SynthesisChest2020
Chest CT Imaging Signature of Coronavirus Disease 2019 Infection: In Pursuit of the Scientific Evidence.
Synthesis in Chest, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
66 citing papers in PubMed, 2 syntheses or guidelines pooled it, 121 citations in OpenAlex.
- Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review.Computer methods and programs in biomedicine · 2022Pooled it
- Pulmonary embolism in patients with COVID-19 and value of D-dimer assessment: a meta-analysis.European radiology · 2021Pooled it
- Prediction of potential severe coronavirus disease 2019 patients based on CT radiomics: A retrospective study.Medical physics · 2022Trial
- Visual and AI-Based Assessment of COVID-19 Pneumonia: Practicability and Reproducibility of an Established Semi-Quantitative Chest CT Scoring System.Diagnostics (Basel, Switzerland) · 2025Article
- Prognostic value of functional CT imaging in COVID-ARDS: a two-centre prospective observational study.Respiratory research · 2025Observational
- Incidence of secondary pericardial effusions associated with different etiologies: a comprehensive review of literature.Journal of cardiothoracic surgery · 2025Review
- Severe acute respiratory syndrome coronavirus 2 infection unevenly impacts metabolism in the coronal periphery of the lungs.iScience · 2025Article
- Lung abnormalities on computed tomography of Vietnamese patients with COVID-19 and the association with medical variables.IJID regions · 2024Article
- ERS International Congress 2023: highlights from the Thoracic Oncology Assembly.ERJ open research · 2024Article
- COVID-19 progression in hospitalized patients using follow-upJournal of thoracic disease · 2023Article
- New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023Article
- COVID-19 Pneumonia with Migratory Pattern in Agammaglobulinemic Patients: A Report of Two Cases and Review of Literature.Tomography (Ann Arbor, Mich.) · 2023Review
- Research on the Application of Artificial Intelligence in Public Health Management: Leveraging Artificial Intelligence to Improve COVID-19 CT Image Diagnosis.International journal of environmental research and public health · 2023Article
- Reduction in Chest CT Severity and Improved Hospital Outcomes in SARS-CoV-2 Omicron Compared with Delta Variant Infection.Radiology · 2023Article
- Cavitary lung lesion as sequelae of mild COVID-19 in a patient with HIV.Clinical infection in practice · 2023Article
- Multi-center Integrating Radiomics, Structured Reports, and Machine Learning Algorithms for Assisted Classification of COVID-19 in Lung Computed Tomography.Journal of medical and biological engineering · 2023Article
- Sarcoidosis and COVID-19: At the Cross-Road between Immunopathology and Clinical Manifestation.Biomedicines · 2022Review
- Changes in diagnostic usefulness of the JRS scoring system in COVID-19 pneumonia by SARS-CoV-2 vaccination.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022Article
- Observational
- Air trapping in COVID-19 patients following hospital discharge: retrospective evaluation with paired inspiratory/expiratory thin-section CT.European radiology · 2022Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on by
- Commented on byResponse.2021
Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChest CT may be used for the diagnosis of coronavirus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19. RESEARCH QUESTION: What is the chest CT imaging signature of COVID-19 infection? STUDY DESIGN AND
methodsA systematic literature search was performed for original studies on chest CT imaging findings in patients with COVID-19. Methodologic quality of studies was evaluated. Pooled prevalence of chest CT imaging findings were calculated with the use of a random effects model in case of between-study heterogeneity (predefined as I
resultsTwenty-eight studies were included. The median number of patients with COVID-19 per study was 124 (range, 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range, >76.3%-100%). Twenty-seven of the studies (96%) had a retrospective design. Methodologic quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (eight studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT imaging findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT imaging findings ranged between 10.5% and 63.2%.
interpretationStudies on chest CT imaging findings in COVID-19 suffer from methodologic quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT imaging findings appear to be suggestive of COVID-19, but normal chest CT imaging findings do not exclude COVID-19, not even in symptomatic patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.