Predictive Models for Tuberculous Pleural Effusions in a High Tuberculosis Prevalence Region

Overview

Journal Lung

Specialty Pulmonary Medicine

Date 2011 Nov 8

PMID 22057296

Citations 5

Authors

Ersin Demirer

Andrew C Miller

Erdogan Kunter

Zafer Kartaloglu

Scott D Barnett

Elamin M Elamin

Affiliations

Soon will be listed here.

Abstract

Background: Patients with pleural effusions who reside in geographic areas with a high prevalence of tuberculosis frequently have similar clinical manifestations of other diseases. The aim of our study was to develop a simple but accurate clinical score for differential diagnosis of tuberculosis pleural effusion (TPE) from non-TB pleural effusion (NTPE).

Methods: This was an unblinded, prospective study of Turkish patients 18 years of age or older with pleural effusion of indeterminate etiology conducted from June 2003 to June 2005. Unconditional logistic regression models were used to discriminate TPE cases from NTPE cases. Standard errors for the area under the curve (AUC) were calculated using the Mann-Whitney method. Data were statistically significance if two-tailed P < 0.05.

Results: A total of 63.3% (157/248) of the patients had TPE while 36.7% (91/248) of the patients had other etiologies for pleural effusions. We were able to provide a predictive model of TPE that included age <47 years and either pleural fluid adenosine deaminase enzyme (PADA) >35 U/l or pleural serum protein ratio >0.710. However, only the combination of age <47 and PADA >35 U/l was significant (odds ratio [OR]: 7.46; 95% confidence interval [CI]: 3.99-13.96). The generated summary score (range = 0-6) was significantly predictive of TPE (OR: 2.91; 95% CI: 2.18-3.89) and with high AUC (0.79).

Conclusion: We propose an affordable model that includes age <47 years and PADA >35 U/l for timely diagnosis of TPE in geographical regions with a high prevalence of TB.

Citing Articles

Diagnostic scoring systems for tuberculous pleural effusion in patients with lymphocyte-predominant exudative pleural profile: A development study.

Kaewwinud J, Pienchitlertkajorn S, Koomtanapat K, Lumkul L, Wongyikul P, Phinyo P Heliyon. 2024; 10(1):e23440.

PMID: 38332886 PMC: 10851221. DOI: 10.1016/j.heliyon.2023.e23440.

Development and validation of a prediction model to assess the probability of tuberculous pleural effusion in patients with unexplained pleural effusion.

Lei X, Wang J, Yang Z Sci Rep. 2023; 13(1):10904.

PMID: 37407665 PMC: 10322972. DOI: 10.1038/s41598-023-38048-2.

Application of Adenosine Deaminase and γ-Interferon Release Assay in Pleural Fluid for the Diagnosis of Tuberculous Pleural Effusion in Patients Over 40 Years Old.

Li Z, Chen J, Zeng J, Shi P, Xiong X, Wang M Infect Drug Resist. 2023; 16:1009-1018.

PMID: 36824067 PMC: 9942497. DOI: 10.2147/IDR.S400838.

Tuberculous pleural effusion prediction using ant colony optimizer with grade-based search assisted support vector machine.

Li C, Hou L, Pan J, Chen H, Cai X, Liang G Front Neuroinform. 2023; 16:1078685.

PMID: 36601381 PMC: 9806141. DOI: 10.3389/fninf.2022.1078685.

Developing Predictive Models to Determine Patients in End-of-Life Care in Administrative Datasets.

Swerdel J, Reps J, Fife D, Ryan P Drug Saf. 2020; 43(5):447-455.

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