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Zhu Z, Hu G, Ying Z, Wang J, Han W, Pan Z, Tian X, Song W, Sui X, Song L, Jin Z. Time-dependent CT score-based model for identifying severe/critical COVID-19 at a fever clinic after the emergence of Omicron variant. Heliyon 2024; 10:e27963. [PMID: 38586383 PMCID: PMC10998101 DOI: 10.1016/j.heliyon.2024.e27963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 02/22/2024] [Accepted: 03/08/2024] [Indexed: 04/09/2024] Open
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 P < 0.001). The radiology score models reached AUCs of 0.96 (95% CI 0.94-0.98), 0.90 (95% CI 0.87-0.94), and 0.89 (95% CI 0.84-0.94) during the early, intermediate, and late phases, respectively. The integrated models including demographic and clinical risk factors greatly enhanced the AUC during the intermediate and late phases compared with the values obtained with the radiology score models; however, an improvement in accuracy was not observed. 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.
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Affiliation(s)
- Zhenchen Zhu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ge Hu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhoumeng Ying
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhua Wang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Han
- Department of Epidemiology and Biostatistics, Institute of Basic Medicine Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhengsong Pan
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinlun Tian
- Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Song
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Sui
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lan Song
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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The "Target Sign" in a 46-Year-Old Patient with COVID-19 Pneumonia. Case Rep Radiol 2021; 2021:9956927. [PMID: 34721918 PMCID: PMC8556123 DOI: 10.1155/2021/9956927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 09/27/2021] [Accepted: 10/02/2021] [Indexed: 11/18/2022] Open
Abstract
COVID-19 has various imaging manifestations, most commonly peripheral ground-glass opacities with a basilar posterior predominance. Less common imaging manifestations include consolidations, findings typical of organizing pneumonia, such as “halo” or a “reverse halo” sign, and vascular enlargement. Our case describes a “target sign” on CT, which is uncommon but is increasingly being recognized. The target sign consists of a central nodular opacity with surrounding ground-glass opacity, then a surrounding relatively lucent ring, and a more peripheral ring of consolidation or ground-glass opacification. This may be the sequela of focal vascular enlargement, endothelial injury, microangiopathy, and perivascular inflammation. The case described involves a 46-year-old male who presented with subjective fevers, nonproductive cough, and hypoxia, subsequently diagnosed with COVID-19. CT imaging performed as part of initial work-up revealed multifocal ground-glass opacities scattered throughout the lung parenchyma, as well as multiple target sign lesions. Although it is a rare finding, the target sign, when present, may suggest the diagnosis of COVID-19.
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Gurumurthy B, Das SK, Hiremath R, Shetty S, Hiremath A, Gowda T. Spectrum of atypical pulmonary manifestations of COVID-19 on computed tomography. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2021. [PMCID: PMC7930897 DOI: 10.1186/s43055-021-00448-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Background The typical CT manifestations of COVID-19 pneumonia include ground-glass opacity (GGO) with or without consolidation and superimposed interlobular septal thickening. These are often rounded in morphology and frequently bilateral, multilobar, posterior, peripheral, and basilar in distribution. The various atypical CT features of COVID-19 are seldom described in the literature. The study aims to enumerate the atypical pulmonary CT features in patients with COVID-19 pneumonia in correlation with the disease severity. Results A total of 298 confirmed cases of COVID-19 pneumonia with positive reverse transcription polymerase chain reaction (RT-PCR) who underwent chest CT scans were retrospectively evaluated. The cohort included 234 (78.5%) men and 64 (21.5%) women and the mean age was 53.48 ± 15.74 years. The most common presenting symptoms were fever [n = 197 (66.1%)] and cough [n = 139 (46.6%)]. Out of 298 cases of COVID-19 pneumonia, 218 cases (73.1%) showed typical CT features while 63 cases (21.1%) showed atypical CT features with concurrent classical findings and the remaining 17 cases (5.8%) were normal. Among the atypical CT features, the most common was pulmonary cysts [n = 27 (9%)]. The other features in the order of frequency included pleural effusion [n = 17 (5.7%)], nodules [n = 13 (4.3%)], bull’s eye/target sign[n = 4 (1.3%)], cavitation [n = 3 (1.0%)], spontaneous pneumothorax [n = 2 (0.6%)], hilar lymphadenopathy [n = 2 (0.6%)], spontaneous pneumo-mediastinum with subcutaneous emphysema [n = 1 (0.3%)], Halo sign [n = 1 (0.3%)], empyema [n = 1 (0.3%)] and necrotizing pneumonia with abscess [n = 1 (0.3%)]. Conclusion CT imaging features of COVID-19 pneumonia while in a vast majority of cases is classical, atypical diverse patterns are also encountered. A comprehensive knowledge of various atypical presentations on imaging plays an important role in the early diagnosis and management of COVID-19.
