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  1. Article: [CT imaging features of patients with different clinical types of COVID-19].

    Zhong, Qi / Li, Zhi / Shen, Xiaoyong / Xu, Kaijin / Shen, Yihong / Fang, Qiang / Chen, Feng / Liang, Tingbo

    Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences

    2020  Volume 49, Issue 2, Page(s) 198–202

    Abstract: Objective: To investigate the CT findings of patients with different clinical types of coronavirus ... with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe ... critical ill. No significant abnormality in chest CT imaging in mild patients. The 35 cases of moderate type ...

    Abstract Objective: To investigate the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19).
    Methods: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were collected and divided into 4 groups according to the clinical stages based on
    Results: Among 67 patients, 3(4.5%) were mild, 35 (52.2%) were moderate, 22 (32.8%) were severe, and 7(10.4%) were critical ill. No significant abnormality in chest CT imaging in mild patients. The 35 cases of moderate type included 3 (8.6%) single lesions, the 22 cases of severe cases included 1 (4.5%) single lesion and the rest cases were with multiple lesions. CT images of moderate patients were mainly manifested by solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients.
    Conclusions: CT images of patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
    MeSH term(s) Betacoronavirus/isolation & purification ; COVID-19 ; Coronavirus Infections/classification ; Coronavirus Infections/diagnostic imaging ; Humans ; Lung/diagnostic imaging ; Pandemics/classification ; Pneumonia, Viral/classification ; Pneumonia, Viral/diagnostic imaging ; SARS-CoV-2 ; Tomography, X-Ray Computed
    Keywords covid19
    Language Chinese
    Publishing date 2020-05-24
    Publishing country China
    Document type Journal Article
    ISSN 1008-9292
    ISSN 1008-9292
    DOI 10.3785/j.issn.1008-9292.2020.03.05
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: [CT imaging features of patients with different clinical types of COVID-19]

    Zhong, Qi / Li, Zhi / Shen, Xiaoyong / Xu, Kaijin / Shen, Yihong / Fang, Qiang / Chen, Feng / Liang, Tingbo

    Zhejiang Da Xue Xue Bao Yi Xue Ban

    Abstract: ... CONCLUSIONS: CT images of patients with different clinical types of COVID-19 have characteristic ... OBJECTIVE: To investigate the CT findings of patients with different clinical types of coronavirus ... among patients with different clinical types. RESULTS: Among 67 patients, 3(4.5%) were mild, 35 (52.2%) were ...

    Abstract OBJECTIVE: To investigate the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19). METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were collected and divided into 4 groups according to the clinical stages based on Diagnosis and treatment of novel coronavirus pneumonia (trial version 6). The CT imaging characteristics were analyzed among patients with different clinical types. RESULTS: Among 67 patients, 3(4.5%) were mild, 35 (52.2%) were moderate, 22 (32.8%) were severe, and 7(10.4%) were critical ill. No significant abnormality in chest CT imaging in mild patients. The 35 cases of moderate type included 3 (8.6%) single lesions, the 22 cases of severe cases included 1 (4.5%) single lesion and the rest cases were with multiple lesions. CT images of moderate patients were mainly manifested by solid plaque shadow and halo sign (18/35, 51.4%); while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31.8%). Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients. CONCLUSIONS: CT images of patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #32391664
    Database COVID19

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  3. Article: CT imaging features of patients with different clinical types of coronavirus disease 2019 (COVID-19)

    Zhong, Qi / Li, Zhi / Shen, Xiaoyong / Xu, Kaijin / Shen, Yihong / Fang, Qiang / Chen, Feng / Liang, Tingbo

    Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences

    Abstract: ... all of them were severe or critical ill patients CONCLUSIONS: CT images in patients with different clinical types ... OBJECTIVE: To analyze the CT findings of patients with different clinical types of coronavirus ... among patients with different clinical types RESULTS: Among 67 patients, 3 (4 5%) were mild cases, 35 (52 2 ...

