Diagnostic accuracy and cellular origin of pleural fluid CXCR3 ligands for tuberculous pleural effusion.

BACKGROUND: Pleural biomarkers represent potential diagnostic tools for tuberculous pleural effusion (TPE) due to their advantages of low cost, short turnaround time, and less invasiveness. This study evaluated the diagnostic accuracy of two CXCR3 ligands, C-X-C motif chemokine ligand 9 (CXCL9) and CXCL11, for TPE. In addition, we investigated the cellular origins and biological roles of CXCL9 and CXCL11 in the development of TPE. METHODS: This double-blind study prospectively enrolled patients with undiagnosed pleural effusion from two centers (Hohhot and Changshu) in China. Pleural fluid on admission was obtained and levels of CXCL9 and CXCL11 were measured by an enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve and the decision curve analysis (DCA) were used to evaluate their diagnostic accuracy and net benefit, respectively. THP-1 cell-derived macrophages were treated with Bacillus Calmette-Guérin (BCG), and quantitative real-time PCR (qRT-PCR) and ELISA were used to determine the mRNA and protein levels of CXCL9 and CXCL11. The chemoattractant activities of CXCL9 and CXCL11 for T helper (Th) cells were analyzed by a transwell assay. RESULTS: One hundred and fifty-three (20 TPEs and 133 non-TPEs) patients were enrolled in the Hohhot Center, and 58 (13 TPEs and 45 non-TPEs) were enrolled in the Changshu Center. In both centers, we observed increased CXCL9 and CXCL11 in TPE patients. The areas under the ROC curves (AUCs) of pleural CXCL9 and CXCL11 in the Hohhot Center were 0.70 (95 % CI: 0.55-0.85) and 0.68 (95 % CI: 0.52-0.84), respectively. In the Changshu Center, the AUCs of CXCL9 and CXCL11 were 0.96 (95 % CI: 0.92-1.00) and 0.97 (95 % CI: 0.94-1.00), respectively. The AUCs of CXCL9 and CXCL11 decreased with the advancement of age. The decision curves of CXCL9 and CXCL11 showed net benefits in both centers. CXCL9 and CXCL11 were upregulated in BCG-treated macrophages. Pleural fluid from TPE and conditioned medium from BCG-treated macrophages were chemotactic for Th cells. Anti-CXCL9 or CXCL11 neutralizing antibodies could partly block the chemotactic activity. CONCLUSIONS: Pleural CXCL9 and CXCL11 are potential diagnostic markers for TPE, but their diagnostic accuracy is compromised in elderly patients. CXCL9 and CXCL11 can promote the migration of peripheral Th cells, thus representing a therapeutic target for the treatment of TPE.

Clinical significance of pleural fluid lactate dehydrogenase/adenosine deaminase ratio in the diagnosis of tuberculous pleural effusion.

BACKGROUND: Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE. METHODS: The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE. RESULTS: The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P < 0.01) and MPE group (10 U/L, P < 0.001). The median pfADA level in the TPE group was 41 (32, 52) U/L; it was lowest in the MPE group at 9 (7, 12) U/L and highest in the PPE group at 43 (23, 145) U/L. The pfLDH level in the PPE group was 2542 (1109, 6219) U/L, which was significantly higher than that in the TPE group 449 (293, 664) U/L. In the differential diagnosis between TPE and non-TPE, the AUC of pfLDH/pfADA for diagnosing TPE was the highest at 0.946 (0.925, 0.966), with an optimal cutoff value of 23.20, sensitivity of 93.9%, specificity of 87.0%, and Youden index of 0.809. In the differential diagnosis of TPE and PPE, the AUC of pfLDH/pfADA was the highest at 0.964 (0.939, 0.989), with an optimal cutoff value of 24.32, sensitivity of 94.6%, and specificity of 94.4%; this indicated significantly better diagnostic efficacy than that of the single index of pfLDH. In the differential diagnosis between TPE and MPE, the AUC of pfLDH/pfADA was 0.926 (0.896, 0.956), with a sensitivity of 93.4% and specificity of 80.0%; this was not significantly different from the diagnostic efficacy of pfADA. CONCLUSIONS: Compared with single biomarkers, pfLDH/pfADA has higher diagnostic value for TPE and can identify patients with TPE early, easily, and economically.

