, Saab I, Dangeard S, Bennani S, Chassagnon G, et al. COVID-19 pneumonia: A review of typical CT findings and differential diagnosis. Diagn Interv Imaging 2020;101:263-8.  Back to cited text no. 7
Ye Z, Zhang Y, Wang Y, Huang Z, Song B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): A pictorial review. Eur Radiol 2020;30:4381-9.  Back to cited text no. 8
Wang M, Guo L, Chen Q, Xia G, Wang B. Typical radiological progression and clinical features of patients with coronavirus disease 2019. Aging (Albany NY) 2020;12:7652-9.  Back to cited text no. 9
Fan L, Li D, Xue H, Zhang L, Liu Z, Zhang B, et al. Progress and prospect on imaging diagnosis of COVID-19. Chin J Acad Radiol 2020;3:4-13.  Back to cited text no. 10
Song F, Shi N, Shan F, Zhang ZY, Shen J, Lu HZ, et al. Emerging 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology 2020;295:210-7.  Back to cited text no. 11
Zhao W, Zhong Z, Xie X, Yu Q, Liu J. Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: A multicenter study. AJR Am J Roentgenol 2020;214:1072-7.  Back to cited text no. 12
Francone M, Lafrate F, Maria Masci G, Coco S, Cilia F, Manganaro L, et al. Chest CT score in COVID-19 patients: Correlation with disease severity and short-term prognosis. Eur Soc Radiol 2020;30:6808-17.  Back to cited text no. 13
Zhang B, Zhang J, Chen H, Coco S, Cilia F, Manganaro L, et al. Novel coranavirus disease 2019(COVID-19): Relationship between chest CT scores and laboratory parameters. Eur J Nucl Med Mol Imaging 2020;47:2083-9.  Back to cited text no. 14
Tan C, Huang Y, Shi F, Tan K, Ma Q, Chen Y, et al. C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early. J. Med Virol 2020;92:856-62.  Back to cited text no. 15
Huang G, Gong T, Wang G, Wang J, Guo X, Cai E, et al. Timely diagnosis and treatment shortens the time to resolution of coronavirus disease (COVID-19) pneumonia and lowers the highest and last CT scores from sequential chest CT. AJR Am J Roentgenol 2020;215:367-73.  Back to cited text no. 16
Pan F, Ye F, Sun P, Gui S, Liang B, Li L, et al. Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia. Radiology 2020;295:715-21.  Back to cited text no. 17
Cheng Z, Qin L, Cao Q, Dai J, Pan A, Yang W, et al. Quantitative computed tomography of the coronavirus disease 2019 (COVID-19) pneumonia. Radiol Infect Dis 2020;7:55-61.  Back to cited text no. 18
Zhang ZL, Hou YL, Li DT, Li FZ. Laboratory findings of COVID-19: A systematic review and meta-analysis. Scand J Clin Lab Invest 2020;80:1-7.  Back to cited text no. 19
Martins-Filho PR, Tavares CS, Santos VS. Factors associated with mortality patıents with COVID-19. Eur J Intern Med 2020;76:97-9.  Back to cited text no. 20
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;21:180.  Back to cited text no. 21
Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020;46:846-8.  Back to cited text no. 22
Xiong Y, Sun D, Liu Y, Fan YQ, Zhao LY, Li XM, et al. Clinical and high- resolution CT features of COVID-19 infection: Comparision of the initial and fallow-up changes. Invest Radiol 2020;55:332-9.  Back to cited text no. 23
Velavan TP, Meyer CG. Mild versus severe COVID-19: Laboratory markers. Int J Infect Dis 2020;95:304-7.  Back to cited text no. 24
Nurshad A. Elevated level of C-reactive protein may be an early marker to predict risk for severity of COVID-19. J Med Virol 2020;92:2409-11.  Back to cited text no. 25
Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020;323:1061-9.  Back to cited text no. 26
Aziz M, Fatima R, Lee-Smith W, Assaly R. The association of low serum albumin level with severe COVID-19: A systematic review and meta-analysis. Crit Care 2020;24:255.  Back to cited text no. 27
Huang J, Cheng A, Kumar R, Fang YY, Chen GP, Zhu YY, et al. Hypoalbuminemia predicts the outcome of COVID-19 independent of age and co-morbidity. J Med Virol 2020;92:2152-8.  Back to cited text no. 28
Salehi S, Abedi A, Balakrishnan S, Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19): A systematic review of imaging findings in 919 patients. AJR Am J Roentgenol 2020;215:87-93.  Back to cited text no. 29
Xu X, Yu C, Qu J, Zhang L, Jiang S, Huang D, et al. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. Eur J Nucl Med Mol Imaging 2020;47:1275-80.  Back to cited text no. 30
Sun D, Li X, Guo D, Wu L, Chen T, Fang Z, et al. CT quantitative analysis and its relationship with clinical features for assessing the severity of patients with COVID-19. Korean J Radiol 2020;21:859-68.  Back to cited text no. 31


  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Materials and Me...
Article Figures
Article Tables

 Article Access Statistics
    PDF Downloaded1107    
    Comments [Add]    

Recommend this journal