    Abstract OBJECTIVE: To analyze the CT findings of patients with different clinical types of coronavirus disease 2019 (COVID-19) METHODS: A total of 67 patients diagnosed as COVID-19 by nucleic acid testing were included and divided into 4 groups according to the clinical staging based on Diagnosis and treatment of novel coronavirus pneumonia (Trial version 6) The CT imaging characteristics were analyzed among patients with different clinical types RESULTS: Among 67 patients, 3 (4 5%) were mild cases, 35 (52 2%) were ordinary cases, 22 (32 8%) were severe cases, and 7 (10 4%) were critically ill There were no abnormal CT findings in mild cases In 35 ordinary cases, there were single lesions in 3 cases (8 6%) and multiple lesions in 33 cases (91 4%), while in severe case 1 case had single lesion (4 5%) and 21 had multiple lesions (95 5%) CT images of ordinary patients were mainly manifested as solid plaque shadow and halo sign (18/35, 51 4%);while fibrous strip shadow with ground glass shadow was more frequent in severe cases (7/22, 31 8%) Consolidation shadow as the main lesion was observed in 7 cases, and all of them were severe or critical ill patients CONCLUSIONS: CT images in patients with different clinical types of COVID-19 have characteristic manifestations, and solid shadow may predict severe and critical illness
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #807608
    Database COVID19

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  4. Article: Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant.

    Zhu, Zhenchen / Hu, Ge / Ying, Zhoumeng / Wang, Jinhua / Han, Wei / Pan, Zhengsong / Tian, Xinlun / Song, Wei / Sui, Xin / Song, Lan / Jin, Zhengyu

    Heliyon

    2024  Volume 10, Issue 7, Page(s) e27963

    Abstract: ... This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic ... critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment. ... combining qualitative CT features and the CT score complements clinical factors for identifying severe ...

    Abstract Rationale and objectives: The computed tomography (CT) score has been used to evaluate the severity of COVID-19 during the pandemic; however, most studies have overlooked the impact of infection duration on the CT score. This study aimed to determine the optimal cutoff CT score value for identifying severe/critical COVID-19 during different stages of infection and to construct corresponding predictive models using radiological characteristics and clinical factors.
    Materials and methods: This retrospective study collected consecutive baseline chest CT images of confirmed COVID-19 patients from a fever clinic at a tertiary referral hospital from November 28, 2022, to January 8, 2023. Cohorts were divided into three subcohorts according to the time interval from symptom onset to CT examination at the hospital: early phase (0-3 days), intermediate phase (4-7 days), and late phase (8-14 days). The binary endpoints were mild/moderate and severe/critical infection. The CT scores and qualitative CT features were manually evaluated. A logistic regression analysis was performed on the CT score as determined by a visual assessment to predict severe/critical infection. Receiver operating characteristic analysis was performed and the area under the curve (AUC) was calculated. The optimal cutoff value was determined by maximizing the Youden index in each subcohort. A radiology score and integrated models were then constructed by combining the qualitative CT features and clinical features, respectively, using multivariate logistic regression with stepwise elimination.
    Results: A total of 962 patients (aged, 61.7 ± 19.6 years; 490 men) were included; 179 (18.6%) were classified as severe/critical COVID-19, while 344 (35.8%) had a typical Radiological Society of North America (RSNA) COVID-19 appearance. The AUCs of the CT score models reached 0.91 (95% confidence interval (CI) 0.88-0.94), 0.82 (95% CI 0.76-0.87), and 0.83 (95% CI 0.77-0.89) during the early, intermediate, and late phases, respectively. The best cutoff values of the CT scores during each phase were 1.5, 4.5, and 5.5. The predictive accuracies associated with the time-dependent cutoff values reached 88% (vs.78%), 73% (vs. 63%), and 87% (vs. 57%), which were greater than those associated with universal cutoff value (all
    Conclusion: The time interval between symptom onset and CT examination should be tracked to determine the cutoff value for the CT score for identifying severe/critical COVID-19. The radiology score combining qualitative CT features and the CT score complements clinical factors for identifying severe/critical COVID-19 patients and facilitates timely hierarchical diagnoses and treatment.
    Language English
    Publishing date 2024-03-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e27963
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  5. Article ; Online: Predicting model of mild and severe types of COVID-19 patients using Thymus CT radiomics model: A preliminary study.

    An, Peng / Li, Xiumei / Qin, Ping / Ye, YingJian / Zhang, Junyan / Guo, Hongyan / Duan, Peng / He, Zhibing / Song, Ping / Li, Mingqun / Wang, Jinsong / Hu, Yan / Feng, Guoyan / Lin, Yong

    Mathematical biosciences and engineering : MBE

    2023  Volume 20, Issue 4, Page(s) 6612–6629

    Abstract: ... manifestations and radiomic features of the thymus in COVID-19 patients.: Method: We retrospectively analyzed ... features of the COVID-19 patients. The DeLong test and decision curve analysis (DCA) were used to compare ... radiomic features of COVID-19 patients had the highest predictive value for COVID-19 severity [AUC: 0.967 ...

