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Ann Am Thorac Soc. 2014 Feb;11(2):243-53. doi: 10.1513/AnnalsATS.201308-286FR.

Update on the diagnosis of pulmonary coccidioidomycosis.

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1
1 Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine,and.

Abstract

Coccidioidomycosis is a common cause of community-acquired pneumonia in the southwest United States, Mexico, and South America. The disease has seen a marked increase in incidence in the western United States in the last decade and can be acquired by individuals who travel even briefly through an endemic area, presenting a diagnostic dilemma for clinicians who are not familiar with the disease. The clinical and radiographic manifestations of pulmonary coccidioidomycosis often mimic those of other causes of pneumonia. However, because treatment recommendations and the potential for chronic sequelae of acute infection differ substantially from those for bacterial community-acquired pneumonia, accurate, timely diagnosis of coccidioidomycosis is paramount. A number of diagnostic tests are available with varying sensitivity and specificity, making the approach complex. Radiographic features, although nonspecific, sometimes demonstrate patterns more suggestive of coccidioidomycosis than bacterial community-acquired pneumonias. A routine blood count may reveal eosinophilia. Serologic testing is used most widely but may be negative early in the course of disease, potentially leading to misdiagnosis with subsequent inappropriate treatment and follow-up. The sensitivity of serologic testing is lower in immunocompromised patients, a population at the highest risk for developing severe disease. When clinically appropriate, other biologic specimens, such as sputum, bronchoalveolar lavage fluid, or lung biopsies, may allow for rapid, definitive diagnosis. In light of the significantly increased incidence and complexities in diagnosis of coccidioidomycosis, we examine the diagnostic approach and provide examples of classic clinical and radiographic presentations, discuss the utility of serologic testing, and suggest algorithms that may aid in the diagnosis.

PMID:
24575994
DOI:
10.1513/AnnalsATS.201308-286FR
[Indexed for MEDLINE]

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