What is the significance of adenosine deaminase (ADA) levels in pleural fluid?

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Last updated: May 11, 2025View editorial policy

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From the Guidelines

Adenosine deaminase (ADA) testing in pleural fluid is a valuable diagnostic tool primarily used to detect tuberculous pleuritis, with an ADA level greater than 40 U/L strongly suggesting tuberculosis as the cause of pleural effusion. This test is particularly useful in regions with high TB prevalence or when TB is clinically suspected, as it provides rapid results compared to TB cultures and is relatively inexpensive 1. The test works because Mycobacterium tuberculosis infection triggers a cell-mediated immune response that releases ADA from activated T lymphocytes and macrophages into the pleural space. Some key points to consider when interpreting ADA results include:

  • Elevated ADA levels are highly suggestive of TB, but can occasionally be seen in other conditions such as empyema, lymphoma, rheumatoid arthritis, and some bacterial pneumonias 1.
  • ADA results should be interpreted alongside clinical presentation, other pleural fluid analyses (including acid-fast bacilli staining and culture), and imaging findings 1.
  • The sensitivity and specificity of an elevated ADA level in pleural fluid are estimated to be around 89% and 97%, respectively, although these values can vary depending on the threshold used to define an elevated ADA level 1.
  • Measuring ADA levels in pleural fluid is a recommended practice for diagnosing pleural TB, according to the official American Thoracic Society/Infectious Diseases Society of America/Centers for Disease Control and Prevention clinical practice guidelines 1.

From the Research

Adenosine Deaminase in Pleural Fluid

  • Adenosine deaminase (ADA) is an enzyme found in pleural fluid that can be used as a diagnostic marker for various conditions, including tuberculous pleuritis and malignant pleural effusion 2, 3, 4, 5, 6.
  • The level of ADA in pleural fluid can help differentiate between tuberculous and non-tuberculous pleural effusions, with higher levels typically indicating tuberculous pleuritis 2, 5, 6.
  • A cut-off value of 35-40 U/L is often used to distinguish between tuberculous and non-tuberculous pleural effusions, with sensitivity and specificity ranging from 85-93% and 86-90%, respectively 2, 6.

Diagnostic Accuracy

  • The diagnostic accuracy of ADA in pleural fluid can be improved by combining it with other parameters, such as pH, glucose, and lactate dehydrogenase levels, as well as machine learning algorithms 3.
  • In a low-prevalence setting, the use of ADA in combination with other parameters and machine learning algorithms can achieve an area under the curve (AUC) of 0.98 and an accuracy of 97% for diagnosing tuberculous pleuritis 3.

Malignant Pleural Effusion

  • ADA levels in pleural fluid can also be used to predict survival in patients with malignant pleural effusion, with abnormal levels (<15 or ≥40 U/L) associated with worse survival 4.
  • However, ADA levels can be elevated in non-tuberculous conditions, such as lung cancer and mesothelioma, which can lead to false-positive results 6.

Geographical Variations

  • The utility of ADA in pleural fluid for diagnosing tuberculous pleuritis may vary depending on the geographical region and the prevalence of tuberculosis 6.
  • In countries with intermediate incidence of tuberculosis, such as Japan, the use of ADA in pleural fluid may be less specific due to the higher prevalence of non-tuberculous conditions with elevated ADA levels 6.

Professional Medical Disclaimer

This information is intended for healthcare professionals. Any medical decision-making should rely on clinical judgment and independently verified information. The content provided herein does not replace professional discretion and should be considered supplementary to established clinical guidelines. Healthcare providers should verify all information against primary literature and current practice standards before application in patient care. Dr.Oracle assumes no liability for clinical decisions based on this content.

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