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dc.contributor.authorKim, Jin Young
dc.contributor.authorJung, Keum Ji.
dc.contributor.authorYoo, Seung-Jin
dc.contributor.authorYoon, Soon Ho
dc.date2022-08-11T08:08:11.000
dc.date.accessioned2022-08-23T15:45:35Z
dc.date.available2022-08-23T15:45:35Z
dc.date.issued2021-10-22
dc.date.submitted2022-03-17
dc.identifier.citation<p>Kim JY, Jung KJ, Yoo SJ, Yoon SH. Stratifying the early radiologic trajectory in dyspneic patients with COVID-19 pneumonia. PLoS One. 2021 Oct 22;16(10):e0259010. doi: 10.1371/journal.pone.0259010. PMID: 34679127; PMCID: PMC8535425. <a href="https://doi.org/10.1371/journal.pone.0259010">Link to article on publisher's site</a></p>
dc.identifier.issn1932-6203 (Linking)
dc.identifier.doi10.1371/journal.pone.0259010
dc.identifier.pmid34679127
dc.identifier.urihttp://hdl.handle.net/20.500.14038/27562
dc.description.abstractOBJECTIVE: This study aimed to stratify the early pneumonia trajectory on chest radiographs and compare patient characteristics in dyspneic patients with coronavirus disease 2019 (COVID-19). MATERIALS AND METHODS: We retrospectively included 139 COVID-19 patients with dyspnea (87 men, 62.7+/-16.3 years) and serial chest radiographs from January to September 2020. Radiographic pneumonia extent was quantified as a percentage using a previously-developed deep learning algorithm. A group-based trajectory model was used to categorize the pneumonia trajectory after symptom onset during hospitalization. Clinical findings, and outcomes were compared, and Cox regression was performed for survival analysis. RESULTS: Radiographic pneumonia trajectories were categorized into four groups. Group 1 (n = 83, 59.7%) had negligible pneumonia, and group 2 (n = 29, 20.9%) had mild pneumonia. Group 3 (n = 13, 9.4%) and group 4 (n = 14, 10.1%) showed similar considerable pneumonia extents at baseline, but group 3 had decreasing pneumonia extent at 1-2 weeks, while group 4 had increasing pneumonia extent. Intensive care unit admission and mortality were significantly more frequent in groups 3 and 4 than in groups 1 and 2 (P < .05). Groups 3 and 4 shared similar clinical and laboratory findings, but thrombocytopenia ( < 150x103/muL) was exclusively observed in group 4 (P = .016). When compared to groups 1 and 2, group 4 (hazard ratio, 63.3; 95% confidence interval, 7.9-504.9) had a two-fold higher risk for mortality than group 3 (hazard ratio, 31.2; 95% confidence interval, 3.5-280.2), and this elevated risk was maintained after adjusting confounders. CONCLUSION: Monitoring the early radiologic trajectory beyond baseline further prognosticated at-risk COVID-19 patients, who potentially had thrombo-inflammatory responses.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=34679127&dopt=Abstract">Link to Article in PubMed</a></p>
dc.rightsCopyright © 2021 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectCOVID-19
dc.subjectpneumonia
dc.subjectchest radiography
dc.subjectInfectious Disease
dc.subjectRadiology
dc.subjectRespiratory Tract Diseases
dc.subjectVirus Diseases
dc.titleStratifying the early radiologic trajectory in dyspneic patients with COVID-19 pneumonia
dc.typeJournal Article
dc.source.journaltitlePloS one
dc.source.volume16
dc.source.issue10
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1370&amp;context=covid19&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/covid19/363
dc.identifier.contextkey28381363
refterms.dateFOA2022-08-23T15:45:35Z
html.description.abstract<p>OBJECTIVE: This study aimed to stratify the early pneumonia trajectory on chest radiographs and compare patient characteristics in dyspneic patients with coronavirus disease 2019 (COVID-19).</p> <p>MATERIALS AND METHODS: We retrospectively included 139 COVID-19 patients with dyspnea (87 men, 62.7+/-16.3 years) and serial chest radiographs from January to September 2020. Radiographic pneumonia extent was quantified as a percentage using a previously-developed deep learning algorithm. A group-based trajectory model was used to categorize the pneumonia trajectory after symptom onset during hospitalization. Clinical findings, and outcomes were compared, and Cox regression was performed for survival analysis.</p> <p>RESULTS: Radiographic pneumonia trajectories were categorized into four groups. Group 1 (n = 83, 59.7%) had negligible pneumonia, and group 2 (n = 29, 20.9%) had mild pneumonia. Group 3 (n = 13, 9.4%) and group 4 (n = 14, 10.1%) showed similar considerable pneumonia extents at baseline, but group 3 had decreasing pneumonia extent at 1-2 weeks, while group 4 had increasing pneumonia extent. Intensive care unit admission and mortality were significantly more frequent in groups 3 and 4 than in groups 1 and 2 (P < .05). Groups 3 and 4 shared similar clinical and laboratory findings, but thrombocytopenia ( < 150x103/muL) was exclusively observed in group 4 (P = .016). When compared to groups 1 and 2, group 4 (hazard ratio, 63.3; 95% confidence interval, 7.9-504.9) had a two-fold higher risk for mortality than group 3 (hazard ratio, 31.2; 95% confidence interval, 3.5-280.2), and this elevated risk was maintained after adjusting confounders.</p> <p>CONCLUSION: Monitoring the early radiologic trajectory beyond baseline further prognosticated at-risk COVID-19 patients, who potentially had thrombo-inflammatory responses.</p>
dc.identifier.submissionpathcovid19/363
dc.contributor.departmentDepartment of Radiology
dc.source.pagese0259010


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Copyright © 2021 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Except where otherwise noted, this item's license is described as Copyright © 2021 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.