    Abstract Objective: To predict COVID-19 severity by building a prediction model based on the clinical manifestations and radiomic features of the thymus in COVID-19 patients.
    Method: We retrospectively analyzed the clinical and radiological data from 217 confirmed cases of COVID-19 admitted to Xiangyang NO.1 People's Hospital and Jiangsu Hospital of Chinese Medicine from December 2019 to April 2022 (including 118 mild cases and 99 severe cases). The data were split into the training and test sets at a 7:3 ratio. The cases in the training set were compared in terms of clinical data and radiomic parameters of the lasso regression model. Several models for severity prediction were established based on the clinical and radiomic features of the COVID-19 patients. The DeLong test and decision curve analysis (DCA) were used to compare the performances of several models. Finally, the prediction results were verified on the test set.
    Result: For the training set, the univariate analysis showed that BMI, diarrhea, thymic steatosis, anorexia, headache, findings on the chest CT scan, platelets, LDH, AST and radiomic features of the thymus were significantly different between the two groups of patients (P < 0.05). The combination model based on the clinical and radiomic features of COVID-19 patients had the highest predictive value for COVID-19 severity [AUC: 0.967 (OR 0.0115, 95%CI: 0.925-0.989)] vs. the clinical feature-based model [AUC: 0.772 (OR 0.0387, 95%CI: 0.697-0.836), P < 0.05], laboratory-based model [AUC: 0.687 (OR 0.0423, 95%CI: 0.608-0.760), P < 0.05] and model based on CT radiomics [AUC: 0.895 (OR 0.0261, 95%CI: 0.835-0.938), P < 0.05]. DCA also confirmed the high clinical net benefits of the combination model. The nomogram drawn based on the combination model could help differentiate between the mild and severe cases of COVID-19 at an early stage. The predictions from different models were verified on the test set.
    Conclusion: Severe cases of COVID-19 had a higher level of thymic involution. The thymic differentiation in radiomic features was related to disease progression. The combination model based on the radiomic features of the thymus could better promote early clinical intervention of COVID-19 and increase the cure rate.
    MeSH term(s) Humans ; COVID-19/diagnostic imaging ; COVID-19/epidemiology ; Retrospective Studies ; Thymus Gland/diagnostic imaging ; Disease Progression ; Fatty Liver
    Language English
    Publishing date 2023-05-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2265126-3
    ISSN 1551-0018 ; 1551-0018
    ISSN (online) 1551-0018
    ISSN 1551-0018
    DOI 10.3934/mbe.2023284
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  6. Article ; Online: Comparison between original SARS-CoV-2 strain and omicron variant on thin-section chest CT imaging of COVID-19 pneumonia.

    Pingping, Zeng / Yanyu, Zhou / Xuri, Sun / Qiming, Huang / Yi, Wang / Guoliang, Tan

    Radiologie (Heidelberg, Germany)

    2023  Volume 63, Issue Suppl 2, Page(s) 55–63

    Abstract: ... to May 31, 2022. Data on the demographics, comorbidities, symptoms, clinical types, and CT features were ... of age, sex, clinical types, symptoms, and comorbidities. The main CT features differed between the two ... Objectives: We investigated different computed tomography (CT) features between Omicron-variant ...

