Utility of a Simple Scoring System in Differentiating Bacterial Infections in Cases of Fever of Unknown Origin
Xu Teng, Li Wang, Shi Wu, Fenfen Zhou, Haihui Huang
Abstract
BACKGROUND: Infectious disease is the leading cause of fever of unknown origin (FUO). Serum inflammatory markers historically used to diagnose bacterial infection have sufficient diagnostic sensitivity but low specificity. This study aimed to develop a simple scoring system for differentiating bacterial infections from other causes of early-stage FUO. METHODS: This study included a retrospective cohort of patients presenting with FUO at the Huashan Hospital (January 2014 to June 2017). The diagnostic utility of serum inflammatory markers for bacterial infection was evaluated using the receiver operating characteristic (ROC) curve analysis. Relevant markers were subsequently measured prospectively in a separate cohort of FUO patients (December 2017 to May 2019). A scoring system was based on inflammatory markers and other test results. RESULTS: Bacterial infection was identified in 34% of patients in the retrospective cohort. The area under the ROC curve (AUC) was 0.644 (95% confidence interval [CI], .595-.693) for C-reactive protein, 0.624 (95% CI, .573-.675) for procalcitonin, and 0.646 (95% CI, .595-.697) for serum ferritin (SF) in diagnosing bacterial infection. Bacterial infection was found in 29% of cases in the prospective cohort. A model based on serum amyloid A (SAA) and SF levels and neutrophil percentage yielded an AUC of 0.775 (95% CI, .695-.854). Validation analysis indicated lower probability (<15%) of bacterial infection for patients with a score <16.5 points. CONCLUSIONS: A scoring system based on SAA and SF levels and neutrophil percentage can help distinguish bacterial infection from other causes of FUO, potentially reducing antibiotic use.