Biomarkers for distinguishing tuberculous pleural effusion from non-tuberculosis effusion: a retrospective study.

BACKGROUND: Pleural effusion (PE) is a common clinical feature that presents a diagnostic challenge for clinicians. In this retrospective study, we aimed to assess the biomarkers, ratios, and multiple indicators in serum and Pleural effusion for the differential diagnosis of tuberculous pleural effusion (TPE) from non-tuberculosis effusion (non-TPE). METHODS: The participants, who were divided into two groups: TPE and non-TPE (MPE and PPE), from Ningbo First Hospital, were incorporated in this study. The clinical and laboratory features were collected and analyzed using logistic regression analysis. Twelve biomarkers and their ratios in serum and PE were investigated for TPE versus non-TPE. Additionally, the value of multiple indicators for joint diagnosis was estimated. RESULTS: Biomarkers and ratios showed good diagnostic performance. The five variables including Serum ADA, IGRA, Effusion ADA, Effusion ADA/Serum ADA and Effusion LDH/Effusion ADA were identified as valuable parameters for differential diagnosis of TPE from non-TPE. The combined diagnosis of the five indexes yielded the highest diagnostic accuracy for TPE with an AUC (0.919), sensitivity (90.30%), and specificity (94.50%). CONCLUSIONS: The biomarkers and ratios demonstrated strong diagnostic performance, and the utilization of multiple indicators for joint diagnosis can improve the diagnostic efficacy of tuberculous pleurisy.

Toll-like Receptor 2 Mediates VEGF Overexpression and Mesothelial Hyperpermeability in Tuberculous Pleural Effusion.

Toll-like receptor (TLR) is essential for the immune response to Mycobacterium tuberculosis (MTB) infection. However, the mechanism whereby TLR mediates the MTB-induced pleural mesothelial hyperpermeability in tuberculous pleural effusion (TBPE) remains unclear. Pleural effusion size and pleural fluid levels of vascular endothelial growth factor (VEGF) and soluble TLR2 (sTLR2) in patients with TBPE (n = 36) or transudative pleural effusion (TPE, n = 16) were measured. The effects of MTB H37Ra (MTBRa) on pleural mesothelial permeability and the expression of VEGF and zonula occludens (ZO)-1 in human pleural mesothelial cells (PMCs) were assessed. Levels of VEGF and sTLR2 were significantly elevated in TBPE compared to TPE. Moreover, effusion VEGF levels correlated positively, while sTLR2 values correlated negatively, with pleural effusion size in TBPE. In human PMCs, MTBRa substantially activated JNK/AP-1 signaling and upregulated VEGF expression, whereas knockdown of TLR2 remarkably inhibited MTBRa-induced JNK phosphorylation and VEGF overexpression. Additionally, both MTBRa and VEGF markedly reduced ZO-1 expression and induced pleural mesothelial permeability, while TLR2 silencing or pretreatment with anti-VEGF antibody significantly attenuated the MTBRa-triggered effects. Collectively, TLR2 mediates VEGF overproduction and downregulates ZO-1 expression in human PMCs, leading to mesothelial hyperpermeability in TBPE. Targeting TLR2/VEGF pathway may confer a potential treatment strategy for TBPE.

Development and validation of a prediction model for tuberculous pleural effusion: a large cohort study and external validation.

BACKGROUND: Distinguishing tuberculous pleural effusion (TPE) from non-tuberculosis (TB) benign pleural effusion (BPE) remains to be a challenge in clinical practice. The aim of the present study was to develop and validate a novel nomogram for diagnosing TPE. METHODS: In this retrospective analysis, a total of 909 consecutive patients with TPE and non-TB BPE from Ningbo First Hospital were divided into the training set and the internal validation set at a ratio of 7:3, respectively. The clinical and laboratory features were collected and analyzed by logistic regression analysis. A diagnostic model incorporating selected variables was developed and was externally validated in a cohort of 110 patients from another hospital. RESULTS: Six variables including age, effusion lymphocyte, effusion adenosine deaminase (ADA), effusion lactatedehy drogenase (LDH), effusion LDH/effusion ADA, and serum white blood cell (WBC) were identified as valuable parameters used for developing a nomogram. The nomogram showed a good diagnostic performance in the training set. A novel scoring system was then established based on the nomogram to distinguish TPE from non-TB BPE. The scoring system showed good diagnostic performance in the training set [area under the curve (AUC) (95% confidence interval (CI)), 0.937 (0.917-0.957); sensitivity, 89.0%, and specificity, 89.5%], the internal validation set [AUC (95%CI), 0.934 (0.902-0.966); sensitivity, 88.7%, and specificity, 90.3%], and the external validation set [(AUC (95%CI), 0.941 (0.891-0.991); sensitivity, 93.6%, and specificity, 87.5%)], respectively. CONCLUSIONS: The study developed and validated a novel scoring system based on a nomogram originated from six clinical parameters. The novel scoring system showed a good diagnostic performance in distinguishing TPE from non-TB BPE and can be conveniently used in clinical settings.

