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Updated: Sep 28, 2026

A Periprosthetic Joint Candida albicans Infection Model in Mouse
Published on: February 2, 2024
Heparin-binding protein as an emerging host-response biomarker for periprosthetic joint infection: a narrative review
Qirui Chen1,2, Khalid Waleed1,2, Ai Peng3
1Department of Orthopedics, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Background:
Joint infections, including periprosthetic joint infection (PJI), remain difficult to diagnose because conventional markers such as C-reactive protein, erythrocyte sedimentation rate, white blood cell count, and procalcitonin may lack specificity, particularly after surgery or in inflammatory conditions. Heparin-binding protein (HBP), also known as azurocidin 1, is a neutrophil-derived mediator that is rapidly released during bacterial infection and may provide additional diagnostic value.
Methods:
A narrative review was conducted using major English- and Chinese-language databases to identify clinical studies evaluating HBP in PJI, musculoskeletal infection, systemic infection, or infection-versus-inflammation settings. Studies reporting diagnostic performance measures, including area under the receiver operating characteristic curve, sensitivity, specificity, or cutoff values, were included.
Results:
HBP concentrations were generally higher in infected patients than in non-infected or inflammatory controls. Across included studies, reported HBP AUC values ranged from 0.693 to 0.968. In PJI, serum HBP showed AUCs of 0.856 and 0.968 in available studies, whereas synovial fluid HBP showed more modest individual accuracy. HBP also demonstrated value in differentiating bacterial infection from sterile inflammatory disease, including rheumatoid arthritis with superimposed bacterial infection.
Conclusion:
HBP is a biologically plausible adjunctive biomarker for the diagnosis of bacterial infection and PJI. However, current evidence remains heterogeneous, and further large-scale prospective studies are needed to standardize cutoff values and clarify its role in diagnostic algorithms.

