Applied value of monitoring serum hepcidin in differential diagnosis of infection versus tumor fevers

Increased serum levels of hepcidin and C-reactive protein in patients with brucellosis

Background

Increased serum level of C-reactive protein (CRP) as a classic acute phase protein has commonly been reported in acute brucellosis. Hepcidin is also an acute phase protein and has a critical role in host defense. The aim of this study was to compare the level of hepcidin and CRP in patients with brucellosis.

Methods

All patients with brucellosis referred to Sina Hospital during a 10-month period were included. Serum samples were checked for hepcidin levels in patients and also in the control group. Information on demographic and clinical characteristics was determined through completion of a questionnaire.

Results

A total of 42 patients with brucellosis and 42 healthy controls were enrolled. The most common symptoms of brucellosis were fever (76%) and arthralgia (69%). The mean serum level of hepcidin in patients (42.6±11.7 pg/mL) was significantly higher than in the controls (17.3±4.2 pg/mL) (p<0.001). The mean serum levels of CRP in patients and controls were 12.6±12.2 and 3.1±2.4 mg/L, respectively (p=0.001).

Conclusions

Increased serum levels of hepcidin in brucellosis can be considered a diagnostic biomarker of inflammation and active disease. Further studies are needed to identify the role of hepcidin as a host defense mechanism in brucellosis.

Establishment of a Predictive Model Related to Pathogen Invasion for Infectious Diseases and Its Diagnostic Value in Fever of Unknown Origin

The present study aimed to establish a list of parameters indicative of pathogen invasion and develop a predictive model to distinguish the etiologies of fever of unknown origin (FUO) into infectious and non-infectious causes. From January 2014 to September 2017, 431 patients with FUO were prospectively enrolled in the study population. This study established a list of 26 variables from the following 4 aspects: host factors, epidemiological factors, behavioral factors, and iatrogenic factors. Predefined predicted variables were included in a multivariate logistic regression analysis to develop a predictive model. The predictive model and the corresponding scoring system were developed using data from the confirmed diagnoses and 9 variables were eventually identified. These factors were incorporated into the predictive model. This model discriminated between infectious and non-infectious causes of FUO with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.63. The predictive model and corresponding scoring system based on factors concerning pathogen invasion appear to be reliable screening tools to discriminate between infectious and non-infectious causes of FUO.