ASSESSMENT OF LDH/ADA RATIO IN PATIENTS WITH AND WITHOUT TUBERCULAR PLEURAL EFFUSION

Background: Tubercular pleural effusion (TPE) is a common manifestation of extrapulmonary tuberculosis, especially in high-burden countries. The diagnostic evaluation typically includes pleural fluid adenosine deaminase (ADA) and lactate dehydrogenase (LDH) levels. Recent studies suggest that the LDH/ADA ratio may enhance diagnostic accuracy and help differentiate TPE from other etiologies. Aim: To assess the LDH/ADA ratio in patients with confirmed tubercular pleural effusion and evaluate its diagnostic utility. Methods: This cross-sectional study included 100 patients with exudative pleural effusion, of which 70 had confirmed TPE based on microbiological, histopathological, or clinical criteria, and 30 had non-tubercular exudative effusion. Pleural fluid ADA, LDH, and LDH/ADA ratio were measured. Statistical analysis included ROC curve analysis, sensitivity, specificity, and predictive values. Results: Mean ADA levels in TPE patients were significantly higher than in non-TPE cases (p<0.001). LDH levels were elevated in both groups, but the LDH/ADA ratio was significantly lower in TPE patients (mean 12.4 ± 4.1) compared to non-TPE patients (mean 28.6 ± 5.9, p<0.001). ROC analysis showed an LDH/ADA ratio cut-off of ≤16.0 had a sensitivity of 91.4% and specificity of 88.3% for diagnosing TPE.  Conclusion: The LDH/ADA ratio is a simple, cost-effective, and valuable adjunctive tool in differentiating tubercular pleural effusion from other exudative pleural effusions.

Authors

Publication Details

Published
2025-08-13
DOI
https://doi.org/10.53555/y3s2fk44
Primary Topic
Pleural and Pulmonary Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ASSESSMENT OF LDH/ADA RATIO IN PATIENTS WITH AND WITHOUT TUBERCULAR PLEURAL EFFUSION

Rajeev Kumar Jaiswal
Pleural and Pulmonary Diseases
article

ASSESSMENT OF LDH/ADA RATIO IN PATIENTS WITH AND WITHOUT TUBERCULAR PLEURAL EFFUSION

Rajeev Kumar Jaiswal
article en

Abstract

Background: Tubercular pleural effusion (TPE) is a common manifestation of extrapulmonary tuberculosis, especially in high-burden countries. The diagnostic evaluation typically includes pleural fluid adenosine deaminase (ADA) and lactate dehydrogenase (LDH) levels. Recent studies suggest that the LDH/ADA ratio may enhance diagnostic accuracy and help differentiate TPE from other etiologies. Aim: To assess the LDH/ADA ratio in patients with confirmed tubercular pleural effusion and evaluate its diagnostic utility. Methods: This cross-sectional study included 100 patients with exudative pleural effusion, of which 70 had confirmed TPE based on microbiological, histopathological, or clinical criteria, and 30 had non-tubercular exudative effusion. Pleural fluid ADA, LDH, and LDH/ADA ratio were measured. Statistical analysis included ROC curve analysis, sensitivity, specificity, and predictive values. Results: Mean ADA levels in TPE patients were significantly higher than in non-TPE cases (p<0.001). LDH levels were elevated in both groups, but the LDH/ADA ratio was significantly lower in TPE patients (mean 12.4 ± 4.1) compared to non-TPE patients (mean 28.6 ± 5.9, p<0.001). ROC analysis showed an LDH/ADA ratio cut-off of ≤16.0 had a sensitivity of 91.4% and specificity of 88.3% for diagnosing TPE.  Conclusion: The LDH/ADA ratio is a simple, cost-effective, and valuable adjunctive tool in differentiating tubercular pleural effusion from other exudative pleural effusions.

Zero hunger
Openalex Percentile: Top 68%
Pleural and Pulmonary Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.