Objectives. The diagnosis of periprosthetic joint infection (PJI) is difficult and requires a battery of tests and clinical findings. The purpose of this review is to summarize all current evidence for common and new serum biomarkers utilized in the diagnosis of PJI. Methods. We searched two literature databases, using terms that encompass all hip and knee arthroplasty procedures, as well as PJI and statistical terms reflecting diagnostic parameters. The findings are summarized as a narrative review. Results. Erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were the two most commonly published serum biomarkers. Most evidence did not identify other serum biomarkers that are clearly superior to ESR and CRP. Other serum biomarkers have not demonstrated superior sensitivity and have failed to replace CRP and ESR as first-line screening tests. D-dimer appears to be a promising biomarker, but more research is necessary. Factors that influence serum biomarkers include temporal trends, stage of revision, and implant-related factors (metallosis). Conclusion. Our review helped to identify factors that can influence serum biomarkers’ level changes; the recognition of such factors can help improve their diagnostic utility. As such, we cannot rely on ESR and CRP alone for the diagnosis of PJI prior to second-stage reimplantation, or in metal-on-metal or corrosion cases. The future of serum biomarkers will likely shift towards using genomics and proteomics to identify proteins transcribed via messenger RNA in response to infection and sepsis. Cite this article: A. Saleh, J. George, M. Faour, A. K. Klika, C. A. Higuera. Serum biomarkers in periprosthetic joint infections. Bone Joint Res 2018;7:85–93. DOI: 10.1302/2046-3758.71.BJR-2017-0323

Aims

Osteoporosis is common in total hip arthroplasty (THA) patients. It plays a substantial factor in the surgery’s outcome, and previous studies have revealed that pharmacological treatment for osteoporosis influences implant survival rate. The purpose of this study was to examine the prevalence of and treatment rates for osteoporosis prior to THA, and to explore differences in osteoporosis-related biomarkers between patients treated and untreated for osteoporosis.