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Comparative Study
. 2018 Jun 11;8(1):8802.
doi: 10.1038/s41598-018-27198-3.

Fibrinogen - A Practical and Cost Efficient Biomarker for Detecting Periprosthetic Joint Infection

S M Klim  1 , F Amerstorfer  1 , G Gruber  2 , G A Bernhardt  1 , R Radl  1 , L Leitner  1 , A Leithner  1 , M Glehr  1
Affiliations
Comparative Study

Fibrinogen - A Practical and Cost Efficient Biomarker for Detecting Periprosthetic Joint Infection

S M Klim et al. Sci Rep. .

Erratum in

Abstract

The early and accurate diagnosis of periprosthetic joint infection (PJI) can be challenging. Fibrinogen plays an important role in mediating inflammation of bacterial infections and therefore could be a valuable biomarker for PJI. The purpose of this study was to investigate the sensitivity and specificity of serum levels of fibrinogen in detecting PJI, and to compare the results with the established PJI biomarkers C-reactive protein (CRP) and leukocyte count. Eighty-four patients (124 surgeries) were prospectively included. The preoperatively analyzed parameters were fibrinogen, CRP and leukocyte count. The sensitivity and specificity of the biomarkers were calculated and compared. Fibrinogen (p < 0.001), CRP (p < 0.001) and leukocyte count (p < 0.001) had a statistically significant correlation with the criteria defining the presence of PJI. For fibrinogen, the value of 519 mg/dl had a sensitivity of 0.90 and a specificity of 0.34. The CRP cut-off point of 11.00 mg/dl had a sensitivity of 0.90 and a specificity of 0.74. The leukocyte count of 5.68 G/l had a sensitivity of 0.90 and a specificity of 0.39. Our results indicated that fibrinogen is a significant biomarker for detecting a bacterial PJI. It has shown to be a cost-efficient diagnostic support with high sensitivity and specificity.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Recruitment of study patients.
Figure 2
Figure 2
ROC curve showing the PJI predictive value of fibrinogen. (A) leucocytes (B) and CRP (C) for all operations. The ROC curve is a graphic plot of the positive rate (sensitivity) versus the false positive rate (specificity).
See this image and copyright information in PMC

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