A scoring model for diagnosis of tuberculous pleural effusion.

BACKGROUND: Due to the low efficiency of a single clinical feature or laboratory variable in the diagnosis of tuberculous pleural effusion (TBPE), the diagnosis of TBPE is still challenging. This study aimed to build a scoring diagnostic model based on laboratory variables and clinical features to differentiate TBPE from non-tuberculous pleural effusion (non-TBPE). METHODS: A retrospective study of 125 patients (63 with TBPE; 62 with non-TBPE) was undertaken. Univariate analysis was used to select the laboratory and clinical variables relevant to the model composition. The statistically different variables were selected to undergo binary logistic regression. Variables B coefficients were used to define a numerical score to calculate a scoring model. A receiver operating characteristic (ROC) curve was used to calculate the best cut-off value and evaluate the performance of the model. Finally, we add a validation cohort to verify the model. RESULTS: Six variables were selected in the scoring model: Age ≤ 46 years old (4.96 points), Male (2.44 points), No cancer (3.19 points), Positive T-cell Spot (T-SPOT) results (4.69 points), Adenosine Deaminase (ADA) ≥ 24.5U/L (2.48 point), C-reactive Protein (CRP) ≥ 52.8 mg/L (1.84 points). With a cut-off value of a total score of 11.038 points, the scoring model's sensitivity, specificity, and accuracy were 93.7%, 96.8%, and 99.2%, respectively. And the validation cohort confirms the model with the sensitivity, specificity, and accuracy of 92.9%, 93.3%, and 93.1%, respectively. CONCLUSION: The scoring model can be used in differentiating TBPE from non-TBPE.

Diagnostic accuracy of pleural fluid lactate dehydrogenase to adenosine deaminase ratio for tuberculous pleural effusion: an analysis of two cohorts.

BACKGROUND: This study aimed to evaluate the diagnostic accuracy of pleural fluid (PF) lactate dehydrogenase (LDH) to adenosine deaminase (ADA) (LDH/ADA) ratio for tuberculous pleural effusion (TPE). Especially to explore whether the LDH/ADA ratio provides added diagnostic value to ADA. METHODS: The diagnostic accuracy of PF LDH/ADA ratio and ADA for TPE was evaluated in two cohorts, named the BUFF (Biomarkers for patients with Undiagnosed pleural eFFusion) cohort (62 with TPE and 194 with non-TPE) and the SIMPLE (a Study Investigating Markers in PLeural Effusion) cohort (33 with TPE and 177 with non-TPE). Receiver operating characteristic (ROC) curve and decision curve were used to measure the diagnostic accuracy of the PF LDH/ADA ratio. The added diagnostic value of the LDH/ADA ratio to ADA was evaluated with net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: The area under the ROC curves (AUCs) of PF ADA and LDH/ADA ratio in the BUFF cohort were 0.76 and 0.74, respectively. In the SIMPLE cohort, the AUCs of PF ADA and LDH/ADA ratio were 0.80 and 0.85, respectively. The decision curves of PF LDH/ADA and ADA were close in both the BUFF and SIMPLE cohorts. The NRI and IDI analyses did not reveal any added diagnostic value of LDH/ADA to ADA. CONCLUSIONS: PF LDH/ADA ratio has moderate diagnostic accuracy for TPE. It does not provide added diagnostic value beyond ADA. The current evidence does not support LDH/ADA ratio for diagnosing TPE.

