A diagnostic algorithm for tuberculous pleurisy using the ELISPOT assay on peripheral blood and pleural effusion

Abstract

Background: Diagnosis of tuberculous (TB) pleurisy remains challenging due to the paucibacillary nature of the disease. We prospectively assessed the diagnostic usefulness of the T-cell based ELISPOT assay, and created a clinical algorithm for differentiating TB pleurisy from other diagnoses.

Methods: All adult patients with suspicion for TB pleurisy were enrolled in a tertiary hospital in Seoul, South Korea, over a 7-year period. ELISPOT assays were performed using mononuclear cells from peripheral blood and pleural effusion.

Results: Seventy-seven patients with suspected TB pleurisy were enrolled. Of these, 33 (43%) patients, comprising 27 confirmed and 6 probable TB pleurisy, were classified as TB pleurisy, and 36 (47%) were classified as not TB. The remaining 8 with possible TB pleurisy were excluded from the final analysis. The sensitivities and specificities, respectively, of the diagnostic methods were as follows: pleural fluid adenosine deaminase (ADA) level 32 U/L, 81% and 79%; peripheral blood mononuclear cells (PBMC) ELISPOT assay, 82% and 73%; pleural effusion-mononuclear cells (PE-MC) ELISPOT assay, 58% and 87%. When the diagnostic algorithm was applied, PBMC ELISPOT ≥6 spots or ADA ≥32 U/L’ as a rule-out test safely excluded 46% (12/26) of the not TB patients, and ‘PE-MC ≥6 spots’ as a rule-in test accurately classified 23% (7/31) of the patients with TB pleurisy.

Conclusions: A diagnostic algorithm combining ELISPOT assays and ADA levels in pleural fluid appears to be a promising and non-invasive approach for patients with suspected TB pleurisy.

Keywords:

• Diagnosis
• ELISPOT
• TB-specific T lymphocytes
• tuberculous pleurisy

Disclosure statement

There are no potential conflicts of interest for any authors.

Funding information

This work was supported by grants from the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (NRF-2013R1A1A1A05004354) and by the Ministry of Education (grant NRF-2015R1D1A1A01059315) and the Asan Institute For Life Sciences (2015-1004).