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...

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Bibliographic Details
Published inScientific reports Vol. 10; no. 1; p. 2023
Main Authors Li, Kui, Jiang, Zicheng, Zhu, Yanan, Fan, Chuanqi, Li, Tao, Ma, Wenqi, He, Yingli
Format Journal Article
LanguageEnglish
Published England Nature Publishing Group 06.02.2020
Nature Publishing Group UK
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Summary: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.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-59041-z