Clinical and serological approach to patients with brucellosis: A common diagnostic dilemma and a worldwide perspective

Microb Pathog. 2019 Apr:129:125-130. doi: 10.1016/j.micpath.2019.02.011. Epub 2019 Feb 10.

Abstract

According to the WHO factsheet, although approximately half a million brucellosis cases are reported annually, the true incidence is always 10-25 times higher than the reported number of cases. Therefore, we face a common yet uncommonly recognized entity of brucellosis, which highlights the importance of providing precise and understandable guidelines for physician to recognize and manage the disease. Up to now, there is no distinct and clear guideline for brucellosis diagnosis. Hence, this article presents for the first time an algorithm based on our 30 years clinical experiences for brucellosis diagnosis. There are several serological patterns of brucellosis due to the insidious nature and serologic response of this disease. In contrast to most infectious diseases, the IgM response to brucellosis remains after the acute phase, IgG responses often fade after improvement and there is no lifelong positivity for IgG antibody. This diversity of serological pattern leads to seven clinical subtypes of the disease; three of those do not need any medical intervention. In endemic regions, this issue makes a challenging diagnostic puzzle for clinicians, which may consequently lead to national and international over- or underestimation of brucellosis incidence. On one hand, this may change the epidemiological landscape of brucellosis. On the other hand, drugs used in therapy are often accompanied by serious or sometimes irreversible side effects. Accordingly, we attempt to create a unique template to better identify these seven serological patterns and give a comprehensive insight into the diagnostic approach to brucellosis. Moreover, we describe in detail the appropriate use of wright, 2 ME, Coomb's WRIGHT, and ELISA tests.

Keywords: Algorithm; Antibody; Approach; Brucellosis; Diagnosis; Management; Serology.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Antibodies, Bacterial / blood
  • Brucellosis / diagnosis*
  • Brucellosis / pathology*
  • Humans
  • Immunoassay / methods*
  • Immunoglobulin G / blood
  • Immunoglobulin M / blood
  • Serologic Tests / methods*

Substances

  • Antibodies, Bacterial
  • Immunoglobulin G
  • Immunoglobulin M