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Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis

OBJECTIVES: To investigate the association between longitudinal total pulmonary infection volume and volume ratio over time and clinical types in COVID-19 pneumonia patients. METHODS: This retrospective review included 367 patients with COVID-19 pneumonia. All patients underwent CT examination at ba...

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Autores principales: Zhang, Tingting, Li, Xiao, Ji, Xiang, Lu, Jianping, Fang, Xu, Bian, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046497/
https://www.ncbi.nlm.nih.gov/pubmed/33855587
http://dx.doi.org/10.1007/s00330-021-07860-7
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author Zhang, Tingting
Li, Xiao
Ji, Xiang
Lu, Jianping
Fang, Xu
Bian, Yun
author_facet Zhang, Tingting
Li, Xiao
Ji, Xiang
Lu, Jianping
Fang, Xu
Bian, Yun
author_sort Zhang, Tingting
collection PubMed
description OBJECTIVES: To investigate the association between longitudinal total pulmonary infection volume and volume ratio over time and clinical types in COVID-19 pneumonia patients. METHODS: This retrospective review included 367 patients with COVID-19 pneumonia. All patients underwent CT examination at baseline and/or one or more follow-up CT. Patients were categorized into two clinical types (moderate and severe groups). The severe patients were matched to the moderate patients via propensity scores (PS). The association between total pulmonary infection volume and volume ratio and clinical types was analyzed using a generalized additive mixed model (GAMM). RESULTS: Two hundred and seven moderate patients and 160 severe patients were enrolled. The baseline clinical and imaging variables were balanced using PS analysis to avoid patient selection bias. After PS analysis, 172 pairs of moderate patients were allocated to the groups; there was no difference in the clinical and CT characteristics between the two groups (p > 0.05). A total of 332 patients, including 396 CT scans, were assessed. The impact of total pulmonary infection volume and volume ratio with time was significantly affected by clinical types (p for interaction = 0.01 and 0.01, respectively) using GAMM. Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm(3) (95% confidence interval [CI]: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group. CONCLUSIONS: Longitudinal total pulmonary infection volume and volume ratio are independently associated with the clinical types of COVID-19 pneumonia. KEY POINTS: • The impact of total pulmonary infection volume and volume ratio over time was significantly affected by the clinical types (p for interaction = 0.01 and 0.01, respectively) using the GAMM. • Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm(3) (95% CI: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group.
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spelling pubmed-80464972021-04-15 Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis Zhang, Tingting Li, Xiao Ji, Xiang Lu, Jianping Fang, Xu Bian, Yun Eur Radiol Chest OBJECTIVES: To investigate the association between longitudinal total pulmonary infection volume and volume ratio over time and clinical types in COVID-19 pneumonia patients. METHODS: This retrospective review included 367 patients with COVID-19 pneumonia. All patients underwent CT examination at baseline and/or one or more follow-up CT. Patients were categorized into two clinical types (moderate and severe groups). The severe patients were matched to the moderate patients via propensity scores (PS). The association between total pulmonary infection volume and volume ratio and clinical types was analyzed using a generalized additive mixed model (GAMM). RESULTS: Two hundred and seven moderate patients and 160 severe patients were enrolled. The baseline clinical and imaging variables were balanced using PS analysis to avoid patient selection bias. After PS analysis, 172 pairs of moderate patients were allocated to the groups; there was no difference in the clinical and CT characteristics between the two groups (p > 0.05). A total of 332 patients, including 396 CT scans, were assessed. The impact of total pulmonary infection volume and volume ratio with time was significantly affected by clinical types (p for interaction = 0.01 and 0.01, respectively) using GAMM. Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm(3) (95% confidence interval [CI]: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group. CONCLUSIONS: Longitudinal total pulmonary infection volume and volume ratio are independently associated with the clinical types of COVID-19 pneumonia. KEY POINTS: • The impact of total pulmonary infection volume and volume ratio over time was significantly affected by the clinical types (p for interaction = 0.01 and 0.01, respectively) using the GAMM. • Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm(3) (95% CI: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group. Springer Berlin Heidelberg 2021-04-15 2021 /pmc/articles/PMC8046497/ /pubmed/33855587 http://dx.doi.org/10.1007/s00330-021-07860-7 Text en © European Society of Radiology 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Chest
Zhang, Tingting
Li, Xiao
Ji, Xiang
Lu, Jianping
Fang, Xu
Bian, Yun
Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title_full Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title_fullStr Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title_full_unstemmed Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title_short Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis
title_sort generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with covid-19 pneumonia: a propensity score analysis
topic Chest
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046497/
https://www.ncbi.nlm.nih.gov/pubmed/33855587
http://dx.doi.org/10.1007/s00330-021-07860-7
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