Diagnostic Evaluation of Pleural Effusion Conditions
Summary
Pleural effusion, the accumulation of fluid in the pleural space, may reflect a broad spectrum of underlying disorders ranging from infection and malignancy to systemic diseases. Accurate characterisation of pleural fluid is essential to direct appropriate therapy and avoid unnecessary invasive procedures. Initial evaluation typically includes biochemical assays such as protein and lactate dehydrogenase (LDH) to distinguish exudative from transudative effusions, combined with cytological examination to seek malignant cells or infectious agents. Enzymatic markers, notably adenosine deaminase (ADA), have long served as cost-effective tools in identifying tuberculous pleural effusion, while more recent biomarker panels integrate enzymes or immune-related factors to enhance specificity. Advances in molecular diagnostics, including rapid nucleic acid amplification tests and metagenomic sequencing, are redefining pathogen detection and broadening the differential diagnosis. Emerging approaches employing machine-learning algorithms to integrate multiple laboratory parameters have demonstrated improved accuracy in distinguishing tuberculous, malignant and parapneumonic effusions. Taken together, these developments underscore a trend towards multimodal, minimally invasive strategies that balance diagnostic yield with timeliness and global applicability.
Research from Nature Portfolio
No recent Nature Portfolio content available.
Diagnostic Evaluation of Pleural Effusion Conditions publication trend
The graph below shows the total number of articles in diagnostic evaluation of pleural effusion conditions across all publications each year (not limited to Nature Index journals).
Technical terms
Pleural effusion: Accumulation of fluid between the lung and chest wall pleura.
Exudative effusion: Pleural fluid rich in protein and LDH, indicating local pleural pathology.
Adenosine deaminase (ADA): Enzyme whose elevated activity suggests tuberculous pleural inflammation.
Lactate dehydrogenase (LDH): Cellular enzyme used to classify effusions and assess tissue turnover.
Biomarker: Measurable substance indicating a specific disease state or condition.
Metagenomic next-generation sequencing (mNGS): Unbiased sequencing of all nucleic acid in a sample to detect pathogens.
Machine-learning model: Computational algorithm that integrates multiple variables to improve diagnostic accuracy.
References
- Granzyme A as biomarker for diagnosis in tuberculous pleural effusion. JCI Insight (2024).
- Complement regulatory proteins: Candidate biomarkers in differentiating tuberculosis pleural effusion. Frontiers in Immunology (2023).
- Diagnostic accuracy and microbial profiles of tuberculous pleurisy: a comparative study of metagenomic next generation sequencing and GeneXpert Mycobacterium tuberculosis. Frontiers in Cellular and Infection Microbiology (2023).
About these summaries
This Nature Research Intelligence Topic summary is created with the cited references and a large language model. We take care to ground generated text with facts, and have systems in place to gain human feedback on the overall quality of the process in line with our AI principles. We strive to create accurate and useful summaries for people unfamiliar with the research topic and that supports this goal. These pages are a beta release and will be updated as we learn how best to help people gain value from a research topic summary.
Turn complex research questions into confident strategic decisions
When you're under pressure to set direction, justify investment, or understand your competitive position, you need more than raw data — you need trusted insights you can act on.
Benchmark your performance against global peers using robust, methodologically sound analysis.
Combine quantitative metrics with qualitative expert insight to uncover strengths, gaps and emerging opportunities.
Gain tailored, decision-ready recommendations aligned to your strategic priorities.
Talk to us to learn more about our data dashboards and bespoke strategy reports.
Grow research skills, confidence and careers with training built for every stage of the research lifecycle.
Developed with Nature Portfolio journal Editors and internationally renowned experts. Discover three ways to learn:
Self-paced, online courses in convenient bite-sized units, covering key skills across scientific writing, publishing, grant writing, data analysis, and more.
Expert trainer-led workshops with hands-on exercises and real-time feedback across core research skills, delivered via interactive group sessions.
Editor-led workshops combining core principles in writing and publishing, personalised 1:1 feedback from Nature Portfolio Editors and hands-on exercises.
Explore course catalogues and workshop agendas, enquire about the options or request institutional pricing.