Diagnostic performance of D-dimer in predicting pulmonary embolism in tuberculous pleural effusion patients.

BACKGROUND: Tuberculous pleural effusion (TPE) patients usually have elevated D-dimer levels. The diagnostic performance of D-dimer in predicting pulmonary embolism (PE) in the TPE population is unclear. This study aimed to assess the diagnostic performance of D-dimer for PE in the TPE population and explore its potential mechanism. METHODS: We retrospectively analysed patients who were admitted to Xinhua Hospital and Weifang Respiratory Disease Hospital with confirmed TPE between March 2014 and January 2020. D-dimer levels were compared between patients with and without PE. To test the diagnostic performance of D-dimer in predicting PE, receiver operating characteristic curve analysis was performed. Positive predictive value (PPV) and negative predictive value (NPV) were also reported. To explore the potential mechanism of PE in TPE, inflammatory biomarkers were compared between PE and non-PE patients. RESULTS: This study included 248 patients (170 males and 78 females) aged 43 ± 20.6 years. Elevated D-dimer levels (≥ 0.5 mg/L) were detected in 186/248 (75%) patients. Of the 150 patients who underwent computed tomography pulmonary angiography, 29 were diagnosed with PE. Among the TPE population, the PE patients had significantly higher D-dimer levels than the non-PE patients (median, 1.06 mg/L vs. 0.84 mg/L, P < 0.05). The optimal cut-off value for D-dimer in predicting PE in TPE was 1.18 mg/L, with a sensitivity of 89.7% and a specificity of 77.8% (area under curve, 0.893; 95% confidence interval 0.839-0.947; P < 0.01). The PPV was 49.1%, while the NPV was 96.9% at a D-dimer cut-off of 1.18 mg/L for PE. PE patients had lower median WBC and interleukin (IL)-8 values (5.14 × 109/L vs. 6.1 × 109/L, P < 0.05; 30.2 pg/ml vs. 89.7 pg/ml, P < 0.05) but a higher median IL-2 receptor value (1964.8 pg/ml vs. 961.2 pg/ml, P < 0.01) than those in the non-PE patients. CONCLUSIONS: D-dimer is an objective biomarker for predicting PE in patients with TPE. A D-dimer cut-off of 1.18 mg/L in the TPE population may reduce unnecessary radiological tests due to its excellent sensitivity, specificity, and NPV for PE. The imbalance of prothrombotic and antithrombotic cytokines may partly be attributed to the formation of pulmonary emboli in patients with TPE.

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

PURPOSE: Pleural effusion (PE) is a common clinical manifestation, and millions of people suffer from pleural disease. Herein, this retrospective study was performed to evaluate the biomarkers and ratios in serum and pleural fluid (PF) for the differential diagnosis of the multiple types of PE and search for a new diagnostic strategy for PE. METHODS: In-patients, who developed tuberculous PE (TPE), malignant PE (MPE), complicated parapneumonic effusion (CPPE), uncomplicated PPE (UPPE), or PE caused by connective tissue diseases (CTDs) and underwent thoracentesis at Peking University People's Hospital from November 2016 to April 2019, were included in this study. Eleven biomarkers and their ratios in serum and PF were investigated and compared between pairs of the different PE groups, and a decision-tree was developed. RESULTS: Totally 112 PE cases, including 25 MPE, 33 TPE, 19 CPPE, 27 UPPE, and 8 PE caused by CTDs, were reviewed. Biomarkers and ratios showed good diagnostic performance with high area under the curve values, sensitivities, and specificities for the differential diagnosis of the multiple types of PE. According to the decision-tree analysis, the combination of adenosine deaminase (ADA), serum albumin, serum lactate dehydrogenase, total protein, PF-LDH/ADA, and PF-LDH/TP provided the best predictive capacity with an overall accuracy of 84.8%; the sensitivity and specificity for TPE diagnosis were 100% and 98.7%, respectively. CONCLUSION: The biomarkers and ratios showed good diagnostic performance, and a decision-tree with an overall accuracy of 84.8% was developed to differentiate the five types of PE in clinical settings.

GC-MS metabolomics identifies novel biomarkers to distinguish tuberculosis pleural effusion from malignant pleural effusion.