    Title translation Vergleich zwischen dem Original-SARS-CoV-2-Stamm und der Omikron-Variante in der Dünnschicht-Thorax-CT-Bildgebung bei COVID-19-Pneumonie.
    Abstract Objectives: We investigated different computed tomography (CT) features between Omicron-variant and original-strain SARS-CoV‑2 pneumonia to facilitate the clinical management.
    Materials and methods: Medical records were retrospectively reviewed to select patients with original-strain SARS-CoV‑2 pneumonia from February 22 to April 22, 2020, or Omicron-variant SARS-CoV‑2 pneumonia from March 26 to May 31, 2022. Data on the demographics, comorbidities, symptoms, clinical types, and CT features were compared between the two groups.
    Results: There were 62 and 78 patients with original-strain or Omicron-variant SARS-CoV‑2 pneumonia, respectively. There were no differences between the two groups in terms of age, sex, clinical types, symptoms, and comorbidities. The main CT features differed between the two groups (p = 0.003). There were 37 (59.7%) and 20 (25.6%) patients with ground-glass opacities (GGO) in the original-strain and Omicron-variant pneumonia, respectively. A consolidation pattern was more frequently observed in the Omicron-variant than original-strain pneumonia (62.8% vs. 24.2%). There was no difference in crazy-paving pattern between the original-strain and Omicron-variant pneumonia (16.1% vs. 11.6%). Pleural effusion was observed more often in Omicron-variant pneumonia, while subpleural lesions were more common in the original-strain pneumonia. The CT score in the Omicron-variant group was higher than that in the original-strain group for critical-type (17.00, 16.00-18.00 vs. 16.00, 14.00-17.00, p = 0.031) and for severe-type (13.00, 12.00-14.00 vs 12.00, 10.75-13.00, p = 0.027) pneumonia.
    Conclusion: The main CT finding of the Omicron-variant SARS-CoV‑2 pneumonia included consolidations and pleural effusion. By contrast, CT findings of original-strain SARS-CoV‑2 pneumonia showed frequent GGO and subpleural lesions, but without pleural effusion. The CT scores were also higher in the critical and severe types of Omicron-variant than original-strain pneumonia.
    MeSH term(s) Humans ; COVID-19/diagnostic imaging ; COVID-19/pathology ; SARS-CoV-2 ; Lung/diagnostic imaging ; Lung/pathology ; Retrospective Studies ; Tomography, X-Ray Computed/methods ; Pneumonia/diagnostic imaging ; Pneumonia/pathology ; Pleural Effusion/diagnostic imaging ; Pleural Effusion/pathology
    Language English
    Publishing date 2023-06-06
    Publishing country Germany
    Document type Journal Article
    ISSN 2731-7056
    ISSN (online) 2731-7056
    DOI 10.1007/s00117-023-01147-2
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  7. Article ; Online: CT findings of COVID-19 pneumonia in ICU-patients

    Riccardo Cau / Zeno Falaschi / Alessio Paschè / Pietro Danna / Roberto Arioli / Chiara D. Arru / Domenico Zagaria / Stefano Tricca / Jasjit S. Suri / Mannudeep K. Karla / Alessandro Carriero / Luca Saba

    Journal of Public Health Research (2021)

    2021  

    Abstract: ... involvement by consolidation (p=0.02) and GGO (p=0.001). Conclusions: CT imaging features of ICU patients ... affected by COVID-19 are significantly different compared with non-ICU patients. Identification of CT ... patterns and clinical characteristics in intensive care unit (ICU) and non-ICU patients with COVID-19 ...

    Abstract Background: In December 2019, a cluster of unknown etiology pneumonia cases occurred in Wuhan, China leading to identification of the responsible pathogen as SARS-coV-2. Since then, the coronavirus disease 2019 (COVID-19) has spread to the entire world. Computed Tomography (CT) is frequently used to assess severity and complications of COVID-19 pneumonia. The purpose of this study is to compare the CT patterns and clinical characteristics in intensive care unit (ICU) and non-ICU patients with COVID-19 pneumonia. Design and Methods: This retrospective study included 218 consecutive patients (136 males; 82 females; mean age 63±15 years) with laboratory-confirmed SARS-coV-2. Patients were categorized in two different groups: (a) ICU patients and (b) non-ICU inpatients. We assessed the type and extent of pulmonary opacities on chest CT exams and recorded the information on comorbidities and laboratory values for all patients. Results: Of the 218 patients, 23 (20 males: 3 females; mean age 60 years) required ICU admission, 195 (118 males: 77 females, mean age 64 years) were admitted to a clinical ward. Compared with non-ICU patients, ICU patients were predominantly males (60% versus 83% p=0.03), had more comorbidities, a positive CRP (p=0.04) and higher LDH values (p=0.008). ICU patients’ chest CT demonstrated higher incidence of consolidation (p=0.03), mixed lesions (p=0.01), bilateral opacities (p<0.01) and overall greater lung involvement by consolidation (p=0.02) and GGO (p=0.001). Conclusions: CT imaging features of ICU patients affected by COVID-19 are significantly different compared with non-ICU patients. Identification of CT features could assist in a stratification of the disease severity and supportive treatment.
    Keywords CT ; COVID-19 ; severity score ; ICU ; Public aspects of medicine ; RA1-1270
    Subject code 610
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher PAGEPress Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Chest CT features and progression of patients with coronavirus disease 2019.

