Significance of Pleural Fluid Neutrophil-Lymphocyte Ratio and Pleural Fluid Protein as Additional Biomarkers in Differentiating Tubercular Pleural Effusions From Non-tubercular Effusions

Background: Tubercular pleural effusion (TPE) remains a significant diagnostic challenge in tuberculosis-endemic regions. Current diagnostic methods have substantial limitations, necessitating the investigation of complementary biomarkers. Objectives: The primary objective of this study was to evaluate the diagnostic utility of pleural fluid neutrophil-lymphocyte ratio (NLR) and pleural fluid protein as adjunctive biomarkers, in combination with adenosine deaminase (ADA), for differentiating TPEs from non-tubercular effusions (NTEs). The secondary objective was to assess their potential clinical utility as simple, cost-effective adjuncts in routine diagnostic practice. Methods: A case-control study involving 50 patients (25 TPE cases, 25 NTE controls) was conducted at Vinayaka Missions Medical College and Hospital over 18 months. Pleural fluid was analyzed for protein concentration, cell counts (for NLR calculation), ADA levels, and Mycobacterium tuberculosis detection using CBNAAT (GeneXpert MTB/RIF assay; Cepheid, Sunnyvale, California, USA). Results: Mean pleural fluid NLR was significantly elevated in TPE (1.63 ± 6.37) versus NTE controls (0.77 ± 2.06; p = 0.047). Pleural fluid protein showed marked elevation in TPE patients (4.67 ± 2.36 g/dL) versus controls (2.90 ± 1.85 g/dL; p = 0.014). Pleural ADA demonstrated superior discrimination (TPE: 84.95 ± 21.10 U/L versus NTE: 21.45 ± 15.78 U/L; p < 0.0001). Combined analysis of elevated pleural protein, elevated NLR, and elevated ADA provided enhanced diagnostic accuracy: sensitivity: 96%, specificity: 92%, positive predictive value: 95%, and negative predictive value: 94%. Conclusion: Pleural fluid protein and NLR serve as useful adjunctive biomarkers in the diagnostic evaluation of pleural effusions. When combined with ADA, these readily available, cost-effective parameters substantially enhance diagnostic accuracy for differentiating TPEs from NTEs.