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      CT Quantification of COVID-19 Pneumonia at Admission Can Predict Progression to Critical Illness: A Retrospective Multicenter Cohort Study

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          Abstract

          Objective: Early identification of coronavirus disease 2019 (COVID-19) patients with worse outcomes may benefit clinical management of patients. We aimed to quantify pneumonia findings on CT at admission to predict progression to critical illness in COVID-19 patients.

          Methods: This retrospective study included laboratory-confirmed adult patients with COVID-19. All patients underwent a thin-section chest computed tomography (CT) scans showing evidence of pneumonia. CT images with severe moving artifacts were excluded from analysis. Patients' clinical and laboratory data were collected from medical records. Three quantitative CT features of pneumonia lesions were automatically calculated using a care.ai Intelligent Multi-disciplinary Imaging Diagnosis Platform Intelligent Evaluation System of Chest CT for COVID-19, denoting the percentage of pneumonia volume (PPV), ground-glass opacity volume (PGV), and consolidation volume (PCV). According to Chinese COVID-19 guidelines (trial version 7), patients were divided into noncritical and critical groups. Critical illness was defined as a composite of admission to the intensive care unit, respiratory failure requiring mechanical ventilation, shock, or death. The performance of PPV, PGV, and PCV in discrimination of critical illness was assessed. The correlations between PPV and laboratory variables were assessed by Pearson correlation analysis.

          Results: A total of 140 patients were included, with mean age of 58.6 years, and 85 (60.7%) were male. Thirty-two (22.9%) patients were critical. Using a cutoff value of 22.6%, the PPV had the highest performance in predicting critical illness, with an area under the curve of 0.868, sensitivity of 81.3%, and specificity of 80.6%. The PPV had moderately positive correlation with neutrophil (%) ( r = 0.535, p < 0.001), erythrocyte sedimentation rate ( r = 0.567, p < 0.001), d-Dimer ( r = 0.444, p < 0.001), high-sensitivity C-reactive protein ( r = 0.495, p < 0.001), aspartate aminotransferase ( r = 0.410, p < 0.001), lactate dehydrogenase ( r = 0.644, p < 0.001), and urea nitrogen ( r = 0.439, p < 0.001), whereas the PPV had moderately negative correlation with lymphocyte (%) ( r = −0.535, p < 0.001).

          Conclusions: Pneumonia volume quantified on initial CT can non-invasively predict the progression to critical illness in advance, which serve as a prognostic marker of COVID-19.

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          Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

          Nanshan Chen, Min Zhou, Xuan Dong … (2022)
          Summary Background In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia. Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020. Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure. Interpretation The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection. Funding National Key R&D Program of China.
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            Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

            Zunyou Wu, Jennifer M. McGoogan (2020)
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              Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

              Xiaobo Yang, Yuan Yu, Jiqian Xu … (2020)
              Summary Background An ongoing outbreak of pneumonia associated with the severe acute respiratory coronavirus 2 (SARS-CoV-2) started in December, 2019, in Wuhan, China. Information about critically ill patients with SARS-CoV-2 infection is scarce. We aimed to describe the clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia. Methods In this single-centered, retrospective, observational study, we enrolled 52 critically ill adult patients with SARS-CoV-2 pneumonia who were admitted to the intensive care unit (ICU) of Wuhan Jin Yin-tan hospital (Wuhan, China) between late December, 2019, and Jan 26, 2020. Demographic data, symptoms, laboratory values, comorbidities, treatments, and clinical outcomes were all collected. Data were compared between survivors and non-survivors. The primary outcome was 28-day mortality, as of Feb 9, 2020. Secondary outcomes included incidence of SARS-CoV-2-related acute respiratory distress syndrome (ARDS) and the proportion of patients requiring mechanical ventilation. Findings Of 710 patients with SARS-CoV-2 pneumonia, 52 critically ill adult patients were included. The mean age of the 52 patients was 59·7 (SD 13·3) years, 35 (67%) were men, 21 (40%) had chronic illness, 51 (98%) had fever. 32 (61·5%) patients had died at 28 days, and the median duration from admission to the intensive care unit (ICU) to death was 7 (IQR 3–11) days for non-survivors. Compared with survivors, non-survivors were older (64·6 years [11·2] vs 51·9 years [12·9]), more likely to develop ARDS (26 [81%] patients vs 9 [45%] patients), and more likely to receive mechanical ventilation (30 [94%] patients vs 7 [35%] patients), either invasively or non-invasively. Most patients had organ function damage, including 35 (67%) with ARDS, 15 (29%) with acute kidney injury, 12 (23%) with cardiac injury, 15 (29%) with liver dysfunction, and one (2%) with pneumothorax. 37 (71%) patients required mechanical ventilation. Hospital-acquired infection occurred in seven (13·5%) patients. Interpretation The mortality of critically ill patients with SARS-CoV-2 pneumonia is considerable. The survival time of the non-survivors is likely to be within 1–2 weeks after ICU admission. Older patients (>65 years) with comorbidities and ARDS are at increased risk of death. The severity of SARS-CoV-2 pneumonia poses great strain on critical care resources in hospitals, especially if they are not adequately staffed or resourced. Funding None.
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                Author and article information