    Xie, Linjun / Hou, Keke / Xu, Huayan / Fu, Hang / Xu, Rong / Liu, Hui / Zhou, Zhongqin / Li, Zhenlin / Yang, Ming / Guo, Yingkun

    The British journal of radiology

    2020  Volume 93, Issue 1116, Page(s) 20200219

    Abstract: ... The clinical and chest imaging findings of COVID-19 patients with different severity types were compared ... of adult COVID-19 patients with common type, severe and critically severe type were included ... and progression of the disease observed in COVID-19 patients.: Methods: Forty-nine confirmed cases ...

    Abstract Objectives: Coronavirus disease 2019 (COVID-19) is a major public health emergency. It poses a grave threat to human life and health. The purpose of the study is to investigate the chest CT findings and progression of the disease observed in COVID-19 patients.
    Methods: Forty-nine confirmed cases of adult COVID-19 patients with common type, severe and critically severe type were included in this retrospective single-center study. The thin-section chest CT features and progress of the disease were evaluated. The clinical and chest imaging findings of COVID-19 patients with different severity types were compared. The CT severity score and MuLBSTA score (a prediction of mortality risk) were calculated in those patients.
    Results: Among the 49 patients, 35 patients (71%) were common type and 14 patients (28%) were severe and critically severe type. Nearly all patients (98%) had pure ground-glass opacities (GGO) in CT imaging. Of the severe and critically severe type patients, 86% exhibited GGO with consolidation, in comparison with 54% of the patients with common type. Fibrosis presented in 79% of the severe and critically severe type patients and 43% of the common type patients. The severe and critically severe type patients were significantly more prone to experience five-lobe involvement compared to the common type patients (
    Conclusions: The severe and critically severe type patients often experienced more severe lung lesions, including GGO with consolidation. The CT severity score and MuLBSTA score may be helpful for the assessment of COVID-19 severity and progression.
    Advances in knowledge: Chest CT has the value of evaluated radiographical features of COVID-19 and allow for dynamic observation of the disease progression. Considering coagulation disorder of COVID-19, MuLBSTA score may need to be updated to increase new understanding of COVID-19.
    MeSH term(s) Adult ; Aged ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnostic imaging ; Disease Progression ; Female ; Humans ; Lung/diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral/diagnostic imaging ; Reproducibility of Results ; Retrospective Studies ; SARS-CoV-2 ; Severity of Illness Index ; Tomography, X-Ray Computed/methods ; Young Adult
    Keywords covid19
    Language English
    Publishing date 2020-11-13
    Publishing country England
    Document type Journal Article
    ZDB-ID 2982-8
    ISSN 1748-880X ; 0007-1285
    ISSN (online) 1748-880X
    ISSN 0007-1285
    DOI 10.1259/bjr.20200219
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  9. Article ; Online: COVID-19: What Iodine Maps From Perfusion CT can reveal-A Prospective Cohort Study.

    Santamarina, Mario G / Boisier Riscal, Dominique / Beddings, Ignacio / Contreras, Roberto / Baque, Martiniano / Volpacchio, Mariano / Martinez Lomakin, Felipe

    Critical care (London, England)

    2020  Volume 24, Issue 1, Page(s) 619

    Abstract: ... seen in patients with COVID-19 pneumonia and correlate them with clinical outcomes.: Material and ... methods: A prospective cohort study was carried out with 45 RT-PCR-confirmed COVID-19 patients ... by sCTA are associated with increased admission to ICU and initiation of IMV in COVID-19 patients. ...

