Literature DB >> 18573650

A decision tree for differentiating tuberculous from malignant pleural effusions.

José M Porcel1, Carmen Alemán, Silvia Bielsa, Javier Sarrapio, Tomás Fernández de Sevilla, Aureli Esquerda.   

Abstract

OBJECTIVE: To improve physicians' ability to discriminate tuberculous from malignant pleural effusions through a simple clinical algorithm that avoids pleural biopsy.
DESIGN: We retrospectively compared the clinical and pleural fluid features of 238 adults with pleural effusion who satisfied diagnostic criteria for tuberculosis (n=64) or malignancy (n=174) at one academic center (derivation cohort). Then, we built a decision tree model to predict tuberculosis using the C4.5 algorithm. The model was validated with an independent sample set from another center that included 74 tuberculous and 293 malignant effusions (validation cohort).
RESULTS: Among 12 potential predictor variables, the classification tree analysis selected four discriminant parameters (age>35 years, pleural fluid adenosine deaminase>38U/L, temperature>or=37.8 degrees C, and pleural fluid LDH>320U/L) from the derivation cohort. The generated flowchart had 92.2% sensitivity, 98.3% specificity, and an area under the ROC curve of 0.976 for diagnosing tuberculosis. The corresponding operating characteristics for the validation cohort were 85.1%, 96.9% and 0.958.
CONCLUSIONS: Applying a decision tree analysis that contains simple clinical and laboratory data can help in the differential diagnosis of tuberculous and malignant pleural effusions.

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Year:  2008        PMID: 18573650     DOI: 10.1016/j.rmed.2008.03.001

Source DB:  PubMed          Journal:  Respir Med        ISSN: 0954-6111            Impact factor:   3.415


  14 in total

1.  Predictive models for tuberculous pleural effusions in a high tuberculosis prevalence region.

Authors:  Ersin Demirer; Andrew C Miller; Erdogan Kunter; Zafer Kartaloglu; Scott D Barnett; Elamin M Elamin
Journal:  Lung       Date:  2011-11-06       Impact factor: 2.584

Review 2.  Diagnostic tests for tuberculous pleural effusion.

Authors:  E E McGrath; P B Anderson
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2010-06-16       Impact factor: 3.267

Review 3.  Tuberculous pleural effusion.

Authors:  José M Porcel
Journal:  Lung       Date:  2009-08-13       Impact factor: 2.584

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Journal:  Eur Radiol       Date:  2013-01-10       Impact factor: 5.315

Review 5.  Myelomatous pleural effusion: a case series in a single institution and literature review.

Authors:  Young-Uk Cho; Hyun-Sook Chi; Chan-Jeoung Park; Seongsoo Jang; Eul-Ju Seo; Cheolwon Suh
Journal:  Korean J Lab Med       Date:  2011-10-03

6.  Tuberculosis disease diagnosis using artificial immune recognition system.

Authors:  Shahaboddin Shamshirband; Somayeh Hessam; Hossein Javidnia; Mohsen Amiribesheli; Shaghayegh Vahdat; Dalibor Petković; Abdullah Gani; Miss Laiha Mat Kiah
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Review 7.  Tuberculous pleurisy: an update.

Authors:  Doosoo Jeon
Journal:  Tuberc Respir Dis (Seoul)       Date:  2014-04-25

8.  Novel biomarker analysis of pleural effusion enhances differentiation of tuberculous from malignant pleural effusion.

Authors:  Kuan-Yuan Chen; Po-Hao Feng; Chih-Cheng Chang; Tzu-Tao Chen; Hsiao-Chi Chuang; Chun-Nin Lee; Chien-Ling Su; Lian-Yu Lin; Kang-Yun Lee
Journal:  Int J Gen Med       Date:  2016-06-11

9.  Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

Authors:  Armon Arpagaus; Fabian Christoph Franzeck; George Sikalengo; Robert Ndege; Dorcas Mnzava; Martin Rohacek; Jerry Hella; Klaus Reither; Manuel Battegay; Tracy Renee Glass; Daniel Henry Paris; Farida Bani; Omary Ngome Rajab; Maja Weisser
Journal:  PLoS One       Date:  2020-03-04       Impact factor: 3.240

10.  A retrospective study on the combined biomarkers and ratios in serum and pleural fluid to distinguish the multiple types of pleural effusion.

Authors:  Liyan Lin; Shuguang Li; Qiao Xiong; Hui Wang
Journal:  BMC Pulm Med       Date:  2021-03-19       Impact factor: 3.317

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