Literature DB >> 33656732

Identification, Monitoring, and Prediction of Disease Severity in Patients with COVID-19 Pneumonia Based on Chest Computed Tomography Scans: A Retrospective Study.

Ramezan Jafari1, Sara Ashtari2, Mohamad Amin Pourhoseingholi2, Houshyar Maghsoudi1, Fatemeh Cheraghalipoor1, Nematollah Jonaidi Jafari3, Hassan Saadat4, Farshid Rahimi-Bashar5, Amir Vahedian-Azimi6, Amirhossein Sahebkar7,8,9,10.   

Abstract

Background and Aims Non-contrast chest computed tomography (CT) scans can accurately evaluate the type and extent of lung lesions. The aim of this study was to investigate the chest CT features associated with critical and non-critical patients with coronavirus disease 2019 (COVID-19). Methods A total of 1078 patients with COVID-19 pneumonia who underwent chest CT scans, including 169 critical cases and 909 non-critical cases, were enrolled in this retrospective study. The scans of all participants were reviewed and compared in two groups of study. In addition, the risk factors associated with disease in critical and non-critical patients were analyzed. Results Chest CT scans showed bilateral and multifocal involvement in most (86.4%) of the participants, with 97.6 and 84.3% reported in critical and non-critical patients, respectively. The incidences of pure consolidation (p = 0.019), mixed ground-glass opacities (GGOs) and consolidation (p < 0.001), pleural effusion (p < 0.001), and intralesional traction bronchiectasis (p = 0.007) were significantly higher in critical compared to non-critical patients. However, non-critical patients showed higher incidence of pure GGOs than the critical patients (p < 0.001). Finally, the total opacity scores of the critical patients were significantly higher than those of non-critical patients (13.71 ± 6.26 versus 4.86 ± 3.52, p < 0.001), with an area under the curve of 0.91 (0.88-0.94) for COVID-19 detection. Conclusions Our results revealed that the chest CT examination was an effective means of detecting pulmonary parenchymal abnormalities in the natural course of COVID-19. It can distinguish the critical patients from the non-critical patients (AUC = 0.91), which is helpful for the judgment of clinical condition and has important clinical value for the diagnosis and follow-up of COVID-19 pneumonia.

Entities:  

Keywords:  COVID-2019; Chest CT scan; Critical; Non-critical; Prediction; Prognosis; Risk factor

Year:  2021        PMID: 33656732     DOI: 10.1007/978-3-030-59261-5_24

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  5 in total

Review 1.  The pivotal role of CD69 in autoimmunity.

Authors:  Armita Mahdavi Gorabi; Saeideh Hajighasemi; Nasim Kiaie; Seyed Mohammad Gheibi Hayat; Tannaz Jamialahmadi; Thomas P Johnston; Amirhossein Sahebkar
Journal:  J Autoimmun       Date:  2020-04-11       Impact factor: 7.094

2.  Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection.

Authors:  Adam Bernheim; Xueyan Mei; Mingqian Huang; Yang Yang; Zahi A Fayad; Ning Zhang; Kaiyue Diao; Bin Lin; Xiqi Zhu; Kunwei Li; Shaolin Li; Hong Shan; Adam Jacobi; Michael Chung
Journal:  Radiology       Date:  2020-02-20       Impact factor: 11.105

3.  Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges.

Authors:  Chih-Cheng Lai; Tzu-Ping Shih; Wen-Chien Ko; Hung-Jen Tang; Po-Ren Hsueh
Journal:  Int J Antimicrob Agents       Date:  2020-02-17       Impact factor: 5.283

4.  Coronavirus disease 2019 (COVID-19): current status and future perspectives.

Authors:  Heng Li; Shang-Ming Liu; Xiao-Hua Yu; Shi-Lin Tang; Chao-Ke Tang
Journal:  Int J Antimicrob Agents       Date:  2020-03-29       Impact factor: 5.283

5.  CT manifestations of coronavirus disease-2019: A retrospective analysis of 73 cases by disease severity.

Authors:  Kai-Cai Liu; Ping Xu; Wei-Fu Lv; Xiao-Hui Qiu; Jin-Long Yao; Jin-Feng Gu; Wei Wei
Journal:  Eur J Radiol       Date:  2020-03-12       Impact factor: 3.528

  5 in total
  1 in total

1.  Predicting the Disease Severity of Virus Infection.

Authors:  Xin Qi; Li Shen; Jiajia Chen; Manhong Shi; Bairong Shen
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

  1 in total

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