BACKGROUND: Tuberculous pleural effusions (TBPEs) and malignant pleural effusions (MPEs) are two of the most common and severe forms of exudative effusions. Clinical differentiation is challenging; however, metabolomics is a collection of powerful tools currently being used to screen for disease-specific biomarkers. METHODS: 17 TBPE and 17 MPE patients were enrolled according to the inclusion criteria. The normalization gas chromatography-mass spectrometry (GC-MS) data were imported into the SIMCA-P + 14.1 software for multivariate analysis. The principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to analyze the data, and the top 50 metabolites of variable importance projection (VIP) were obtained. Metabolites were qualitatively analyzed using the National Institute of Standards and Technology (NIST) databases. Pathway analysis was performed by MetaboAnalyst 4.0. The detection of biochemical indexes such as urea and free fatty acids in these pleural effusions was also verified, and significant differences were found between these two groups. RESULTS: 1319 metabolites were screened by non-targeted metabonomics of GC-MS. 9 small molecules (urea, L-5-oxoproline, L-valine, DL-ornithine, glycine, L-cystine, citric acid, stearic acid, and oleamide) were found to be significantly different (p < 0.05 for all). In OPLS-DA, 9 variables were considered significant for biological interpretation (VIP≥1). However, after the ROC curve was performed, it was found that the metabolites with better diagnostic value were stearic acid, L-cystine, citric acid, free fatty acid, and creatinine (AUC > 0.8), with good sensitivity and specificity. CONCLUSION: Stearic acid, L-cystine, and citric acid may be potential biomarkers, which can be used to distinguish between the TBPE and the MPE.

Influence of age on the diagnostic accuracy of soluble biomarkers for tuberculous pleural effusion: a post hoc analysis.

BACKGROUND: Accurately diagnosing pleural effusion is a frequent and significant problem in clinical practice. Combining pleural biomarkers with patients' age may be a valuable method for diagnosing TPE. We sought to evaluate the influence of age on diagnostic values of pleural adenosine deaminase (ADA), interferon-gamma (IFN-γ), and interleukin 27 (IL-27) for tuberculous pleural effusion (TPE). METHODS: Two hundred seventy-four consecutive adult patients with pleural effusion were selected from Beijing and Wuhan between January 1, 2014 and June 30, 2015, and their pleural fluid concentrations of ADA, IFN-γ, and IL-27 were tested. Biomarker performance was analyzed by standard receiver operating characteristic (ROC) curves according to different ages. RESULTS: Data from the Beijing cohort showed that ADA, IFN-γ, and IL-27 could all accurately diagnose TPE in young patients (≤ 40 years of age). With a cutoff of 21.4 U/L, the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ADA for diagnosing TPE were 1.000 (95% confidence interval: 0.884-1.000), 100.0, 100.0%, 100.0, and 100.0, respectively. In older patients (> 40 years of age), IL-27 and IFN-γ were excellent biomarkers for discriminating TPE versus non-TPE cases. With a cutoff of 591.4 ng/L, the AUC, sensitivity, specificity, PPV, and NPV of IL-27 for diagnosing TPE were 0.976 (95% confidence interval: 0.932-0.995), 96.3, 99.0%, 96.3, and 99.0, respectively. Similar diagnostic accuracy among the three pleural biomarkers was validated in the Wuhan cohort. CONCLUSIONS: Among young patients, ADA is reliable for diagnosing TPE. Conversely, in older patients, IL-27 and IFN-γ are excellent biomarkers to differentiate TPE versus non-TPE cases.

Anaphylatoxins Enhance Recruitment of Nonclassical Monocytes via Chemokines Produced by Pleural Mesothelial Cells in Tuberculous Pleural Effusion.

