Diagnostic Yield of Routine Pericardial Fluid Cultures and Clinical Predictors of Bacterial Pericarditis

Background: Pericardial effusion has a broad differential diagnosis, whereas bacterial pericarditis is rare. Despite this, routine culturing of pericardial fluid is frequently performed, and its diagnostic yield remains uncertain. Methods: We conducted a retrospective study of all pericardial fluid cultures obtained at a tertiary medical center between January 2016 and May 2024. Cultures were classified as true positive if a recognized bacterial pathogen was isolated or if it was deemed clinically pathogenic by an infectious disease’s specialist at the medical record. Contaminants were defined according to CDC criteria. Clinical, laboratory, and imaging variables were analyzed using univariate testing and multivariable logistic regression. Results: Among 198 eligible pericardial fluid cultures, 8 (4%) yielded true bacterial pathogens, whereas 43 (23%) grew contaminants and 147 (73%) remained sterile. Thus, contaminant growth occurred more than five times as frequently as that of true pathogens. The most frequent pathogens were Staphylococcus aureus and Streptococcus species. No demographic features, presenting symptoms, or imaging findings were associated with culture positivity. In multivariable analysis, concurrent bacteremia (odds ratio [OR] 17.49; p = 0.002) and higher peripheral neutrophil percentage (OR 1.20; p = 0.012) independently predicted bacterial pericarditis. In models incorporating pericardial fluid cell counts, a lower mononuclear cell percentage was also independently associated with infection (OR 0.91; p = 0.03). Conclusions: Bacterial pericarditis is uncommon, and routine pericardial fluid cultures, of all pericardial fluid specimens, have a low diagnostic yield with substantial contamination. Laboratory markers, particularly bacteremia and neutrophilia, may help identify patients most likely to benefit from culture. A selective, laboratory-guided approach may improve diagnostic efficiency and reduce unnecessary testing.