    Abstract Background: Subtraction CT angiography (sCTA) is a technique used to evaluate pulmonary perfusion based on iodine distribution maps. The aim of this study is to assess lung perfusion changes with sCTA seen in patients with COVID-19 pneumonia and correlate them with clinical outcomes.
    Material and methods: A prospective cohort study was carried out with 45 RT-PCR-confirmed COVID-19 patients that required hospitalization at three different hospitals, between April and May 2020. In all cases, a basic clinical and demographic profile was obtained. Lung perfusion was assessed using sCTA. Evaluated imaging features included: Pattern predominance of injured lung parenchyma in both lungs (ground-glass opacities, consolidation and mixed pattern) and anatomical extension; predominant type of perfusion abnormality (increased perfusion or hypoperfusion), perfusion abnormality distribution (focal or diffuse), extension of perfusion abnormalities (mild, moderate and severe involvement); presence of vascular dilatation and vascular tortuosity. All participants were followed-up until hospital discharge searching for the development of any of the study endpoints. These endpoints included intensive-care unit (ICU) admission, initiation of invasive mechanical ventilation (IMV) and death.
    Results: Forty-one patients (55.2 ± 16.5 years, 22 men) with RT-PCR-confirmed SARS-CoV-2 infection and an interpretable iodine map were included. Patients with perfusion anomalies on sCTA in morphologically normal lung parenchyma showed lower Pa/Fi values (294 ± 111.3 vs. 397 ± 37.7, p = 0.035), and higher D-dimer levels (1156 ± 1018 vs. 378 ± 60.2, p < 0.01). The main common patterns seen in lung CT scans were ground-glass opacities, mixed pattern with predominant ground-glass opacities and mixed pattern with predominant consolidation in 56.1%, 24.4% and 19.5% respectively. Perfusion abnormalities were common (36 patients, 87.8%), mainly hypoperfusion in areas of apparently healthy lung. Patients with severe hypoperfusion in areas of apparently healthy lung parenchyma had an increased probability of being admitted to ICU and to initiate IMV (HR of 11.9 (95% CI 1.55-91.9) and HR 7.8 (95% CI 1.05-61.1), respectively).
    Conclusion: Perfusion abnormalities evidenced in iodine maps obtained by sCTA are associated with increased admission to ICU and initiation of IMV in COVID-19 patients.
    MeSH term(s) Adult ; Aged ; COVID-19 ; Contrast Media ; Coronavirus Infections/diagnostic imaging ; Female ; Humans ; Iodine ; Male ; Middle Aged ; Pandemics ; Perfusion Imaging/methods ; Pneumonia, Viral/diagnostic imaging ; Prospective Studies ; Tomography, X-Ray Computed/methods
    Chemical Substances Contrast Media ; Iodine (9679TC07X4)
    Keywords covid19
    Language English
    Publishing date 2020-10-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041406-7
    ISSN 1466-609X ; 1364-8535
    ISSN (online) 1466-609X
    ISSN 1364-8535
    DOI 10.1186/s13054-020-03333-3
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  10. Article ; Online: Chest CT features of coronavirus disease-19 (COVID-19) pneumonia: which findings on initial CT can predict an adverse short-term outcome?

    Parry, Arshed Hussain / Wani, Abdul Haseeb / Shah, Naveed Nazir / Yaseen, Mudasira / Jehangir, Majid

    BJR open

    2020  Volume 2, Issue 1, Page(s) 20200016

    Abstract: Objective: To study the spectrum of chest CT features in coronavirus disease-19 (COVID-19 ... distribution and type of abnormal lung findings were recorded. Patients with positive CT findings were divided ... of clinically unstable patients (63.6 ± 8.3 years) was significantly different from the clinically stable group ...

    Abstract Objective: To study the spectrum of chest CT features in coronavirus disease-19 (COVID-19) pneumonia and to identify the initial CT findings that may have the potential to predict a poor short-term outcome.
    Methods: This was a retrospective study comprising 211 reverse transcriptase-polymerase chain reaction (RT-PCR) positive patients who had undergone non-contrast chest CT. Prevalence, extent, pattern, distribution and type of abnormal lung findings were recorded. Patients with positive CT findings were divided into two groups; clinically stable (requiring in-ward hospitalization) and clinically unstable [requiring intensive care unit (ICU) admission or demised] based on short-term follow-up.
    Results: Lung parenchymal abnormalities were present in 42.2% (89/211) whereas 57.8% (122/211) cases had a normal chest CT. The mean age of clinically unstable patients (63.6 ± 8.3 years) was significantly different from the clinically stable group (44.6 ± 13.2 years) (
    Conclusion: Certain imaging findings on initial CT have the potential to predict short-term outcome in COVID-19 pneumonia. Extensive pulmonary abnormalities, evaluated by combined anteroposterior, central-peripheral and a higher percentage of the total lung involvement, indicate a poor short-term outcome. Similarly, the presence of crazy paving pattern, consolidation with air bronchogram and segmental vascular changes are also indicators of poor short-term outcome.
    Advances in knowledge: Certain findings on initial CT can predict an adverse short-term prognosis in COVID-19 pneumonia.
    Keywords covid19
    Language English
    Publishing date 2020-06-19
    Publishing country England
    Document type Journal Article
    ISSN 2513-9878
    ISSN (online) 2513-9878
    DOI 10.1259/bjro.20200016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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