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CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods

BACKGROUND: Lung involvement in COVID-19 can be quantified by chest CT scan with some triage and prognostication value. Optimizing initial triage of patients could help decrease adverse health impacts of the disease through better clinical management. At least 6 CT severity score (CTSS) systems have...

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Autores principales: Almasi Nokiani, Alireza, Shahnazari, Razieh, Abbasi, Mohammad Amin, Divsalar, Farshad, Bayazidi, Marzieh, Sadatnaseri, Azadeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116070/
http://dx.doi.org/10.1186/s43055-022-00781-5
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author Almasi Nokiani, Alireza
Shahnazari, Razieh
Abbasi, Mohammad Amin
Divsalar, Farshad
Bayazidi, Marzieh
Sadatnaseri, Azadeh
author_facet Almasi Nokiani, Alireza
Shahnazari, Razieh
Abbasi, Mohammad Amin
Divsalar, Farshad
Bayazidi, Marzieh
Sadatnaseri, Azadeh
author_sort Almasi Nokiani, Alireza
collection PubMed
description BACKGROUND: Lung involvement in COVID-19 can be quantified by chest CT scan with some triage and prognostication value. Optimizing initial triage of patients could help decrease adverse health impacts of the disease through better clinical management. At least 6 CT severity score (CTSS) systems have been proposed. We aimed to evaluate triage and prognostication performance of seven different CTSSs, including one proposed by ourselves, in hospitalized COVID-19 patients diagnosed by positive polymerase chain reaction (PCR). RESULTS: After exclusion of 14 heart failure and significant preexisting pulmonary disease patients, 96 COVID-19, PCR-positive patients were included into our retrospective study, admitted from February 20, 2020, to July 22. Their mean age was 63.6 ± 17.4 years (range 21–88, median 67). Fifty-seven (59.4%) were men, and 39 (40.6%) were women. All CTSSs showed good interrater reliability as calculated intraclass correlation coefficients (ICCs) between two radiologists were 0.764–0.837. Those CTSSs with more numerous segmentations showed the best ICCs. As judged by area under curve (AUC) for each receiver operator characteristic (ROC) curve, only three CTSSs showed acceptable AUCs (AUC = 0.7) for triage of severe/critical patients. All CTSSs showed acceptable AUCs for prognostication (AUCs = 0.76–0.79). Calculated AUCs for different CTSSs were not significantly different for triage and for prediction of severe/critical disease, but some difference was shown for prediction of critical disease. CONCLUSIONS: Men are probably affected more frequently than women by COVID-19. Quantification of lung disease in COVID-19 is a readily available and easy tool to be used in triage and prognostication, but we do not advocate its use in heart failure or chronic respiratory disease patients. The scoring systems with more numerous segmentations are recommended if any future imaging for comparison is contemplated. CTSS performance in triage was much lower than earlier reports, and only three CTSSs showed acceptable AUCs in this regard. CTSS performed better for prognostic purposes than for triage as all 7 CTSSs showed acceptable AUCs in both types of prognostic ROC curves. There is not much difference among performance of different CTSSs.
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spelling pubmed-91160702022-05-18 CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods Almasi Nokiani, Alireza Shahnazari, Razieh Abbasi, Mohammad Amin Divsalar, Farshad Bayazidi, Marzieh Sadatnaseri, Azadeh Egypt J Radiol Nucl Med Research BACKGROUND: Lung involvement in COVID-19 can be quantified by chest CT scan with some triage and prognostication value. Optimizing initial triage of patients could help decrease adverse health impacts of the disease through better clinical management. At least 6 CT severity score (CTSS) systems have been proposed. We aimed to evaluate triage and prognostication performance of seven different CTSSs, including one proposed by ourselves, in hospitalized COVID-19 patients diagnosed by positive polymerase chain reaction (PCR). RESULTS: After exclusion of 14 heart failure and significant preexisting pulmonary disease patients, 96 COVID-19, PCR-positive patients were included into our retrospective study, admitted from February 20, 2020, to July 22. Their mean age was 63.6 ± 17.4 years (range 21–88, median 67). Fifty-seven (59.4%) were men, and 39 (40.6%) were women. All CTSSs showed good interrater reliability as calculated intraclass correlation coefficients (ICCs) between two radiologists were 0.764–0.837. Those CTSSs with more numerous segmentations showed the best ICCs. As judged by area under curve (AUC) for each receiver operator characteristic (ROC) curve, only three CTSSs showed acceptable AUCs (AUC = 0.7) for triage of severe/critical patients. All CTSSs showed acceptable AUCs for prognostication (AUCs = 0.76–0.79). Calculated AUCs for different CTSSs were not significantly different for triage and for prediction of severe/critical disease, but some difference was shown for prediction of critical disease. CONCLUSIONS: Men are probably affected more frequently than women by COVID-19. Quantification of lung disease in COVID-19 is a readily available and easy tool to be used in triage and prognostication, but we do not advocate its use in heart failure or chronic respiratory disease patients. The scoring systems with more numerous segmentations are recommended if any future imaging for comparison is contemplated. CTSS performance in triage was much lower than earlier reports, and only three CTSSs showed acceptable AUCs in this regard. CTSS performed better for prognostic purposes than for triage as all 7 CTSSs showed acceptable AUCs in both types of prognostic ROC curves. There is not much difference among performance of different CTSSs. Springer Berlin Heidelberg 2022-05-18 2022 /pmc/articles/PMC9116070/ http://dx.doi.org/10.1186/s43055-022-00781-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Almasi Nokiani, Alireza
Shahnazari, Razieh
Abbasi, Mohammad Amin
Divsalar, Farshad
Bayazidi, Marzieh
Sadatnaseri, Azadeh
CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title_full CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title_fullStr CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title_full_unstemmed CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title_short CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
title_sort ct severity score in covid-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116070/
http://dx.doi.org/10.1186/s43055-022-00781-5
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