In the present study, we sought to elucidate the mechanisms by which monocytes migrate into the pleural space in the presence of anaphylatoxins in tuberculous pleural effusion (TPE). Monocytes in both pleural effusion and blood were counted, and their phenotypic characteristics were analyzed. Activation of the complement system was detected in TPE. The effects of Mpt64 and anaphylatoxins on the production of chemokines in pleural mesothelial cells (PMCs) were measured. The chemoattractant activity of chemokines produced by PMCs for monocytes was observed. Levels of CD14+CD16+ monocytes were significantly higher in TPE than in blood. Three pathways of the complement system were activated in TPE. C3a-C3aR1, C5a-C5aR1, CCL2-CCR2, CCL7-CCR2, and CX3CL1-CX3CR1 were coexpressed in PMCs and monocytes isolated from TPE. Moreover, we initially found that Mpt64 stimulated the expression of C3a and C5a in PMCs. C3a and C5a not only induced CCL2, CCL7, and CX3CL1 expression in PMCs but also stimulated production of IL-1ß, IL-17, and IL-27 in monocytes. C3a and C5a stimulated PMCs to secrete CCL2, CCL7, and CX3CL1, which recruited CD14+CD16+ monocytes to the pleural cavity. As a result, the infiltration of CD14+CD16+ monocytes engaged in the pathogenesis of TPE by excessive production of inflammatory cytokines.

Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.

BACKGROUND: The differential diagnosis of tuberculous pleural effusion (TPE) is challenging. In recent years, artificial intelligence (AI) machine learning algorithms have started being used to an increasing extent in disease diagnosis due to the high level of efficiency, objectivity, and accuracy that they offer. METHODS: Data samples on 192 patients with TPE, 54 patients with parapneumonic pleural effusion (PPE), and 197 patients with malignant pleural effusion (MPE) were retrospectively collected. Based on 28 different features obtained via statistical analysis, TPE diagnostic models using four machine learning algorithms (MLAs), namely logistic regression, k-nearest neighbors (KNN), support vector machine (SVM) and random forest (RF) were established and their respective diagnostic performances were calculated. The respective diagnostic performances of each of the four algorithmic models were compared with that of pleural fluid adenosine deaminase (pfADA). Based on 12 features with the most significant impacts on the accuracy of the RF model, a new RF model was designed for clinical application. To demonstrate its external validity, a prospective study was conducted and the diagnostic performance of the RF model was calculated. RESULTS: The respective sensitivity and specificity of each of the four TPE diagnostic models were as follows: logistic regression - 80.5 and 84.8%; KNN- 78.6 and 86.6%; SVM - 83.2 and 85.9%; and RF - 89.1 and 93.6%. The sensitivity and specificity of pfADA were 85.4 and 84.1%, respectively, at the best cut-off value of 17.5 U/L. RF was the superior method among the four MLAs, and was also superior to pfADA. The newly designed RF model (based on 12 out of 28 features) exhibited an acceptable performance rate for the diagnosis of TPE with a sensitivity and specificity of 90.6 and 92.3%, respectively. In the prospective study, its sensitivity and specificity were 100.0 and 90.0%, respectively. CONCLUSIONS: Establishing a model for the diagnosis of TPE using RF resulted in a more effective, economical, and faster diagnostic method. This method could enable clinicians to diagnose and treat TPE more effectively.

Thrombin Upregulates PAI-1 and Mesothelial-Mesenchymal Transition Through PAR-1 and Contributes to Tuberculous Pleural Fibrosis.

Thrombin is an essential procoagulant and profibrotic mediator. However, its implication in tuberculous pleural effusion (TBPE) remains unknown. The effusion thrombin and plasminogen activator inhibitor-1 (PAI-1) levels were measured among transudative pleural effusion (TPE, n = 22) and TBPE (n = 24) patients. Pleural fibrosis, identified as radiological residual pleural thickening (RPT) and shadowing, was measured at 12-month follow-up. Moreover, in vivo and in vitro effects of thrombin on PAI-1 expression and mesothelial-mesenchymal transition (MMT) were assessed. We demonstrated the effusion thrombin levels were significantly higher in TBPE than TPE, especially greater in TBPE patients with RPT > 10mm than those without, and correlated positively with PAI-1 and pleural fibrosis area. In carbon black/bleomycin-treated mice, knockdown of protease-activated receptor-1 (PAR-1) markedly downregulated α-smooth muscle actin (α-SMA) and fibronectin, and attenuated pleural fibrosis. In pleural mesothelial cells (PMCs), thrombin concentration-dependently increased PAI-1, α-SMA, and collagen I expression. Specifically, Mycobacterium tuberculosis H37Ra (MTBRa) induced thrombin production by PMCs via upregulating tissue factor and prothrombin, and PAR-1 silencing considerably abrogated MTBRa-stimulated PAI-1 expression and MMT. Consistently, prothrombin/PAR-1 expression was evident in the pleural mesothelium of TBPE patients. Conclusively, thrombin upregulates PAI-1 and MMT and may contribute to tuberculous pleural fibrosis. Thrombin/PAR-1 inhibition may confer potential therapy for pleural fibrosis.

