Evidence map›Paper›PMID 39311916›Full record

ArticleEuropean radiology2025

Diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities.

Jong Eun Lee, Hyo-Jae Lee, Gyeryeong Park, Kum Ju Chae, Kwang Nam Jin, Eva Castañer, Benoit Ghaye, Jane P Ko, Helmut Prosch, Scott Simpson and 5 more

Abstract read
In one paragraph

Article in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from 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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Jong Eun LeeDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, Seoul, Korea.
Hyo-Jae LeeDepartment of Radiology, Chonnam National University Hospital Gwangju, Gwangju, Korea.
Gyeryeong ParkDepartment of Radiology, Chonnam National University Hospital Gwangju, Gwangju, Korea.
Kum Ju ChaeDepartment of Radiology, Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea.
Kwang Nam JinDepartment of Radiology, Seoul National University-Seoul Metropolitan Government Boramae Medical Center, Seoul, Korea.
Eva CastañerDepartment of Radiology, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, Sabadell, Spain.
Benoit GhayeDepartment of Radiology, Cliniques Universitaires Saint Luc, Catholic University of Louvain, Brussels, Belgium.
Jane P KoDepartment of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, NY, USA.
Helmut ProschDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna General Hospital, Vienna, Austria.
Scott SimpsonDepartment of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
Anna Rita LariciDepartment of Diagnostic Imaging and Oncological Radiotherapy, Department of Radiological and Hematological Sciences, A. Gemelli University Polyclinic Foundation IRCCS, Catholic University of the Sacred Heart, Rome, Italy.
Jeffrey P KanneDepartment of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Thomas FrauenfelderInstitute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.
Yeon Joo JeongDepartment of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Korea.
Soon Ho YoonDepartment of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea. yshoka@snu.ac.kr.ORCID http://orcid.org/0000-0002-3700-0165

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDistinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities (ILA) on CT can be challenging if clinical information is limited. This study aimed to evaluate the diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from ILA.

methodsThis multi-reader, multi-case study included 60 age- and sex-matched subjects with chest CT scans. There were 40 cases of ILA (20 fibrotic and 20 non-fibrotic) and 20 cases of post-COVID-19 residual abnormalities. Fifteen radiologists from multiple nations with varying levels of experience independently rated suspicion scores on a 5-point scale to distinguish post-COVID-19 residual abnormalities from fibrotic ILA or non-fibrotic ILA. Interobserver agreement was assessed using the weighted κ value, and the scores of individual readers were compared with the consensus of all readers. Receiver operating characteristic curve analysis was conducted to evaluate the diagnostic performance of suspicion scores for distinguishing post-COVID-19 residual abnormalities from ILA and for differentiating post-COVID-19 residual abnormalities from both fibrotic and non-fibrotic ILA.

resultsRadiologists' diagnostic performance for distinguishing post-COVID-19 residual abnormalities from ILA was good (area under the receiver operating characteristic curve (AUC) range, 0.67-0.92; median AUC, 0.85) with moderate agreement (κ = 0.56). The diagnostic performance for distinguishing post-COVID-19 residual abnormalities from non-fibrotic ILA was lower than that from fibrotic ILA (median AUC = 0.89 vs. AUC = 0.80, p = 0.003).

conclusionRadiologists demonstrated good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA, but careful attention is needed to avoid misdiagnosing them as non-fibrotic ILA. KEY POINTS: Question How good are radiologists at differentiating interstitial lung abnormalities (ILA) from changes related to COVID-19 infection? Findings Radiologists had a median AUC of 0.85 in distinguishing post-COVID-19 abnormalities from ILA with moderate agreement (κ = 0.56). Clinical relevance Radiologists showed good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA; nonetheless, caution is needed in distinguishing residual abnormalities from non-fibrotic ILA.

Indexed as

COVID-19Lung Diseases, InterstitialRadiologistsTomography, X-Ray ComputedAdultAgedDiagnosis, DifferentialFemaleHumansLungMaleMiddle AgedObserver VariationSARS-CoV-2COVID-19Diagnostic imagingLung diseases, InterstitialTomography, X-ray computed

Identifiers

PMID39311916
PMCPMC11913901

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.