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Shuai W, Chen X, Shan Y, Li W, Ma W, Lu Q, Li D. Clinical Characteristics and CT Findings in 148 Non-COVID-19 Influenza-Like Illness Cases: A Retrospective Control Study. Front Public Health 2021; 9:616963. [PMID: 33634067 PMCID: PMC7900189 DOI: 10.3389/fpubh.2021.616963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
Background: This study was to collect clinical features and computed tomography (CT) findings of Influenza-Like Illness (ILI) cases, and to evaluate the correlation between clinical data and the abnormal chest CT in patients with the Influenza-Like Illness symptoms. Methods: Patients with the Influenza-Like Illness symptoms who attended the emergency department of The Six Medical Center of The PLA General Hospital from February 10 to April 1, 2020 were enrolled. Clinical and imaging data of the enrolled patients were collected and analyzed. The association between clinical characteristics and abnormal chest CT was also analyzed. Results: A total of 148 cases were enrolled in this study. Abnormalities on chest CT were detected in 61/148 (41.2%) patients. The most common abnormal CT features were as follows: patchy consolidation 22/61(36.1%), ground-glass opacities 21/61(34.4%), multifocal consolidations 17/61(27.9%). The advanced age and underlying diseases were significantly associated with abnormal chest CT. Conclusions: Abnormal chest CT is a common condition in Influenza-Like Illness cases. The presence of advanced age and concurrent underlying diseases is significantly associated with abnormal chest CT findings in patients with ILI symptoms. The chest CT characteristic of ILI is different from the manifestation of COVID-19 infection, which is helpful for differential diagnosis.
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Affiliation(s)
- Weizheng Shuai
- Department of Critical Care Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xuxin Chen
- Department of Respiratory and Critical Care Medicine, The Eighth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yi Shan
- Department of Emergency Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wenping Li
- Radiology Department, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wei Ma
- Basic Medical Research Center, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qiaohui Lu
- Radiology Department, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Dawei Li
- Department of Critical Care Medicine, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China
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Marchiori E, Penha D, Nobre LF, Hochhegger B, Zanetti G. Differences and Similarities between the Double Halo Sign, the Chest CT Target Sign and the Reversed Halo Sign in Patients with COVID-19 Pneumonia. Korean J Radiol 2021; 22:672-676. [PMID: 33660464 PMCID: PMC8005353 DOI: 10.3348/kjr.2020.1150] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 09/21/2020] [Accepted: 10/08/2020] [Indexed: 01/15/2023] Open
Affiliation(s)
- Edson Marchiori
- Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
| | - Diana Penha
- Universidade da Beira Interior, Covilhã, Portugal
| | - Luiz Felipe Nobre
- Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Bruno Hochhegger
- Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
| | - Glaucia Zanetti
- Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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Agrò M, Flor N. Single, unilateral halo sign in COVID-19 pneumonia. Clin Imaging 2020; 73:117-118. [PMID: 33383387 PMCID: PMC7764384 DOI: 10.1016/j.clinimag.2020.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 12/04/2020] [Indexed: 11/15/2022]
Affiliation(s)
- Massimiliano Agrò
- School in Radiodiagnostics - Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milano MI, Italy
| | - Nicola Flor
- U.O. di Radiologia - Ospedale L. Sacco ASST Fatebenefratelli Sacco, Via Giovanni Battista Grassi, 74, 20157 Milano MI, Italy.
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