The diagnostic role of pentraxin-3 in the differential diagnosis of pleural effusions

Background/aim: Discrimination of pleural effusion etiology is not always easy in clinical practice. Pentraxin-3 (PTX-3) is a new acute- phase protein. The aim of this study was to investigate the role of PTX-3 in the differential diagnosis of pleural effusions. Materials and methods: This prospective study enrolled all consecutive patients from two tertiary hospitals who underwent diagnostic or therapeutic thoracentesis. In a cohort of 149 subjects with pleural effusion, including transudates and malignant (MPE), tuberculous (TPE), and parapneumonic effusion (PPE), serum and pleural effusion PTX-3 concentration measurements were performed using ELISA. Serum and pleural effusion protein, lactate dehydrogenase, C-reactive protein (CRP), and adenosine deaminase levels were also assessed. Results: Of these patients, 34 had transudates, 29 had PPE, 63 had MPE, and 23 had TPE. There was a weak correlation between pleural effusion PTX-3 level and serum CRP (P < 0.01). There was a significant difference in pleural PTX-3 levels between the exudative effusion groups (P < 0.01). The median pleural effusion PTX-3 was significantly higher in patients with PPE (11.2 ng/mL, 2­17.8) than MPE (4.7 ng/mL, 1.8­13.9) and TPE (3.1 ng/mL, 2.0­4.1). At a cut-off point of 5.89 ng/mL, PTX-3 had the best discriminatory power for PPE versus other exudative effusions (sensitivity: 86.2%, specificity: 87.7%). The exudative effusion group had a significantly different pleural effusion/serum PTX-3 ratio (P = 0.03). Conclusion: PTX-3 concentration in pleural effusion was elevated without a significant correlation with serum PTX-3 in PPE. These results may suggest that PTX-3 is a local acute-phase reactant and may allow discrimination of PPE from other exudative effusions.

Pleural fluid adenosine deaminase/serum C-reactive protein ratio for the differentiation of tuberculous and parapneumonic effusions with neutrophilic predominance and high adenosine deaminase levels.

PURPOSE: Tuberculous pleural effusion (TPE) and parapneumonic effusion (PPE) are usually distinguished by cellular predominance and pleural fluid adenosine deaminase (ADA) levels. However, both diseases may occasionally show similar neutrophilic predominance and high ADA levels. In such cases, the differential diagnosis between TPE and PPE is challenging and has been rarely investigated. METHODS: A retrospective study was conducted on TPE and PPE patients with neutrophilic exudate and pleural fluid ADA levels ≥40 U/L. Individual and combined parameters of routine blood and pleural fluid tests were compared between the two groups, and receiver operating characteristic (ROC) curves were constructed for identifying TPE. RESULTS: Thirty-six TPE and 41 PPE patients were included. White blood cell counts, serum C-reactive protein (S-CRP), and pleural fluid pH, lactate dehydrogenase, and ADA levels showed significant difference between the two groups (p < 0.001). Among multiple parameters, pleural fluid ADA/S-CRP ratio, which best reflected different local and systemic characteristics between TPE and PPE, provided the highest diagnostic accuracy with an area under the ROC curve of 0.93. At a cutoff value of 5.62, ADA/S-CRP ratio had a sensitivity of 89 %, specificity of 88 %, positive likelihood ratio of 7.29, and negative likelihood ratio of 0.13 for identifying TPE. Additionally, more than half of TPE patients had a ratio above 15.82, while none of PPE patients showed such findings. CONCLUSIONS: Pleural fluid ADA/S-CRP ratio, as a simple method using routine laboratory tests, may be helpful in discriminating between TPE and PPE patients with neutrophilic predominance and ADA ≥40 U/L.

Diagnostic value of interleukins for tuberculous pleural effusion: a systematic review and meta-analysis.

