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A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors
The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005193/ https://www.ncbi.nlm.nih.gov/pubmed/32029876 http://dx.doi.org/10.1038/s41598-020-59041-z |
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author | Li, Kui Jiang, Zicheng Zhu, Yanan Fan, Chuanqi Li, Tao Ma, Wenqi He, Yingli |
author_facet | Li, Kui Jiang, Zicheng Zhu, Yanan Fan, Chuanqi Li, Tao Ma, Wenqi He, Yingli |
author_sort | Li, Kui |
collection | PubMed |
description | The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features were collected. Patients were assigned to mild/moderate group or advanced group depending on the lesion severity on chest CT, severe chest CT lesion refers to the moderately dense or less diffuse lesion that exceeds the total volume of one lung, or the dense fusion lesion greater than one third of the volume of one lung, or the lesion with cavity diameter ≥4 cm. Independent risk factors for severe lesions were determined by univariate and multivariate logistic regression analyses, and the diagnostic efficiency of the risk factors was assessed by receiver operating characteristic curve (ROC). Chest CT demonstrated that there were 285 (61.56%) cases with severe lesions; multivariate Logistic regression analysis showed dust exposure [odds ratio (OR) = 4.108, 95% confidence interval (CI) 2.416–6.986], patient classification (OR = 1.792, 95% CI 1.067–3.012), age (OR = 1.018, 95% CI 1.005–1.030), and albumin-globulin ratio (OR = 0.179, 95% CI 0.084–0.383) to be independently correlated with severe lesions on chest CT. ROC curve analysis showed the cutoff values of age, albumin-globulin ratio and combined score to be 39 years, 0.918 and −0.085, respectively. The predictive value of combined score area under the curve 0.753 (95% CI 0.708–0.798) was higher than that of any single factor. The combined score of these four factors further improved the predictive efficacy. |
format | Online Article Text |
id | pubmed-7005193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70051932020-02-18 A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors Li, Kui Jiang, Zicheng Zhu, Yanan Fan, Chuanqi Li, Tao Ma, Wenqi He, Yingli Sci Rep Article The objective of the present investigation was to explore the influencing factors and value of computed tomography (CT) for diagnosing severe chest lesions in active pulmonary tuberculosis (APTB). This retrospective investigation included 463 patients diagnosed with APTB. Relevant clinical features were collected. Patients were assigned to mild/moderate group or advanced group depending on the lesion severity on chest CT, severe chest CT lesion refers to the moderately dense or less diffuse lesion that exceeds the total volume of one lung, or the dense fusion lesion greater than one third of the volume of one lung, or the lesion with cavity diameter ≥4 cm. Independent risk factors for severe lesions were determined by univariate and multivariate logistic regression analyses, and the diagnostic efficiency of the risk factors was assessed by receiver operating characteristic curve (ROC). Chest CT demonstrated that there were 285 (61.56%) cases with severe lesions; multivariate Logistic regression analysis showed dust exposure [odds ratio (OR) = 4.108, 95% confidence interval (CI) 2.416–6.986], patient classification (OR = 1.792, 95% CI 1.067–3.012), age (OR = 1.018, 95% CI 1.005–1.030), and albumin-globulin ratio (OR = 0.179, 95% CI 0.084–0.383) to be independently correlated with severe lesions on chest CT. ROC curve analysis showed the cutoff values of age, albumin-globulin ratio and combined score to be 39 years, 0.918 and −0.085, respectively. The predictive value of combined score area under the curve 0.753 (95% CI 0.708–0.798) was higher than that of any single factor. The combined score of these four factors further improved the predictive efficacy. Nature Publishing Group UK 2020-02-06 /pmc/articles/PMC7005193/ /pubmed/32029876 http://dx.doi.org/10.1038/s41598-020-59041-z Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Li, Kui Jiang, Zicheng Zhu, Yanan Fan, Chuanqi Li, Tao Ma, Wenqi He, Yingli A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title | A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title_full | A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title_fullStr | A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title_full_unstemmed | A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title_short | A valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
title_sort | valuable computed tomography-based new diagnostic tool for severe chest lesions in active pulmonary tuberculosis: combined application of influencing factors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7005193/ https://www.ncbi.nlm.nih.gov/pubmed/32029876 http://dx.doi.org/10.1038/s41598-020-59041-z |
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