ArticleJournal of thoracic disease2022
Clinical diagnostic algorithm in defining tuberculous unilateral pleural effusion in high tuberculosis burden areas short of diagnostic tools.
Article in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH.Respiratory research · 2025Article
- The diagnostic value of hydroxyproline combined with tuberculosis infection T lymphocyte spot assay in pulmonary tuberculosis.Journal of thoracic disease · 2024Article
- Performance verification of a biochemical detection system for hydrothorax and ascites and clinical diagnostic accuracy evaluation of exudate and tuberculous effusion.Journal of thoracic disease · 2024Article
- B and T lymphocyte attenuator as a C-reactive protein and IgA associated auxiliary diagnostic marker for pulmonary tuberculosis: a case-control study.Annals of translational medicine · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Empirical treatment was introduced when pathological or microbiological results of tuberculosis (TB) were not available. This report was designed to evaluate an algorithm based on empirical treatment in defining tuberculous pleural effusion (TPE) in high burden areas but short of diagnostic tools. Methods: In this retrospective study, a total of 924 eligible patients were enrolled and 203 (22.0%) were primarily diagnosed as TPE by our diagnostic algorithm based on effusion characteristics [adenosine deaminase (ADA) and exudate] and immunoassays [purified protein derivative (PPD), Results: A total of 177 (94.65%) cases benefited from standard treatment, 5 (2.67%) failed due to early termination or drug resistance, and 5 (2.67%) were finally confirmed as misdiagnosis. Regarding diagnostic efficacy, 72 (30.13%) patients received four TB tests, and the combination of the four tests could increase the diagnosis of TPE. Besides, receiving operating characteristics curve (ROC) analysis revealed that our algorithm was the best method to differentiate TPE from malignant pleural effusion (MPE) with higher sensitivity and specificity than other serum markers. Conclusions: This clinical diagnostic algorithm was an efficient and available method for the diagnosis of TPE. This diagnostic algorithm should be implemented in regions with high TB prevalence but short of diagnostic tools.
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