BACKGROUND: The ability of interleukins (ILs) to differentiate tuberculous pleural effusion from other types of effusion is controversial. The aim of our study was to summarize the evidence for its use of ruling out or in tuberculous pleural effusion. METHODS: Two investigators independently searched PubMed, EMBASE, Web of Knowledge, CNKI, WANFANG, and WEIPU databases to identify studies assessing diagnostic role of ILs for tuberculous pleural effusion published up to January, 2017. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. The pooled diagnostic sensitivity and specificity of ILs were calculated by using Review Manager 5.3. Area under the summary receiver operating characteristic curve (AUC) was used to summarize the overall diagnostic performance of individual markers. RESULTS: Thirty-eight studies met our inclusion criteria. Pooled sensitivity, specificity and AUC for chosen ILs were as follows: IL-2, 0.67,0.76 and 0.86; IL-6, 0.86, 0.84 and 0.90; IL-12, 0.78, 0.83 and 0.86; IL-12p40, 0.82,0.65 and 0.76; IL-18, 0.87, 0.92 and 0.95; IL-27, 0.93, 0.95 and 0.95; and IL-33, 0.84, 0.80 and 0.88. CONCLUSIONS: Some of these ILs may assist in diagnosing tuberculous pleural effusion, though no single IL is likely to show adequate sensitivity or specificity on its own. Further studies on a large scale with better study design should be performed to assess the diagnostic potential of ILs.

The pleural fluid lactate dehydrogenase/adenosine deaminase ratio differentiates between tuberculous and parapneumonic pleural effusions.

BACKGROUND: Although pleural fluid lactate dehydrogenase (LDH) and adenosine deaminase (ADA) levels are often used to distinguish between tuberculous pleural effusion (TPE) and parapneumonic pleural effusion (PPE), this can be challenging as the LDH level may vary from normal to severely increased in PPE and a significantly elevated ADA is frequently measured in both conditions. In this study, we evaluated use of the pleural fluid LDH/ADA ratio as a new parameter to discriminate TPE from PPE. METHODS: A retrospective study was conducted in patients with pathologically-confirmed TPE (n = 72) and PPE (n = 47) to compare pleural fluid LDH and ADA levels and LDH/ADA ratios between the 2 groups. A receiver operating characteristic (ROC) curve was constructed for identifying TPE. RESULTS: The median pleural fluid LDH and ADA levels and LDH/ADA ratios in the TPE and PPE groups were: 364.5 U/L vs 4037 U/L (P < .001), 33.5 U/L vs 43.3 U/L (P = .249), and 10.88 vs 66.91 (P < .0001), respectively. An area under the ROC curve of 0.9663 was obtained using the LDH/ADA ratio as the indicator for TPE identification, and the sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were, respectively, 93.62%, 93.06%, 13.48, and 0.068 at a cut-off level of 16.20. CONCLUSIONS: The pleural fluid LDH/ADA ratio, which can be determined from routine biochemical analysis, is highly predictive of TPE at a cut-off level of 16.20. Measurement of this parameter may be helpful for clinicians in distinguishing between TPE and PPE.

Diagnostic Utility Of Pleural Fluid Adenosine Deaminase Level In Tuberculous Pleural Effusion.

BACKGROUND: Early diagnosis and management of tuberculosis is essential for decreasing the disease burden. Pakistan is one of the few countries of world with a very high burden of tuberculosis. Many diagnostic tests are available for detection of tuberculosis but each is fraught with certain limitations of its own. METHODS: This study was a cross sectional validation study that sought to determine the validity of pleural fluid adenosine deaminase levels for diagnosis of tuberculous pleural effusion. RESULTS: A total of 160 patients with exudative lymphocytic pleural effusions were enrolled in this study. The mean pleural fluid ADA level was 52.18±1.98 U/L. The mean pleural fluid ADA level in patients diagnosed to have tuberculosis on pleural biopsy/histopathology was higher as compared to patients who did not have tuberculous pleural effusion 52.16±2.4 U/L vs 38.6±3.14 U/L. The difference was found to be statistically significant between the two groups (p<0.05). The sensitivity, specificity, ppv and npv of pleural fluid ADA level were 88.88%, 77.04%, 86.28% and 81.04% respectively. CONCLUSIONS: Despite wide variations in the reported sensitivity and specificity of pleural fluid ADA level, it can be used as a surrogate for pleural biopsy when the latter is not feasible.