Literature DB >> 32903056

Multicenter Study of Temporal Changes and Prognostic Value of a CT Visual Severity Score in Hospitalized Patients With Coronavirus Disease (COVID-19).

Xiaofeng Wang1,2,3, Xingxing Hu4, Weijun Tan5, Peter Mazzone2,3, Eduardo Mireles-Cabodevila2,3, Xiaozhen Han1, Pingyue Huang6, Weihua Hu7, Raed Dweik2,3, Zhenshun Cheng4,8.   

Abstract

BACKGROUND. Chest CT findings have the potential to guide treatment of hospitalized patients with coronavirus disease (COVID-19). OBJECTIVE. The purpose of this study was to assess a CT visual severity score in hospitalized patients with COVID-19, with attention to temporal changes in the score and the role of the score in a model for predicting in-hospital complications. METHODS. This retrospective study included 161 inpatients with COVID-19 from three hospitals in China who underwent serial chest CT scans during hospitalization. CT examinations were evaluated using a visual severity scoring system. The temporal pattern of the CT visual severity score across serial CT examinations during hospitalization was characterized using a generalized spline regression model. A prognostic model to predict major complications, including in-hospital mortality, was created using the CT visual severity score and clinical variables. External model validation was evaluated by two independent radiologists in a cohort of 135 patients from a different hospital. RESULTS. The cohort included 91 survivors with nonsevere disease, 55 survivors with severe disease, and 15 patients who died during hospitalization. Median CT visual lung severity score in the first week of hospitalization was 2.0 in survivors with non-severe disease, 4.0 in survivors with severe disease, and 11.0 in nonsurvivors. CT visual severity score peaked approximately 9 and 12 days after symptom onset in survivors with nonsevere and severe disease, respectively, and progressively decreased in subsequent hospitalization weeks in both groups. In the prognostic model, in-hospital complications were independently associated with a severe CT score (odds ratio [OR], 31.28), moderate CT score (OR, 5.86), age (OR, 1.09 per 1-year increase), and lymphocyte count (OR, 0.03 per 1 × 109/L increase). In the validation cohort, the two readers achieved C-index values of 0.92-0.95, accuracy of 85.2-86.7%, sensitivity of 70.7-75.6%, and specificity of 91.4-91.5% for predicting in-hospital complications. CONCLUSION. A CT visual severity score is associated with clinical disease severity and evolves in a characteristic fashion during hospitalization for COVID-19. A prognostic model based on the CT visual severity score and clinical variables shows strong performance in predicting in-hospital complications. CLINICAL IMPACT. The prognostic model using the CT visual severity score may help identify patients at highest risk of poor outcomes and guide early intervention.

Entities:  

Keywords:  COVID-19; change points; complications; prediction; series CT

Year:  2020        PMID: 32903056     DOI: 10.2214/AJR.20.24044

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  14 in total

1.  Developing and Validating Multi-Modal Models for Mortality Prediction in COVID-19 Patients: a Multi-center Retrospective Study.

Authors:  Joy Tzung-Yu Wu; Miguel Ángel Armengol de la Hoz; Po-Chih Kuo; José Maria Castellano; Leo Anthony Celi; Joseph Alexander Paguio; Jasper Seth Yao; Edward Christopher Dee; Wesley Yeung; Jerry Jurado; Achintya Moulick; Carmelo Milazzo; Paloma Peinado; Paula Villares; Antonio Cubillo; José Felipe Varona; Hyung-Chul Lee; Alberto Estirado
Journal:  J Digit Imaging       Date:  2022-07-05       Impact factor: 4.903

Review 2.  Imaging approach to COVID-19 associated pulmonary embolism.

Authors:  Lukas M Trunz; Patrick Lee; Steven M Lange; Corbin L Pomeranz; Laurence Needleman; Robert W Ford; Ajit Karambelkar; Baskaran Sundaram
Journal:  Int J Clin Pract       Date:  2021-05-24       Impact factor: 3.149

3.  Phenotypes and Subphenotypes of Patients With Coronavirus Disease 2019: A Latent Class Modeling Analysis.

Authors:  Xiaofeng Wang; Lara Jehi; Xinge Ji; Peter J Mazzone
Journal:  Chest       Date:  2021-02-26       Impact factor: 9.410

4.  COVID-19: A qualitative chest CT model to identify severe form of the disease.

Authors:  Antoine Devie; Lukshe Kanagaratnam; Jeanne-Marie Perotin; Damien Jolly; Jean-Noël Ravey; Manel Djelouah; Christine Hoeffel
Journal:  Diagn Interv Imaging       Date:  2020-12-17       Impact factor: 4.026

5.  Visual scoring of chest CT at hospital admission predicts hospitalization time and intensive care admission in Covid-19.

Authors:  Erik Ahlstrand; Sara Cajander; Per Cajander; Edvin Ingberg; Erika Löf; Matthias Wegener; Mats Lidén
Journal:  Infect Dis (Lond)       Date:  2021-04-13

6.  Should CT be used for the diagnosis of RT-PCR-negative suspected COVID-19 patients?

Authors:  Günay Rona; Meral Arifoğlu; Nuray Voyvoda; Ayşe Batırel
Journal:  Clin Respir J       Date:  2021-02-02       Impact factor: 1.761

7.  CT score in COVID-19-related pneumonia, the radiologist, and the internist. Trying to unmask who is "the good", who is "the bad" and who is "the ugly".

Authors:  Giulia Crisci; Valeria Valente; Andrea Salzano; Antonio Cittadini; Alberto Maria Marra
Journal:  Intern Emerg Med       Date:  2021-11-23       Impact factor: 5.472

8.  Associations between CT pulmonary opacity score on admission and clinical characteristics and outcomes in patients with COVID-19.

Authors:  Huanyuan Luo; Yuancheng Wang; Songqiao Liu; Ruoling Chen; Tao Chen; Yi Yang; Duolao Wang; Shenghong Ju
Journal:  Intern Emerg Med       Date:  2021-06-30       Impact factor: 5.472

Review 9.  A Pictorial Review of the Role of Imaging in the Detection, Management, Histopathological Correlations, and Complications of COVID-19 Pneumonia.

Authors:  Barbara Brogna; Elio Bignardi; Claudia Brogna; Mena Volpe; Giulio Lombardi; Alessandro Rosa; Giuliano Gagliardi; Pietro Fabio Maurizio Capasso; Enzo Gravino; Francesca Maio; Francesco Pane; Valentina Picariello; Marcella Buono; Lorenzo Colucci; Lanfranco Aquilino Musto
Journal:  Diagnostics (Basel)       Date:  2021-03-04

10.  Antibodies Can Last for More Than 1 Year After SARS-CoV-2 Infection: A Follow-Up Study From Survivors of COVID-19.

Authors:  Kaihu Xiao; Haiyan Yang; Bin Liu; Xiaohua Pang; Jianlin Du; Mengqi Liu; Yajie Liu; Xiaodong Jing; Jing Chen; Songbai Deng; Zheng Zhou; Jun Du; Li Yin; Yuling Yan; Huaming Mou; Qiang She
Journal:  Front Med (Lausanne)       Date:  2021-07-16
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