                Contributors
                Journal
                Journal ID (nlm-ta): Front Med (Lausanne)
                Journal ID (iso-abbrev): Front Med (Lausanne)
                Journal ID (publisher-id): Front. Med.
                Title: Frontiers in Medicine
                Publisher: Frontiers Media S.A.
                ISSN (Electronic): 2296-858X
                Publication date (Electronic): 17 June 2021
                Publication date Collection: 2021
                Publication date PMC-release: 17 June 2021
                Volume: 8
                Electronic Location Identifier: 689568
                Affiliations
                [1] 1Department of Radiology, Huangpi District Hospital of Traditional Chinese Medicine , Wuhan, China
                [2] 2Department of Radiology, Han Kou Hospital of Wuhan , Wuhan, China
                [3] 3Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou, China
                [4] 4Pulmonary and Critical Care Medicine, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou, China
                [5] 5Department of Respiratory, First Affiliated Hospital of Guangxi University of Science and Technology , Liuzhou, China
                [6] 6Department of Pediatric Hematology, Affiliated Hospital of Guizhou Medical University , Guiyang, China
                [7] 7Department of Hematology, Dawu County People's Hospital , Wuhan, China
                [8] 8Department of Hematology, Zhongnan Hospital of Wuhan University , Wuhan, China
                [9] 9Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou, China
                [10] 10National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Diseases, Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou, China
                [11] 11Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University , Nanning, China
                [12] 12Department of Respiratory, Hankou Hospital of Wuhan , Wuhan, China
                Author notes

                Edited by: Reza Lashgari, Institute for Research in Fundamental Sciences, Iran

                Reviewed by: Gisella Guido, Sapienza University of Rome, Italy; Michaela Cellina, ASST Fatebenefratelli Sacco, Italy

                *Correspondence: Qingsi Zeng zengqingsi@ 123456gzhmu.edu.cn

                This article was submitted to Infectious Diseases - Surveillance, Prevention and Treatment, a section of the journal Frontiers in Medicine

                †These authors have contributed equally to this work

                Article
                DOI: 10.3389/fmed.2021.689568
                PMC ID: 8245676
                PubMed ID: 34222293
                SO-VID: a73d3a70-c002-43a2-9b17-8edb8f8e9feb
                Copyright © Copyright © 2021 Pang, Li, Liu, Wu, Xia, Zhang, Le, Li, Lai, Ou, Ma, Liu, Zhou, Wang, Xie, Zhang, Jiang, Liu and Zeng.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                Date received : 01 April 2021
                Date accepted : 10 May 2021
                Page count
                Figures: 6, Tables: 3, Equations: 0, References: 56, Pages: 12, Words: 6821
                Categories
                Subject: Medicine
                Subject: Original Research

                Keywords: covid-19,pneumonia,critical illness,chest ct,quantification
                Data availability:
                Keywords: covid-19, pneumonia, critical illness, chest ct, quantification

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